{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T12:03:49Z","timestamp":1773921829226,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,10]],"date-time":"2018-11-10T00:00:00Z","timestamp":1541808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate estimates of cultivated area and crop yield are critical to our understanding of agricultural production and food security, particularly for semi-arid regions like the Sahel of West Africa, where crop production is mainly rain-fed and food security is closely correlated with the inter-annual variations in rainfall. Several global and regional land cover products, based on satellite remotely-sensed data, provide estimates of the agricultural land use intensity, but the initial comparisons indicate considerable differences among them, relating to differences in the satellite data quality, classification approaches, and spatial and temporal resolutions. Here, we quantify the accuracy of available cropland products across Sahelian West Africa using an independent, high-resolution, visually interpreted sample dataset that classifies all points across West Africa using a 2-km sample grid (~500,000 points for the study area). We estimate the \u201cquantity\u201d and \u201callocation\u201d disagreements for the cropland class of eight land cover products in five Western Sahel countries (Burkina Faso, Mali, Mauritania, Niger, and Senegal). The results confirm that coarse spatial resolution (300 m, 500 m, and 1000 m) land cover products have higher disagreements in mapping the fragmented agricultural landscape of the Western Sahel. Earlier products (e.g., GLC2000) are less accurate than recent products (e.g., ESA CCI 2013, MODIS 2013 and GlobCover 2009). We also show that two of the finer spatial resolution maps (GFSAD30, and GlobeLand30) using advanced classification approaches (random forest, decision trees, and pixel-object combined) are currently the best available products for cropland identification. However, none of the eight land cover databases examined is consistent in reaching the targeted 75% accuracy threshold in the five Sahelian countries. The majority of currently available land cover products overestimate cultivated areas by an average of 170% relative to the cropland area in the reference data.<\/jats:p>","DOI":"10.3390\/rs10111785","type":"journal-article","created":{"date-parts":[[2018,11,14]],"date-time":"2018-11-14T02:42:41Z","timestamp":1542163361000},"page":"1785","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Assessing Cropland Area in West Africa for Agricultural Yield Analysis"],"prefix":"10.3390","volume":"10","author":[{"given":"Kaboro","family":"Samasse","sequence":"first","affiliation":[{"name":"Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, USA"},{"name":"IPR\/IFRA, BP 06, Koulikoro Mali"}]},{"given":"Niall","family":"Hanan","sequence":"additional","affiliation":[{"name":"Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM 88003, USA"}]},{"given":"Gray","family":"Tappan","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD 57198, USA"}]},{"given":"Yacouba","family":"Diallo","sequence":"additional","affiliation":[{"name":"IPR\/IFRA, BP 06, Koulikoro Mali"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1111\/j.1467-8268.2011.00283.x","article-title":"Food security and human development in Africa: Strategic considerations and directions for further research","volume":"23","author":"Ngororano","year":"2011","journal-title":"Afr. Dev. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2013.08.023","article-title":"Efficient corn and soybean mapping with temporal extendability: A multi-year experiment using Landsat imagery","volume":"140","author":"Zhong","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2445","DOI":"10.1016\/j.rse.2011.05.005","article-title":"Assessing effects of temporal compositing and varying observation periods for large-area land-cover mapping in semi-arid ecosystems: Implications for global monitoring","volume":"115","author":"Herold","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1016\/j.rse.2007.11.013","article-title":"Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets","volume":"112","author":"Herold","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_5","first-page":"25","article-title":"The most detailed portrait of Earth","volume":"136","author":"Arino","year":"2008","journal-title":"Eur. Space Agency"},{"key":"ref_6","unstructured":"ESA-CCI (2013, January 11). Internal Release of Global Land Cover Map with Improved Accuracy over the Existing State of the Art (75.6%). Available online: https:\/\/www.esa-landcover-cci.org\/?q=node\/148."