Detecting Forest Fires in Southwest China From Remote Sensing Nighttime Lights Using the Random Forest Classification Model-Reference-Cited by-同舟云学术

Detecting Forest Fires in Southwest China From Remote Sensing Nighttime Lights Using the Random Forest Classification Model

Published:2024 Issue: Volume:17 Page:10759-10769
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Yu Yuehan¹,Liu Lili²,Chang Zhijian²,Li Yuanqing¹^ORCID,Shi Kaifang³^ORCID

Affiliation:

1. Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, China

2. School of Geographical Sciences, Southwest University, Chongqing, China

3. Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu, China

Funder

National Natural Science Foundation of China

Natural Science Research Program of Anhui Universities

Special Fund for Youth Team of Southwest University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/4609443/10330207/10551624.pdf?arnumber=10551624

Reference47 articles.

1. Historical and current fire regimes in ponderosa pine forests at Zion National Park, Utah: Restoration of pattern and process after a century of fire exclusion

2. Global characterization of fire activity: toward defining fire regimes from Earth observation data

3. Forest Fire Trend and Influence of Climate Variability in India: A Geospatial Analysis at National and Local Scale

4. Historical background and current developments for mapping burned area from satellite Earth observation

5. Forest fire characteristics in China: Spatial patterns and determinants with thresholds