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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
|
