{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T12:57:38Z","timestamp":1765976258037,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,16]],"date-time":"2019-03-16T00:00:00Z","timestamp":1552694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100004421","name":"World Bank Group","doi-asserted-by":"publisher","award":["P160999"],"award-info":[{"award-number":["P160999"]}],"id":[{"id":"10.13039\/100004421","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We developed a land cover and land use mapping framework specifically designed for agricultural systems of the Sudan-Sahel region. The mapping approach extracts information from inter- and intra-annual vegetation dynamics from dense stacks of Landsat 8 images. We applied this framework to create a 30 m spatial resolution land use map with a focus on agricultural landscapes of northern Nigeria for 2015. This map provides up-to-date information with a higher level of spatial and thematic detail resulting in a more precise characterization of agriculture in the region. The map reveals that agriculture is the main land use in the region. Arable land represents on average 52.5% of the area, higher than the reported national average for Nigeria (38.4%). Irrigated agriculture covers nearly 2.2% of the total area, reaching nearly 20% of the cultivated land when traditional floodplain agriculture systems are included, above the reported national average (0.63%). There is significant variability in land use within the region. Cultivated land in the northern section can reach values higher than 75%, most land suitable for agriculture is already under cultivation and there is limited land for future agricultural expansion. Marginal lands, not suitable for permanent agriculture, can reach 30% of the land at lower altitudes in the northeast and northwest. In contrast, the southern section presents lower land use intensity that results in a complex landscape that intertwines areas farms and larger patches of natural vegetation. This map improves the spatial detail of existing sources of LCLU information for the region and provides updated information of the current status of its agricultural landscapes. This study demonstrates the feasibility of multi temporal medium resolution remote sensing data to provide detailed and up-to-date information about agricultural systems in arid and sub arid landscapes of the Sahel region.<\/jats:p>","DOI":"10.3390\/rs11060648","type":"journal-article","created":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T12:18:53Z","timestamp":1552911533000},"page":"648","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Mapping Framework to Characterize Land Use in the Sudan-Sahel Region from Dense Stacks of Landsat Data"],"prefix":"10.3390","volume":"11","author":[{"given":"Fernando","family":"Sedano","sequence":"first","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 207040, USA"}]},{"given":"Vasco","family":"Molini","sequence":"additional","affiliation":[{"name":"World Bank, 7 Rue Larbi Ben Abdellah, Rabat 10001, Morocco"}]},{"given":"M. Abul Kalam","family":"Azad","sequence":"additional","affiliation":[{"name":"World Bank, Plot 102 Yakubu Gowon Crescent Asokoro Abuja, Nigeria"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3520","DOI":"10.1016\/j.rse.2008.04.010","article-title":"A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US","volume":"112","author":"Ozdogan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1016\/j.rse.2010.01.006","article-title":"The spatial distribution of crop types from MODIS data: Temporal unmixing using Independent Component Analysis","volume":"114","author":"Ozdogan","year":"2010","journal-title":"Remote Sens. 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