Assessment of k-Nearest Neighbor and Random Forest classifiers for mapping forest fire areas in central Portugal using Landsat-8, Sentinel-2, and Terra Imagery

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 7; pp. 1 - 25
• Main Authors: Pacheco, Admilson da Penha, Junior, Juarez Antonio da Silva, Ruiz-Armenteros, Antonio Miguel, Henriques, Renato F.
• Format: Journal Article
• Language: English
• Published: Basel Multidisciplinary Digital Publishing Institute (MDPI) 01.04.2021; MDPI AG
• Subjects: Algorithms; ASTER; Biodiversity; Burned; Classification; Classifiers; Climate change; Conservation areas; Desertification; Fires; Forest & brush fires; Forest fires; k-Nearest Neighbor; Landsat; Landsat 8; Landsat satellites; Mapping; MODIS; Random Forest; Remote monitoring; Remote sensing; Satellite imagery; Science & Technology; Sensors; Sentinel 2; Spatial discrimination; Spatial resolution; Terra; Vegetation; Portugal

Forest fires threaten the population’s health, biomass, and biodiversity, intensifying the desertification processes and causing temporary damage to conservation areas. Remote sensing has been used to detect, map, and monitor areas that are affected by forest fires due to the fact that the different...