A MODIS Time Series Data Based Algorithm for Mapping Forest Fire Burned Area

• Published in: Chinese geographical science Vol. 23; no. 3; pp. 344 - 352
• Main Authors: Yang, Wei, Zhang, Shuwen, Tang, Junmei, Bu, Kun, Yang, Jiuchun, Chang, Liping
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer-Verlag 01.06.2013; SP Science Press
• Subjects: algorithms; carbon; China; climate change; Earth and Environmental Science; environmental monitoring; forest fires; Geography; image analysis; moderate resolution imaging spectroradiometer; MODIS; spectral analysis; temporal variation; time series analysis; 全球环境监测; 基础; 时间序列数据; 森林火灾; 积映射; 算法; 过火面积; China, People's Rep., Heilongjiang Prov; China; Global Environmental Monitoring Index (GEMI); Burned Area Index (BAI); Burned area mapping; Moderate Resolution Imaging Spectroradiameter (MODIS)
• ISSN: 1002-0063; 1993-064X
• DOI: 10.1007/s11769-013-0597-6

Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and climate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter (MODIS) time series data in Heilongjiang Province, China. The algorithm is divided into two steps: Firstly, the ‘core’ pixels were extracted to represent the most possible burned pixels based on the comparison of the temporal change of Global Environmental Monitoring Index (GEMI), Burned Area Index (BAI) and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ‘core’ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the highest accuracy of 96.61%.