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| Subset
| tabledap
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| Info
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| Dataset ID
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323
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|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20180323)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180323
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20180323)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180323
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427
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|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20180427)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20180427
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427
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|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20180427)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20180427
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20181128)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20181128
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20181128)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20181128
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190221)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190221
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190221)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190221
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190417)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190417
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190417)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190417
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190726)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20190726
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20190726)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20190726
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20200206)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200206
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20200206)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200206
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20200710)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20200710
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20200710)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20200710
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220307)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220307
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220307)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220307
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220411)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220411
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220411)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220411
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220511)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220511
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220511)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220511
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220824)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20220824
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20220824)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20220824
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20221028)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20221028
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20221028)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20221028
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20230506)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230506
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20230506)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230506
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20230526)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20230526
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20230526)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20230526
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20231207)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20231207
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20231207)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20231207
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240510)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240510
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240510)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240510
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240604)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240604
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240604)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240604
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240719)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240719
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240719)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_portofino_20240719
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729/
| Estimated chlorophyll-a concentration at 60 m spatial resolution - Mondrian forest (20240729)
| The dataset consists of estimated chlorophyll-a (CHL-a) concentration maps obtained as the output of a machine learning model. Multispectral data from twelve bands of the Sentinel-2 mission of the Copernicus Programme of the European Union, together with in situ CHL-a measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework.\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_chl\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_chlorophyll_final_output_MondrianForest_laspezia_20240729
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220307T093204Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220307T093204
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220411T092437Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220411T092437
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220428T094504Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220428T094504
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220510T101316Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220510T101316
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220511T094705Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220511T094705
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220701T092437Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220701T092437
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220716T093548Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220716T093548
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220719T095813Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220719T095813
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220824T092429Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220824T092429
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20220913T090551Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20220913T090551
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20221005T093545Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20221005T093545
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20221007T094510Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20221007T094510
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20221028T093930Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20221028T093930
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20221111T101653Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20221111T101653
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230213T093929Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230213T093929
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230304T094657Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230304T094657
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230417T090555Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230417T090555
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230505T093934Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230505T093934
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230523T101313Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230523T101313
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230524T094702Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230524T094702
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230626T095250Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230626T095250
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230711T100406Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230823T094909Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230823T094909
