{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T22:08:12Z","timestamp":1761948492743,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"3","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\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Environments"],"abstract":"<jats:p>Forest areas in Portugal are often affected by fires. The objective of this work was to analyze the most fire-affected areas in Portugal in the summer of 2016 for two municipalities considering data from Landsat 8 OLI and Sentinel 2A MSI (prefire and postfire data). Different remote sensed data-derived indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR), could be used to identify burnt areas and estimate the burn severity. In this work, NDVI was used to evaluate the area burned, and NBR was used to estimate the burn severity. The results showed that the NDVI decreased considerably after the fire event (2017 images), indicating a substantial decrease in the photosynthesis activity in these areas. The results also indicate that the NDVI differences (dNDVI) assumes the highest values in the burned areas. The results achieved for both sensors regarding the area burned presented differences from the field data no higher than 13.3% (for Sentinel 2A, less than 7.8%). We conclude that the area burned estimated using the Sentinel 2A data is more accurate, which can be justified by the higher spatial resolution of this data.<\/jats:p>","DOI":"10.3390\/environments6030036","type":"journal-article","created":{"date-parts":[[2019,3,19]],"date-time":"2019-03-19T12:12:25Z","timestamp":1552997545000},"page":"36","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["A Statistical and Spatial Analysis of Portuguese Forest Fires in Summer 2016 Considering Landsat 8 and Sentinel 2A Data"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8043-6431","authenticated-orcid":false,"given":"Ana","family":"Teodoro","sequence":"first","affiliation":[{"name":"Department Geosciences, Environment and Land Planning Faculty of Sciences, Rua Campo Alegre, University of Porto, 4169-007 Porto, Portugal"},{"name":"Earth Sciences Institute (ICT), Faculty of Sciences, Rua Campo Alegre, University of Porto, 4169-007 Porto, Portugal"}]},{"given":"Ana","family":"Amaral","sequence":"additional","affiliation":[{"name":"Department Geosciences, Environment and Land Planning Faculty of Sciences, Rua Campo Alegre, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,16]]},"reference":[{"key":"ref_1","first-page":"221","article-title":"Combination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity","volume":"64","author":"Quintano","year":"2018","journal-title":"Int. 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