CLC+ Backbone: Set the Scene in Copernicus for the Coming Decade

Probeck, Markus; Ruiz, Inés; Ramminger, Gernot; Fourie, Christoff; Maier, Pirmin; Ickerott, Martin; Storch, Cornelia; Homolka, Anna; Muller, Sybrand Jacobus; Tiwari, Himanshu; Stumpf, André; Chun, Sooyeon; Mattos, Cristina; Lindmayer, Amelie; Jahangir, Fahad; Endara, Pilar; Berndt, Fabian; Dohr, Mario; Kapferer, W.; Schleicher, Christian; Ralser, Stefan; Innerbichler, Florian; Riffler, Michael; Siklar, Martin; Aifantopoulou, Dora; Paralykidis, Sideris; Pinet, Camille; Jaffrain, Gabriel; Federico, Annalaura di; Corsi, Marco; Langanke, Tobias; Dufourmont, Hans

doi:10.1109/igarss47720.2021.9553252

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…A new product based on the CORINE experience and complementary to it is currently being developed. CORINE Land Cover + (CLC+), also called the "2nd generation CORINE Land Cover", will provide a single repository of European and selected national LUC datasets, which will be integrated in a common grid following the EAGLE data model and nomenclature (Probeck et al, 2021). The created grid will be based on a new product (CLC+ Backbone) obtained through Sentinel imagery segmentation and auxiliary data, which will also classify the landscape through a 18-categories classification scheme (European Environment Agency, 2021).…”

Section: Corine Land Covermentioning

confidence: 99%

Analyzing the uncertainty of the CORINE Land Cover time series (1990-2018) for Spain

García-Álvarez¹,

Olmedo²

2022

Preprint

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CORINE Land Cover is one of the most relevant Land Use Cover (LUC) databases in Europe because of its degree of detail and long time series. Although some studies have assessed the uncertainty of the database for specific years and periods, no work has been found that analyses all the available CORINE time series (1990-2018). In this study, we analyze the uncertainties of the CORINE time series for a specific Spanish region (Asturias). To this end, we compare and analyze the CORINE status layers (CLC) and the CORINE layers of changes (CHA) for each of the mapped periods: 1990-2000, 2000-2006, 2006-2012, 2012-2018. Results show how CLC and CHA layers provide different information, especially after the change of production of CORINE Spain in 2012. The last two CORINE editions (2012, 2018) show a lot of technical changes that make the use of CLC layers very uncertain. In addition, mixed categories, whose definition is imprecise and, therefore, more uncertain, are behind most of detected change in both types of CORINE layers (CHA, CLC).

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Section: Corine Land Covermentioning

confidence: 99%

Analyzing the uncertainty of the CORINE Land Cover time series (1990-2018) for Spain

García-Álvarez¹,

Olmedo²

2022

Preprint

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“…This European programme led by the European Commission (EC) provides with an open policy high-resolution and multispectral data acquired every few days, making possible to observe the surface several times per month. This has triggered new science and applications worldwide (Phiri et al, 2020), including the development of new LULC products for Europe in the framework of Copernicus, such as High Resolution Layers (HRL) and the new generation of CORINE Land Cover (Probeck et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Portuguese Land Cover Monitoring System (SMOS): from research and development (R&D) to operations

Costa

Benevides

Caetano

2023

MAPPING

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The Portuguese Land Cover Monitoring System SMOS (Sistema de Monitorização da Ocupação do Solo) is an initiative conceived and developed by Direção-Geral do Território (DGT) with the aim of continuously produce reference and thematic cartographic products on land use land cover for continental Portugal. SMOS is a collaborative and multifunctional system that involves the Public Administration, the national scientific and technological system, the private sector and the citizen, guided by user needs and open data policy. SMOS represents a paradigm shift in cartography production and uses the latest developments in space technologies and Artificial Intelligence to create maps with more detail, quality and promptness. Here, SMOS is presented, including the initial steps leading to the implementation of the system, its organization and governance, cartographic products and viewers, and foreseen developments.

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“…For example, in Europe, CLC is currently undergoing a thorough revision and evolving to a "second generation", called CLC+. The new CLC+ moves away from traditional visual interpretation of remote sensing data and includes advanced image analysis, such as supervised image classification and segmentation [18]. Other examples include new products and programmes, such as Malinowski et al [19], who developed an automatic classification workflow of multi-temporal Sentinel-2 imagery for Europe to produce a map of 13 classes relative to 2017 and envisaging annual updates.…”

Section: Introductionmentioning

confidence: 99%

Spatially Stratified and Multi-Stage Approach for National Land Cover Mapping Based on Sentinel-2 Data and Expert Knowledge

et al. 2022

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Portugal is building a land cover monitoring system to deliver land cover products annually for its mainland territory. This paper presents the methodology developed to produce a prototype relative to 2018 as the first land cover map of the future annual map series (COSsim). A total of thirteen land cover classes are represented, including the most important tree species in Portugal. The mapping approach developed includes two levels of spatial stratification based on landscape dynamics. Strata are analysed independently at the higher level, while nested sublevels can share data and procedures. Multiple stages of analysis are implemented in which subsequent stages improve the outputs of precedent stages. The goal is to adjust mapping to the local landscape and tackle specific problems or divide complex mapping tasks in several parts. Supervised classification of Sentinel-2 time series and post-classification analysis with expert knowledge were performed throughout four stages. The overall accuracy of the map is estimated at 81.3% (±2.1) at the 95% confidence level. Higher thematic accuracy was achieved in southern Portugal, and expert knowledge significantly improved the quality of the map.

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CLC+ Backbone: Set the Scene in Copernicus for the Coming Decade

Cited by 7 publications

References 8 publications

Analyzing the uncertainty of the CORINE Land Cover time series (1990-2018) for Spain

Analyzing the uncertainty of the CORINE Land Cover time series (1990-2018) for Spain

The Portuguese Land Cover Monitoring System (SMOS): from research and development (R&D) to operations

Spatially Stratified and Multi-Stage Approach for National Land Cover Mapping Based on Sentinel-2 Data and Expert Knowledge

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