First 1-M Resolution Land Cover Map Labeling the Overlap in the 3rd Dimension: The 2018 Map for Wallonia

Céline Bassine, Julien Radoux, Benjamin Beaumont, Taïs Grippa, Moritz Lennert, Céline Champagne, Mathilde De Vroey, Augustin Martinet, Olivier Bouchez, Nicolas Deffense, Eric Hallot, Eléonore Wolff and Pierre Defourny
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Céline Bassine: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Julien Radoux: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Benjamin Beaumont: Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), B-4000 Liège, Belgium
Taïs Grippa: ANAGEO-DGES, Université Libre de Bruxelles, B-1030 Brussels, Belgium
Moritz Lennert: ANAGEO-DGES, Université Libre de Bruxelles, B-1030 Brussels, Belgium
Céline Champagne: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Mathilde De Vroey: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Augustin Martinet: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Olivier Bouchez: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Nicolas Deffense: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium
Eric Hallot: Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), B-4000 Liège, Belgium
Eléonore Wolff: ANAGEO-DGES, Université Libre de Bruxelles, B-1030 Brussels, Belgium
Pierre Defourny: Earth and Life Institute, Université catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium

Data, 2020, vol. 5, issue 4, 1-11

Abstract: Land cover maps contribute to a large diversity of geospatial applications, including but not limited to land management, hydrology, land use planning, climate modeling and biodiversity monitoring. In densely populated and highly fragmented landscapes as observed in the Walloon region (Belgium), very high spatial resolution is required to depict all the infrastructures, buildings and most of the structural elements of the semi-natural landscapes (like hedges and small water bodies). Because of the resolution, the vertical dimension needs explicit handling to avoid discontinuities incompatible with many applications. For example, how to map a river flowing under a bridge? The particularity of our data is to provide a two-digit land cover code to label all the overlapping items. The identification of all the overlaps resulted from the combination of remote sensing image analysis and decision rules involving ancillary data. The final product is therefore semantically precise and accurate in terms of land cover description thanks to the addition of 24 classes on top of the 11 pure land cover classes. The quality of the map has been assessed using a state-of-the-art validation scheme. Its overall accuracy is as high as 91.5%, with an average producer’s accuracy of 86% and an average user’s accuracy of 91%.

Keywords: land cover; map; landscape; remote sensing (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2020
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