{"collections":[{"id":"0798aa197d54eb4332767a5a4077fb0f","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/0798aa197d54eb4332767a5a4077fb0f/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/0798aa197d54eb4332767a5a4077fb0f"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/0798aa197d54eb4332767a5a4077fb0f/queryables"}],"title":"CMIP5","extent":{"spatial":{"bbox":[[-140.99778,41.6751050889,-52.6480987209,83.23324]]},"temporal":{"interval":[["2015-10-22T00:00:00Z","2100-10-22T00:00:00Z"]]}},"license":"proprietary","keywords":["climate change","CMIP5","WCRP","CMIP"],"summaries":{"freq":["YS","MS","allrcps_ensemble_stats"],"scenario":["rcp45","rcp85","rcp26","MS","YS"],"variable_id":["SDII","txgt_30","txgt_32","txgt_37"],"dataset_name":["BCCAQv2"],"collection_id":["CMIP6"]},"description":"The WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).The CMIP5 archive is managed via the Earth System Grid Federation, a globally distributed archive, with various gateways with advanced faceted search capabilities provided by a number of participating organisations. Full details are available from the PCMDI CMIP5 pages (see linked documentation on this record).","stac_version":"1.1.0"},{"id":"c604ffb6d610adbb9a6b4787db7b8fd7","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/c604ffb6d610adbb9a6b4787db7b8fd7/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/c604ffb6d610adbb9a6b4787db7b8fd7"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/c604ffb6d610adbb9a6b4787db7b8fd7/queryables"}],"title":"CMIP6","extent":{"spatial":{"bbox":[[-140.99778,41.6751050889,-52.6480987209,83.23324]]},"temporal":{"interval":[["2015-10-22T00:00:00Z","2100-10-22T00:00:00Z"]]}},"license":"proprietary","keywords":["climate change","CMIP5","WCRP","CMIP"],"summaries":{"freq":["YS","MS"],"scenario":["ssp126","ssp245","ssp585"],"variable_id":["frost_free_season","txgt_29","txgt_30","txgt_32"],"dataset_name":["BCCAQv2_CMIP6"],"collection_id":["CMIP6"]},"description":"The WCRP Coupled Model Intercomparison Project, Phase 6 (CMIP6), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).The CMIP6 archive is managed via the Earth System Grid Federation, a globally distributed archive, with various gateways with advanced faceted search capabilities provided by a number of participating organisations. Full details are available from the PCMDI CMIP6 pages (see linked documentation on this record).","stac_version":"1.1.0"},{"id":"EuroSAT-full-test","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-test/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-test"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/validate/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'test' split.","ml-aoi:split":"validate"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/train/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'test' split.","ml-aoi:split":"train"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-test/queryables"}],"title":"EuroSAT full test","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-21.00040724681893,27.9641563321385,33.532513649760425,65.2408902876518]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["test"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the test split set for training machine learning algorithms.","stats:items":{"count":5400},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"EuroSAT-full-train","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-train/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-train"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/test/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'train' split.","ml-aoi:split":"test"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/validate/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'train' split.","ml-aoi:split":"validate"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-train/queryables"}],"title":"EuroSAT full train","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-21.00040724681893,27.964190338352353,33.53247532314633,65.21068491436765]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["train"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the train split set for training machine learning algorithms.","stats:items":{"count":16200},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"EuroSAT-full-validate","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-validate/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-validate"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/test/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'validate' split.","ml-aoi:split":"test"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/full/train/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'validate' split.","ml-aoi:split":"train"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-full-validate/queryables"}],"title":"EuroSAT full validate","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-21.00040724681893,27.9641563321385,33.532513649760425,65.21068491436765]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["validate"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the validate split set for training machine learning algorithms.","stats:items":{"count":5400},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"EuroSAT-subset-test","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-test/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-test"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/train/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'test' split.","ml-aoi:split":"train"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/validate/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'test' split.","ml-aoi:split":"validate"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-test/queryables"}],"title":"EuroSAT