Remote sensing technology for rapid extraction of burned areas and ecosystem environmental assessment

• Published in: PeerJ (San Francisco, CA) Vol. 11; p. e14557
• Main Authors: Zhang, Shiqi, Bai, Maoyang, Wang, Xiao, Peng, Xuefeng, Chen, Ailin, Peng, Peihao
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 06.02.2023; PeerJ Inc
• Subjects: Burned areas; Burns; China; Ecosystem; Ecosystems; Environmental impact analysis; Environmental Impacts; Environmental Monitoring; Forest fire; Forest fires; Forest management; Forests; GEE platform; Humans; OTSU threshold; Remote sensing; Remote sensing environment index; Remote Sensing Technology; Sentinel-2; Spatial and Geographic Information Science; China; GEE platform; Remote sensing environment index; Forest fire; OTSU threshold; Sentinel-2; Burned areas
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.14557

Forest fires are one of the significant disturbances in forest ecosystems. It is essential to extract burned areas rapidly and accurately to formulate forest restoration strategies and plan restoration plans. In this work, we constructed decision trees and used a combination of differential normalized burn ratio (dNBR) index and OTSU threshold method to extract the heavily and mildly burned areas. The applicability of this method was evaluated with three fires in Muli County, Sichuan, China, and we concluded that the extraction accuracy of this method could reach 97.69% and 96.37% for small area forest fires, while the extraction accuracy was lower for large area fires, only 89.32%. In addition, the remote sensing environment index (RSEI) was used to evaluate the ecological environment changes. It analyzed the change of the RSEI level through the transition matrix, and all three fires showed that the changes in RSEI were stronger for heavily burned areas than for mildly burned areas, after the forest fire the ecological environment (RSEI) was reduced from good to moderate. These results realized the quantitative evaluation and dynamic evaluation of the ecological environment condition, providing an essential basis for the restoration, decision making and management of the affected forests.