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230927T094136Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20230927T094136
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20231009T093025Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T093025
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20231009T100922Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20231009T100922
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20231207T093924Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20231207T093924
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240221T100924Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240221T100924
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240307T094141Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240307T094141
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240424T093547Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240424T093547
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240527T102041Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240527T102041
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240607T095649Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240607T095649
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240618T101146Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240618T101146
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240719T090552Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T090552
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240719T100805Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240719T100805
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240729T090814Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T090814
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659
|
|
| https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659.graph
|
| https://erddap.s4raise.it/erddap/files/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659/
| Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20240729T094659Z)
| The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework\n\ncdm_data_type = Grid\nVARIABLES (all of which use the dimensions [latitude][longitude]):\nestimated_sst\n
| https://erddap.s4raise.it/erddap/metadata/fgdc/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659_fgdc.xml
| https://erddap.s4raise.it/erddap/metadata/iso19115/xml/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659_iso19115.xml
| https://erddap.s4raise.it/erddap/info/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659/index.htmlTable
| https://www.raiseliguria.it/spoke-3/
| https://erddap.s4raise.it/erddap/rss/unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659&showErrors=false&email=
| UNIGE-DITEN
| unige-diten_sea_surface_temperature_final_output_MondrianForest_20240729T094659
|
|
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_bonassola.subset
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_bonassola
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_bonassola.graph
|
| https://erddap.s4raise.it/erddap/files/ingv-lasomma_srs_rainfall_bonassola/
| Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Bonassola
| The SRS (Smart Rainfall System) dataset originates from a dense network of microwave sensors designed for satellite down-links and developed by the University of Genoa together with Artys and Darts Engineering (Genoa, Italy). By analysing the attenuation of satellite signals received by standard parabolic antennas, the system retrieves real-time estimates of rainfall intensity along each observation link and produces high-resolution precipitation maps over the monitored area. The resulting dataset provides continuous time series of rainfall intensity and cumulative precipitation (15 minutes, 1-2-8-12, 24 hours), enabling detailed spatio-temporal characterization of rainfall dynamics.\n\ncdm_data_type = Grid\nVARIABLES:\ntime (seconds since 1970-01-01T00:00:00Z)\nsrs_id\nsrs_sat_id\nrain_level\n
|
|
| https://erddap.s4raise.it/erddap/info/ingv-lasomma_srs_rainfall_bonassola/index.htmlTable
| https://indra.artys.it/INGVRAISE/index.html
| https://erddap.s4raise.it/erddap/rss/ingv-lasomma_srs_rainfall_bonassola.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=ingv-lasomma_srs_rainfall_bonassola&showErrors=false&email=
| INGV, Darts Engineering Srl
| ingv-lasomma_srs_rainfall_bonassola
|
|
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_genova.subset
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_genova
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_genova.graph
|
| https://erddap.s4raise.it/erddap/files/ingv-lasomma_srs_rainfall_genova/
| Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Genova
| The SRS (Smart Rainfall System) dataset originates from a dense network of microwave sensors designed for satellite down-links and developed by the University of Genoa together with Artys and Darts Engineering (Genoa, Italy). By analysing the attenuation of satellite signals received by standard parabolic antennas, the system retrieves real-time estimates of rainfall intensity along each observation link and produces high-resolution precipitation maps over the monitored area. The resulting dataset provides continuous time series of rainfall intensity and cumulative precipitation (15 minutes, 1-2-8-12, 24 hours), enabling detailed spatio-temporal characterization of rainfall dynamics.\n\ncdm_data_type = Grid\nVARIABLES:\ntime (seconds since 1970-01-01T00:00:00Z)\nsrs_id\nsrs_sat_id\nrain_level\n
|
|
| https://erddap.s4raise.it/erddap/info/ingv-lasomma_srs_rainfall_genova/index.htmlTable
| https://indra.artys.it/INGVRAISE/index.html
| https://erddap.s4raise.it/erddap/rss/ingv-lasomma_srs_rainfall_genova.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=ingv-lasomma_srs_rainfall_genova&showErrors=false&email=
| INGV, Darts Engineering Srl
| ingv-lasomma_srs_rainfall_genova
|
|
|
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_laspezia
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_laspezia.graph
|
| https://erddap.s4raise.it/erddap/files/ingv-lasomma_srs_rainfall_laspezia/
| Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - La Spezia
| The SRS (Smart Rainfall System) dataset originates from a dense network of microwave sensors designed for satellite down-links and developed by the University of Genoa together with Artys and Darts Engineering (Genoa, Italy). By analysing the attenuation of satellite signals received by standard parabolic antennas, the system retrieves real-time estimates of rainfall intensity along each observation link and produces high-resolution precipitation maps over the monitored area. The resulting dataset provides continuous time series of rainfall intensity and cumulative precipitation (15 minutes, 1-2-8-12, 24 hours), enabling detailed spatio-temporal characterization of rainfall dynamics.\n\ncdm_data_type = Grid\nVARIABLES:\ntime (seconds since 1970-01-01T00:00:00Z)\nsrs_id\nsrs_sat_id\nrain_level\n
|
|
| https://erddap.s4raise.it/erddap/info/ingv-lasomma_srs_rainfall_laspezia/index.htmlTable
| https://indra.artys.it/INGVRAISE/index.html
| https://erddap.s4raise.it/erddap/rss/ingv-lasomma_srs_rainfall_laspezia.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=ingv-lasomma_srs_rainfall_laspezia&showErrors=false&email=
| INGV, Darts Engineering Srl
| ingv-lasomma_srs_rainfall_laspezia
|
|
|
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_livorno
| https://erddap.s4raise.it/erddap/tabledap/ingv-lasomma_srs_rainfall_livorno.graph
|
| https://erddap.s4raise.it/erddap/files/ingv-lasomma_srs_rainfall_livorno/
| Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Livorno
| The SRS (Smart Rainfall System) dataset originates from a dense network of microwave sensors designed for satellite down-links and developed by the University of Genoa together with Artys and Darts Engineering (Genoa, Italy). By analysing the attenuation of satellite signals received by standard parabolic antennas, the system retrieves real-time estimates of rainfall intensity along each observation link and produces high-resolution precipitation maps over the monitored area. The resulting dataset provides continuous time series of rainfall intensity and cumulative precipitation (15 minutes, 1-2-8-12, 24 hours), enabling detailed spatio-temporal characterization of rainfall dynamics.\n\ncdm_data_type = Grid\nVARIABLES:\ntime (seconds since 1970-01-01T00:00:00Z)\nsrs_id\nsrs_sat_id\nrain_level\n
|
|
| https://erddap.s4raise.it/erddap/info/ingv-lasomma_srs_rainfall_livorno/index.htmlTable
| https://indra.artys.it/INGVRAISE/index.html
| https://erddap.s4raise.it/erddap/rss/ingv-lasomma_srs_rainfall_livorno.rss
| https://erddap.s4raise.it/erddap/subscriptions/add.html?datasetID=ingv-lasomma_srs_rainfall_livorno&showErrors=false&email=
| INGV, Darts Engineering Srl
| ingv-lasomma_srs_rainfall_livorno
|