subset test","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-7.882190080512502,35.06657039178422,32.910449406756946,58.21798141355221]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["test"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the test split set for training machine learning algorithms.","stats:items":{"count":20},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"EuroSAT-subset-train","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-train/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-train"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/validate/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'train' split.","ml-aoi:split":"validate"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/test/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'train' split.","ml-aoi:split":"test"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-train/queryables"}],"title":"EuroSAT subset train","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-7.882190080512502,37.13739173208318,27.911651652899923,58.21798141355221]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["train"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the train split set for training machine learning algorithms.","stats:items":{"count":60},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"EuroSAT-subset-validate","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-validate/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-validate"},{"rel":"cite-as","href":"https://arxiv.org/abs/1709.00029","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"license","href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/html","title":"EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/train/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'validate' split.","ml-aoi:split":"train"},{"rel":"related","href":"https://hirondelle.crim.ca/stac/EuroSAT/stac/subset/test/collection.json","type":"application/json","title":"EuroSAT STAC Collection with samples from 'validate' split.","ml-aoi:split":"test"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/EuroSAT-subset-validate/queryables"}],"title":"EuroSAT subset validate","assets":{"paper":{"href":"https://www.researchgate.net/publication/319463676","type":"text/html","roles":["paper","scientific","citation"],"title":"Scientific Paper","sci:doi":"10.1109/JSTARS.2019.2918242","description":"ResearchGate page with embedded PDF of the scientific paper supporting the dataset."},"source":{"href":"https://github.com/phelber/EuroSAT/","type":"text/html","roles":["data","source","scientific","citation"],"title":"GitHub repository","sci:doi":"10.1109/JSTARS.2019.2918242","description":"Source GitHub repository of the EuroSAT dataset."},"license":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/LICENSE","type":"text/plain","roles":["legal","license"],"title":"License","sci:doi":"10.1109/JSTARS.2019.2918242","description":"License contents associated to the EuroSAT dataset."},"thumbnail":{"href":"https://raw.githubusercontent.com/phelber/EuroSAT/master/eurosat_overview_small.jpg","type":"image/jpeg","roles":["thumbnail","overview"],"sci:doi":"10.1109/JSTARS.2019.2918242","description":"Preview of dataset samples."}},"extent":{"spatial":{"bbox":[[-7.882190080512502,35.06657039178422,32.85346177221201,58.21798141355221]]},"temporal":{"interval":[["2015-06-27T10:25:31.456000Z","2017-06-14T00:00:00Z"]]}},"license":"MIT","version":"0.5.0","summaries":{"gsd":[10],"sci:doi":["10.1109/JSTARS.2019.2918242"],"eo:bands":[{"name":"B01","common_name":"coastal","center_wavelength":0.4439,"full_width_half_max":0.027},{"name":"B02","common_name":"blue","center_wavelength":0.4966,"full_width_half_max":0.098},{"name":"B03","common_name":"green","center_wavelength":0.56,"full_width_half_max":0.045},{"name":"B04","common_name":"red","center_wavelength":0.6645,"full_width_half_max":0.038},{"name":"B05","common_name":"rededge","center_wavelength":0.7039,"full_width_half_max":0.019},{"name":"B06","common_name":"rededge","center_wavelength":0.7402,"full_width_half_max":0.018},{"name":"B07","common_name":"rededge","center_wavelength":0.7825,"full_width_half_max":0.028},{"name":"B08","common_name":"nir","center_wavelength":0.8351,"full_width_half_max":0.145},{"name":"B08A","common_name":"nir08","center_wavelength":0.8648,"full_width_half_max":0.033},{"name":"B09","common_name":"nir09","center_wavelength":0.945,"full_width_half_max":0.026},{"name":"B10","common_name":"cirrus","center_wavelength":1.3735,"full_width_half_max":0.075},{"name":"B11","common_name":"swir16","center_wavelength":1.6137,"full_width_half_max":0.143},{"name":"B12","common_name":"swir22","center_wavelength":2.22024,"full_width_half_max":0.242}],"instruments":["msi"],"ml-aoi:split":["validate"],"sci:citation":["Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification. Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019."],"constellation":["sentinel-2"],"view:off_nadir":[0],"sci:publications":[{"doi":"10.1109/IGARSS.2018.8519248","citation":"Introducing EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification. Patrick Helber, Benjamin Bischke, Andreas Dengel. 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018."}]},"description":"EuroSAT dataset with labeled annotations for land-cover classification and associated imagery. This collection represents the samples part of the validate split set for training machine learning algorithms.","stats:items":{"count":20},"experimental":true,"stac_version":"1.1.0","stac_extensions":["https://stac-extensions.github.io/eo/v1.1.0/schema.json","https://stac-extensions.github.io/ml-aoi/v0.2.