{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T14:15:33Z","timestamp":1765808133624,"version":"build-2065373602"},"reference-count":11,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,31]],"date-time":"2022-12-31T00:00:00Z","timestamp":1672444800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"F\u00e9d\u00e9ration Wallonie-Bruxelles"},{"name":"European Research Infrastructure Consortium"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Ecosystem accounting is based on the definition of the extent and the status of an ecosystem. Land cover maps extents are representative of several ecosystems and can therefore be used to support ecosystem accounting if reliable change information is available. The dataset described in this paper aims to provide land cover information (13 classes) for biodiversity monitoring, which has driven two key features. On one hand, open areas were described in more details (5 classes) than in the other maps available in the study area in order to increase their relevance for biodiversity models. On the other hand, monitoring means that the time series must consist of comparable layers. The time series integrate information from existing high quality land cover maps that are not fully comparable, as well as thematic products (crop type, road network and forest type) and remote sensing data (25 cm orthophotos, 0.8 pts\/m2 LIDAR and Sentinel-1&amp;2 data). Because of the high spatial resolution of the data and the fragmented landscape, boundary errors could cause a large proportion of false change detection if the maps are classified independently. Buildings and forests were therefore consolidated across time in order to build a time series where these changes can be trusted. Based on an independent validation, the overall accuracy was 93.1%, 92.6%, 94.8% and 93.9% +\/\u22121.3% for the years 2006, 2015, 2018 and 2019, respectively. The specific assessment of forest patch change highlighted a 98% +\/\u22122.7% user accuracy across the 4 years and 85% of forest cut detection. This time series will be completed and further consolidated with other dates using the same protocol and legend.<\/jats:p>","DOI":"10.3390\/data8010013","type":"journal-article","created":{"date-parts":[[2023,1,2]],"date-time":"2023-01-02T02:23:06Z","timestamp":1672626186000},"page":"13","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Consistent Land Cover Map Time Series at 2 m Spatial Resolution\u2014The LifeWatch 2006-2015-2018-2019 Dataset for Wallonia"],"prefix":"10.3390","volume":"8","author":[{"given":"Julien","family":"Radoux","sequence":"first","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7564-655X","authenticated-orcid":false,"given":"Axel","family":"Bourdouxhe","sequence":"additional","affiliation":[{"name":"Gembloux AgroBioTech, Universit\u00e9 de Li\u00e8ge, B-4000 Li\u00e8ge, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1854-4159","authenticated-orcid":false,"given":"Thomas","family":"Copp\u00e9e","sequence":"additional","affiliation":[{"name":"Gembloux AgroBioTech, Universit\u00e9 de Li\u00e8ge, B-4000 Li\u00e8ge, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5591-1472","authenticated-orcid":false,"given":"Mathilde","family":"De Vroey","sequence":"additional","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium"}]},{"given":"Marc","family":"Dufr\u00eane","sequence":"additional","affiliation":[{"name":"Gembloux AgroBioTech, Universit\u00e9 de Li\u00e8ge, B-4000 Li\u00e8ge, Belgium"}]},{"given":"Pierre","family":"Defourny","sequence":"additional","affiliation":[{"name":"Earth and Life Institute, Universit\u00e9 Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Radoux, J., Bourdouxhe, A., Coos, W., Dufr\u00eane, M., and Defourny, P. (2019). Improving ecotope segmentation by combining topographic and spectral data. Remote Sens., 11.","DOI":"10.3390\/rs11030354"},{"key":"ref_2","unstructured":"(2022, November 25). Available online: https:\/\/land.copernicus.eu\/eagle\/work-results-documentation-and-tools."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.ecoinf.2017.08.005","article-title":"Landscape delineation strategy and size of mapping units impact the performance of habitat suitability models","volume":"47","author":"Delangre","year":"2018","journal-title":"Ecol. Inform."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"125901","DOI":"10.1016\/j.jnc.2020.125901","article-title":"Comparison of methods to model species habitat networks for decision-making in nature conservation: The case of the wildcat in southern Belgium","volume":"58","author":"Bourdouxhe","year":"2020","journal-title":"J. Nat. 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Data, 5.","DOI":"10.3390\/data5040117"},{"key":"ref_8","unstructured":"Draime, D., Denies, J., and Stephenne, N. (2022, January 23\u201327). 2022 Updating the Walloon land cover map by operational application of artificial intelligence with a deep local authorities\u2019 appropriation. Proceedings of the ESA Living Planet Symposium, Bonn, Germany. Available online: https:\/\/express.converia.de\/frontend\/index.php#."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40965-017-0031-6","article-title":"Orfeo ToolBox: Open source processing of remote sensing images","volume":"2","author":"Grizonnet","year":"2017","journal-title":"Open Geospat. Data Softw. Stand."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"113145","DOI":"10.1016\/j.rse.2022.113145","article-title":"Mowing detection using Sentinel-1 and Sentinel-2 time series for large scale grassland monitoring","volume":"280","author":"Zavagli","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3965","DOI":"10.3390\/rs6053965","article-title":"Automated training sample extraction for global land cover mapping","volume":"6","author":"Radoux","year":"2014","journal-title":"Remote Sens."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/8\/1\/13\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:49:24Z","timestamp":1760147364000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/8\/1\/13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,31]]},"references-count":11,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["data8010013"],"URL":"https:\/\/doi.org\/10.3390\/data8010013","relation":{},"ISSN":["2306-5729"],"issn-type":[{"type":"electronic","value":"2306-5729"}],"subject":[],"published":{"date-parts":[[2022,12,31]]}}}