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

Shiqi Zhang; Maoyang Bai; Xiao Wang; Xuefeng Peng; Ailin Chen; Peihao Peng

doi:10.7717/peerj.14557

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

PeerJ. 2023 Feb 6:11:e14557. doi: 10.7717/peerj.14557. eCollection 2023.

Authors

Shiqi Zhang¹, Maoyang Bai¹, Xiao Wang², Xuefeng Peng³, Ailin Chen^{4

5}, Peihao Peng^{1

3}

Affiliations

¹ College of Earth Sciences, Chengdu University of Technology, Chengdu, China.
² School of Architecture and Civil Engineering, Chengdu University, Chengdu, China.
³ College of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, China.
⁴ Sichuan Earthquake Agency, Chengdu, China.
⁵ Chengdu lnstitute of Tibetan Plateau Earthquake Research, China Earthquake Administration, Chengdu, China.

Abstract

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.

Keywords: Burned areas; Forest fire; GEE platform; OTSU threshold; Remote sensing environment index; Sentinel-2.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Burns*
Ecosystem*
Environmental Monitoring
Forests
Humans
Remote Sensing Technology

Grants and funding

This research was supported by the Second National Survey of Key Protected Wild Plant Resources-Special Survey of Orchidaceae in Sichuan Province (No. 80303-AZZ003), the Special Project of Orchid Survey of National Forestry and Grassland Administration (No. 2019073015) and the Second Tibetan Plateau Scientific Expedition and Research Program (STEP), China (No. 2019QZKK0301). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.