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/stats/v0.2.0/schema.json","https://stac-extensions.github.io/version/v1.0.0/schema.json","https://stac-extensions.github.io/view/v1.0.0/schema.json"]},{"id":"HRDPS_CRIM","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/HRDPS_CRIM/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/HRDPS_CRIM"},{"rel":"about","href":"https://open.canada.ca/data/en/dataset/5b401fa0-6c29-57f0-b3d5-749f301d829d","type":"text/html","title":"Project homepage","hreflang":"en-CA"},{"rel":"about","href":"https://open.canada.ca/data/en/dataset/5b401fa0-6c29-57f0-b3d5-749f301d829d","type":"text/html","title":"Page d'accueil du projet","hreflang":"fr-CA"},{"rel":"author","href":"https://www.canada.ca/en/environment-climate-change.html","type":"text/html","title":"Environment and Climate Change Canada (ECCC)","hreflang":"en-CA"},{"rel":"author","href":"https://www.canada.ca/fr/environnement-changement-climatique.html","type":"text/html","title":"Environnement et Changement Climatique Canada (ECCC)","hreflang":"fr-CA"},{"rel":"describedby","href":"https://eccc-msc.github.io/open-data/msc-data/nwp_hrdps/readme_hrdps_en","type":"text/html","title":"Data and Products of the High Resolution Deterministic Prediction System (HRDPS)","hreflang":"en-CA"},{"rel":"describedby","href":"https://eccc-msc.github.io/open-data/msc-data/nwp_hrdps/readme_hrdps_fr","type":"text/html","title":"Données et Produits du Système à haute résolution de prévision déterministe (SHRPD)","hreflang":"fr-CA"},{"rel":"license","href":"https://eccc-msc.github.io/open-data/licence/readme_en/","type":"text/html","title":"Environment and Climate Change Canada Data Servers End-use License","hreflang":"en-CA"},{"rel":"license","href":"https://eccc-msc.github.io/open-data/licence/readme_fr/","type":"text/html","title":"Licence d’utilisation finale pour les serveurs de données d’Environnement et Changement climatique Canada","hreflang":"fr-CA"},{"rel":"source","href":"https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/birdhouse/testdata/HRDPS/HRDPS_sample/HRDPS_P_TT_10000/catalog.xml","type":"application/xml","title":"THREDDS data source"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/HRDPS_CRIM/queryables"}],"title":"HRDPS","extent":{"spatial":{"bbox":[[-152.7685268,27.2840148,-40.6938032,70.6164825]]},"temporal":{"interval":[["2014-11-18T00:00:00Z","2025-04-01T00:00:00Z"]]}},"license":"other","contacts":[{"logo":{"rel":"icon","href":"https://raw.githubusercontent.com/henriaidasso/image-store/refs/heads/main/img/crim.png","type":"image/png","title":"CRIM"},"links":[{"rel":"about","title":"Site web","target":"https://www.crim.ca/fr/","media_type":"text/html","extra_fields":{"hreflang":"fr-CA"}}],"roles":["indexer"],"emails":[{"roles":["work"],"value":"support-geo@crim.ca"}],"position":"Support","identifier":"CRIM","organization":"Computer Research Institute of Montreal (CRIM)"},{"links":[{"rel":"about","title":"Web page","target":"https://www.canada.ca/en/environment-climate-change.html","media_type":"text/html","extra_fields":{"hreflang":"en-CA"}},{"rel":"about","title":"Site web","target":"https://www.canada.ca/fr/environnement-changement-climatique.html","media_type":"text/html","extra_fields":{"hreflang":"fr-CA"}}],"roles":["licensor","processor","producer"],"emails":[{"roles":["work"],"value":"ECWeather-Meteo@ec.gc.ca"}],"phones":[{"roles":["work"],"value":18199972800}],"position":"Support","addresses":[{"city":"Fredericton","country":"Canada","postalCode":"E3B 6Z4","deliveryPoint":"77 Westmorland Street, suite 260","administrativeArea":"New Brunswick"}],"identifier":"ECCC","organization":"Environment and Climate Change Canada (ECCC)"}],"keywords":["HRDPS","ECCC","MSC","Climate Change","Prediction","High resolution","Deterministic","Meteorological data","Weather and Climate","Meteorological Service of Canada","Environment and Climate Change Canada","Weather and Environmental Operations"],"providers":[{"url":"https://github.com/julemai/CaSPAr/wiki/Available-products","name":"ECCC","roles":["licensor","processor","producer"],"description":"Environment and Climate Change Canada (ECCC)"},{"url":"https://eccc-msc.github.io/open-data","name":"MSC","roles":["processor"],"description":"Meteorological Service of Canada (MSC)"},{"url":"https://www.ouranos.ca","name":"Ouranos","roles":["processor","host"],"description":"Ouranos"}],"summaries":{"needs_summaries_update":["true"]},"description":"High Resolution Deterministic Prediction System","stac_version":"1.0.0"},{"id":"montreal_2023","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://hirondelle.crim.ca/stac/collections/montreal_2023/items"},{"rel":"parent","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections/montreal_2023"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://hirondelle.crim.ca/stac/collections/montreal_2023/queryables"}],"title":"Wildfire Events in Montreal 2023","extent":{"spatial":{"bbox":[[-75.0,45.0,-73.0,46.5]]},"temporal":{"interval":[["2023-08-01T12:00:00Z","2023-08-31T12:00:00Z"]]}},"license":"proprietary","keywords":["wildfire","synthetic","climate"],"description":"Synthetic wildfire event in 2023 with humidity, wind force, and wind direction.","stac_version":"1.1.0"}],"links":[{"rel":"next","type":"application/geo+json","method":"GET","href":"https://hirondelle.crim.ca/stac/collections?offset=10"},{"rel":"root","type":"application/json","href":"https://hirondelle.crim.ca/stac/"},{"rel":"self","type":"application/json","href":"https://hirondelle.crim.ca/stac/collections"}],"numberMatched":13,"numberReturned":10}