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1109\/TGRS.2006.864370","article-title":"Validation of the global land cover 2000 map","volume":"44","author":"Mayaux","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Fritz, S., You, L., Bun, A., See, L., McCallum, I., Schill, C., Perger, C., Liu, J., Hansen, M., and Obersteiner, M. (2011). Cropland for sub-Saharan Africa: A synergistic approach using five land cover data sets. Geophys. Res. Lett., 38.","DOI":"10.1029\/2010GL046213"},{"key":"ref_10","unstructured":"Latham, J., Cumani, R., Rosati, I., and Bloise, M. (2014). Global Land Cover Share (GLC-SHARE) Database Beta-Release Version 1.0-2014, FAO."},{"key":"ref_11","first-page":"1863","article-title":"A Comparative Analysis of Five Cropland Datasets in Africa","volume":"XLII-3","author":"Wei","year":"2018","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Laso Bayas, J.C., See, L., Perger, C., Justice, C., Nakalembe, C., Dempewolf, J., and Fritz, S. (2017). Validation of automatically generated global and regional cropland data sets: The case of Tanzania. Remote Sens., 9.","DOI":"10.3390\/rs9080815"},{"key":"ref_13","unstructured":"Tappan, G.G., Cushing, W.M., Cotillon, S.E., Mathis, M.L., Hutchinson, J.A., and Dalsted, K. (2016). West Africa Land Use Land Cover Time Series."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to Kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2014.02.015","article-title":"Good practices for estimating area and assessing accuracy of land change","volume":"148","author":"Olofsson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_16","unstructured":"CILSS (2016). Landscapes of West Africa\u2014A Window on a Changing World."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cotillon, S.E. (2017). West Africa Land Use and Land Cover Time Series.","DOI":"10.3133\/fs20173004"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Cotillon, S.E., and Mathis, M.L. (2017). Mapping Land Cover through Time with the Rapid Land Cover Mapper\u2014Documentation and User Manual.","DOI":"10.3133\/ofr20171012"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: A new approach to global land cover mapping from Earth observation data","volume":"26","author":"Bartholome","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Arino, O., Gross, D., Ranera, F., Leroy, M., Bicheron, P., Brockman, C., Defourny, P., Vancutsem, C., Achard, F., and Durieux, L. (2007, January 23\u201327). GlobCover: ESA service for global land cover from MERIS. Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007), Barcelona, Spain.","DOI":"10.1109\/IGARSS.2007.4423328"},{"key":"ref_21","unstructured":"Arino, O. (2018, April 25). GlobCover 2009. Available online: http:\/\/epic.awi.de\/31046\/1\/Arino_et_al_GlobCover2009-a.pdf."},{"key":"ref_22","unstructured":"UCL-Geomatics (2017, April 10). Land Cover CCI Product User Guide Version 2.0. Available online: http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/download\/ESACCI-LC-Ph2-PUGv2_2.0.pdf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.isprsjprs.2014.09.002","article-title":"Global land cover mapping at 30 m resolution: A POK-based operational approach","volume":"103","author":"Chen","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1980","DOI":"10.1111\/gcb.12838","article-title":"Mapping global cropland and field size","volume":"21","author":"Fritz","year":"2015","journal-title":"Glob. Chang. Biol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Xiong, J., Thenkabail, P.S., Tilton, J.C., Gumma, M.K., Teluguntla, P., Oliphant, A., Congalton, R.G., Yadav, K., and Gorelick, N. (2017). Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using sentinel-2 and Landsat-8 data on Google earth engine. Remote Sens., 9.","DOI":"10.3390\/rs9101065"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhou, Y.N., Ge, Y., An, R., and Chen, Y. (2018). Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery. Remote Sens., 10.","DOI":"10.3390\/rs10010077"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"See, L., Laso Bayas, J.C., Schepaschenko, D., Perger, C., Dresel, C., Maus, V., Salk, C., Weichselbaum, J., Lesiv, W., and McCallum, I. (2017). LACO-Wiki: A new online land cover validation tool demonstrated using GlobeLand30 for Kenya. Remote Sens., 9.","DOI":"10.3390\/rs9070754"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1080\/014311600210641","article-title":"Beware of per-pixel characterization of land cover","volume":"21","author":"Townshend","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2013\/704504","article-title":"A review of data fusion techniques","volume":"2013","author":"Castanedo","year":"2013","journal-title":"Sci. World J."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1785\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:29:02Z","timestamp":1760196542000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/11\/1785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,10]]},"references-count":30,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2018,11]]}},"alternative-id":["rs10111785"],"URL":"https:\/\/doi.org\/10.3390\/rs10111785","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,10]]}}}