Mapping forest fire risk zones with spatial data and principal component analysis  

作　　者：XU Dong, Guofan Shao, DAI Limin, HAO Zhanqing, TANG Lei & WANG Hui Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China Graduate University of Chinese Academy of Sciences, Beijing 100039, China Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907, USA Department of Management, Shenyang Institute of Aeronautical Engineering, Shenyang 110034, China Department of City Development, Jinan University, Jinan 250002, China 

出　　处：《Science China(Technological Sciences)》2006年第z1期140-149,共10页中国科学（技术科学英文版）

基　　金：jointly supported by the National Natural Science Foundation of China(Grant Nos.70373044 and 30470302);Jilin Yanbian Forestry Group,China's Ministry of Science and Technology(Grant No.04EFN216600328);Liaoning Key Technologies R&D Program(Grant Nos.2004207002 and 2004201003);the Northeast Rejuvenation Program of the Chinese Academy of Sciences.

摘　　要：By integrating forest inventory data with remotely sensed data, new data layers for factors that affect forest fire potentials were generated for Baihe Forestry Bureau in Jilin Province of China. The principle component analysis was used to sort out the relationships between forest fire potentials and environmental factors. The classifications of these factors were performed with GIS, generating three maps: a fuel-based fire risk map, a topography-based fire risk map, and an anthropogenic-factor fire risk map. These three maps were then synthesized to generate the final fire risk map. The linear regression method was used to analyze the relationship between an area-weighted value of forest fire risks and the frequency of historical forest fires at each forest farm. The results showed that the most important factor contributing to forest fire ignition was topography, followed by anthropogenic factors.By integrating forest inventory data with remotely sensed data, new data layers for factors that affect forest fire potentials were generated for Baihe Forestry Bureau in Jilin Province of China. The principle component analysis was used to sort out the relationships between forest fire potentials and environmental factors. The classifications of these factors were performed with GIS, generating three maps: a fuel-based fire risk map, a topography-based fire risk map, and an anthropogenic-factor fire risk map. These three maps were then synthesized to generate the final fire risk map. The linear regression method was used to analyze the relationship between an area-weighted value of forest fire risks and the frequency of historical forest fires at each forest farm. The results showed that the most important factor contributing to forest fire ignition was topography, followed by anthropogenic factors.

关 键 词：WILDFIRE risk  regression analysis  GEOGRAPHIC information system  remote sensing  Baihe FORESTRY Bureau. 

分 类 号：S762[农业科学—森林保护学]