M. Probeck, Inés Ruíz, G. Ramminger, C. Fourie, Pirmin Maier, Martin Ickerott, Cornelia Storch, A. Homolka, S. J. Muller, Himanshu Tiwari, A. Stumpf, Sooyeon Chun, C. Mattos, Amelie Lindmayer, Fahad Jahangir, Pilar Endara, F. Berndt, M. Dohr, W. Kapferer, C. Schleicher, S. Ralser, Florian Innerbichler, M. Riffler, Martin Siklar, Dorothea Aifantopoulou, Sideris Paralykidis, Camille Pinet, G. Jaffrain, A. D. Federico, M. Corsi, T. Langanke, H. Dufourmont
{"title":"CLC+ Backbone: Set the Scene in Copernicus for the Coming Decade","authors":"M. Probeck, Inés Ruíz, G. Ramminger, C. Fourie, Pirmin Maier, Martin Ickerott, Cornelia Storch, A. Homolka, S. J. Muller, Himanshu Tiwari, A. Stumpf, Sooyeon Chun, C. Mattos, Amelie Lindmayer, Fahad Jahangir, Pilar Endara, F. Berndt, M. Dohr, W. Kapferer, C. Schleicher, S. Ralser, Florian Innerbichler, M. Riffler, Martin Siklar, Dorothea Aifantopoulou, Sideris Paralykidis, Camille Pinet, G. Jaffrain, A. D. Federico, M. Corsi, T. Langanke, H. Dufourmont","doi":"10.1109/IGARSS47720.2021.9553252","DOIUrl":null,"url":null,"abstract":"With the CLC+ product suite as part of the Copernicus Land Monitoring Service (CLMS), the European Environment Agency (EEA) has initiated a true paradigm change in European land cover/land use monitoring, building on the 30-years-long rich legacy of the European CORINE Land Cover (CLC) flagship product. The CLC+ Backbone, as first component of the upcoming CLC+ era, will feature an object-oriented wall-to-wall high-resolution inventory of European land cover and its characteristics in unprecedented quality and detail, for the reference year 2018. It will comprise a pan-European combined “hardbone” and “soft-bone” segmentation of vector-based stable landscape objects and a raster-based classification of 11 EAGLE compliant land cover classes at 10m spatial resolution. To this end, a combination of image segmentation and Deep Learning approaches are implemented within a cloud-based infrastructure for a fully integrated analysis of optical/radar time series of Sentinel-1/-2 satellite imagery and auxiliary data. Vector and raster datasets will be fused into a fully attributed, 18 land cover class, vector product with 0.5 ha minimum mapping unit (MMU), additionally incorporating a multitude of further information layers derived from satellite data and various other Copernicus products.","PeriodicalId":315312,"journal":{"name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS47720.2021.9553252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
With the CLC+ product suite as part of the Copernicus Land Monitoring Service (CLMS), the European Environment Agency (EEA) has initiated a true paradigm change in European land cover/land use monitoring, building on the 30-years-long rich legacy of the European CORINE Land Cover (CLC) flagship product. The CLC+ Backbone, as first component of the upcoming CLC+ era, will feature an object-oriented wall-to-wall high-resolution inventory of European land cover and its characteristics in unprecedented quality and detail, for the reference year 2018. It will comprise a pan-European combined “hardbone” and “soft-bone” segmentation of vector-based stable landscape objects and a raster-based classification of 11 EAGLE compliant land cover classes at 10m spatial resolution. To this end, a combination of image segmentation and Deep Learning approaches are implemented within a cloud-based infrastructure for a fully integrated analysis of optical/radar time series of Sentinel-1/-2 satellite imagery and auxiliary data. Vector and raster datasets will be fused into a fully attributed, 18 land cover class, vector product with 0.5 ha minimum mapping unit (MMU), additionally incorporating a multitude of further information layers derived from satellite data and various other Copernicus products.