A comparison of forest fire burned area indices based on HJ satellite data

Wenliang Liu, Litao Wang, Yi Zhou (), Shixin Wang, Jinfeng Zhu and Futao Wang
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Wenliang Liu: Chinese Academy of Sciences
Litao Wang: Chinese Academy of Sciences
Yi Zhou: Chinese Academy of Sciences
Shixin Wang: Chinese Academy of Sciences
Jinfeng Zhu: Chinese Academy of Sciences
Futao Wang: Chinese Academy of Sciences

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 81, issue 2, No 14, 980 pages

Abstract: Abstract The accurate extraction of burned area is important for biomass burning monitoring and loss evaluation. Environment and Disasters Monitoring Microsatellite Constellation put forward by China has two satellites of HJ-1A and HJ-1B in orbit. Each satellite has two CCD cameras with four bands to meet the need of mapping burned area. In order to evaluate the capability for mapping the burned area using HJ satellite’s CCD data, a forest fire occurring in Yuxi, Yunnan Province of Southwest China, was selected to analyze the spectral characteristic in the range of visible and near infrared in this paper. The research of mapping burned area was carried out based on the HJ satellites using three spectral indices (NDVI, GEMI and BAI). The color composite images including NIR band could reflect the spectral change in post-fire vegetation with a higher repetition cycle (2 days, or 1 day in some region) and higher spatial resolution (30 m). Through the comparison with the discrimination index M and extraction accuracy, the BAI has higher discrimination capability than NDVI and GEMI, and the highest M value is 2.1943. The extraction of burned area based on BAI showed higher accuracy, and the highest kappa value is 0.8957. Using HJ satellites, the map of burned area with higher temporal–spatial resolution and higher accuracy could provide the potential for dynamic monitoring and analyzing fire behavior.

Keywords: Burned area; HJ satellites; BAI; GEMI; NDVI (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11069-015-2115-x

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