{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T00:26:53Z","timestamp":1780100813379,"version":"3.54.0"},"reference-count":70,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2017,2,5]],"date-time":"2017-02-05T00:00:00Z","timestamp":1486252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"BMBF","doi-asserted-by":"publisher","award":["FKZ 01LG1202D"],"award-info":[{"award-number":["FKZ 01LG1202D"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Burkina Faso ranges amongst the fastest growing countries in the world with an annual population growth rate of more than three percent. This trend has consequences for food security since agricultural productivity is still on a comparatively low level in Burkina Faso. In order to compensate for the low productivity, the agricultural areas are expanding quickly. The mapping and monitoring of this expansion is difficult, even on the basis of remote sensing imagery, since the extensive farming practices and frequent cloud coverage in the area make the delineation of cultivated land from other land cover and land use types a challenging task. However, as the rapidly increasing population could have considerable effects on the natural resources and on the regional development of the country, methods for improved mapping of LULCC (land use and land cover change) are needed. For this study, we applied the newly developed ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) framework to generate high temporal (8-day) and high spatial (30 m) resolution NDVI time series for all of Burkina Faso for the years 2001, 2007, and 2014. For this purpose, more than 500 Landsat scenes and 3000 MODIS scenes were processed with this automated framework. The generated ESTARFM NDVI time series enabled extraction of per-pixel phenological features that all together served as input for the delineation of agricultural areas via random forest classification at 30 m spatial resolution for entire Burkina Faso and the three years. For training and validation, a randomly sampled reference dataset was generated from Google Earth images and based on expert knowledge. The overall accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the applied methodology. The results show an expansion of agricultural area of 91% between 2001 and 2014 to a total of 116,900 km\u00b2. While rainfed agricultural areas account for the major part of this trend, irrigated areas and plantations also increased considerably, primarily promoted by specific development projects. This expansion goes in line with the rapid population growth in most provinces of Burkina Faso where land was still available for an expansion of agricultural area. The analysis of agricultural encroachment into protected areas and their surroundings highlights the increased human pressure on these areas and the challenges of environmental protection for the future.<\/jats:p>","DOI":"10.3390\/rs9020132","type":"journal-article","created":{"date-parts":[[2017,2,6]],"date-time":"2017-02-06T11:29:27Z","timestamp":1486380567000},"page":"132","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":69,"title":["Monitoring Agricultural Expansion in Burkina Faso over 14 Years with 30 m Resolution Time Series: The Role of Population Growth and Implications for the Environment"],"prefix":"10.3390","volume":"9","author":[{"given":"Kim","family":"Knauer","sequence":"first","affiliation":[{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, Germany"},{"name":"Department of Remote Sensing, University of Wuerzburg, 97074 Wuerzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ursula","family":"Gessner","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3067-4527","authenticated-orcid":false,"given":"Rasmus","family":"Fensholt","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerald","family":"Forkuor","sequence":"additional","affiliation":[{"name":"West African Science Service Center on Climate Change and Adapted Land Use (WASCAL), P.O. Box 9507, Ouagadougou 06, Burkina Faso"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia","family":"Kuenzer","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,2,5]]},"reference":[{"key":"ref_1","unstructured":"FAOSTAT\u2014Food and Agriculture Organization of the United Nations. Available online: http:\/\/faostat3.fao.org\/faostat-gateway\/go\/to\/home\/E."},{"key":"ref_2","unstructured":"(2015). UN Human Development Report, United Nations Development Programme."},{"key":"ref_3","unstructured":"(2016). Global Economic Prospects\u2014Spillovers amid Weak Growth, World Bank."},{"key":"ref_4","unstructured":"(2014). 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