{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T09:20:33Z","timestamp":1775640033183,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T00:00:00Z","timestamp":1624579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2652018077"],"award-info":[{"award-number":["2652018077"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices.<\/jats:p>","DOI":"10.3390\/rs13132492","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T11:07:40Z","timestamp":1624619260000},"page":"2492","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Sensitivity of Spectral Indices on Burned Area Detection using Landsat Time Series in Savannas of Southern Burkina Faso"],"prefix":"10.3390","volume":"13","author":[{"given":"Jinxiu","family":"Liu","sequence":"first","affiliation":[{"name":"School of Information Engineering, China University of Geosciences, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7932-1824","authenticated-orcid":false,"given":"Eduardo Eiji","family":"Maeda","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Geography, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6546-1639","authenticated-orcid":false,"given":"Du","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, China University of Geosciences, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3899-8860","authenticated-orcid":false,"given":"Janne","family":"Heiskanen","sequence":"additional","affiliation":[{"name":"Department of Geosciences and Geography, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland"},{"name":"Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jaridenv.2016.11.005","article-title":"Evaluating Fire Severity in Sudanian Ecosystems of Burkina Faso Using Landsat 8 Satellite Images","volume":"139","author":"Musyimi","year":"2017","journal-title":"J. Arid. Environ."},{"key":"ref_2","first-page":"380","article-title":"Predictive Fire Occurrence Modelling to Improve Burned Area Estimation at a Regional Scale: A Case Study in East Caprivi, Namibia","volume":"11","author":"Siljander","year":"2009","journal-title":"Int. J. Appl. Earth Obs. 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