基于亮温-植被指数-气溶胶光学厚度的MODIS火点监测算法研究  

An Improved Algorithm for Forest Fire Detection:A Study based on Brightness Temperature,Vegetation Index and AOD

作　　者：张婕[1,2] 张文煜[1] 冯建东[3] 王宏义[2] 于泽[2] 宋玮[2] Zhang Jie Zhang Wenyu FengJiandong Yu Ze Wang Hongyi Song Wei(Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province,College of Atmospheric Sciences ,Lanzhou University ,Lanzhou 730000,China College of Atmospheric Sciences ,Chengdu University of Information Technology,Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,Chengdu 610225,China Agricultural Meteorological Center of Sichuan Province ,Chengdu 610072, China)

机构地区：[1]兰州大学大气科学学院,甘肃省干旱气候变化与减灾重点实验室,甘肃兰州730000 [2]成都信息工程大学大气科学学院,高原大气与环境四川省重点实验室,四川成都610225 [3]四川省农业气象中心,四川成都610072

出　　处：《遥感技术与应用》2016年第5期886-892,共7页Remote Sensing Technology and Application

基　　金：国家自然科学基金项目(41305042、41225018);中国气象局大气探测重点开放实验室开放课题(KLAS201408)共同资助

摘　　要：MODIS火灾产品的火点检测算法主要以4和11μm通道亮温数据来识别火点,在应用于不同地区和不同季节时有一定局限性。在分析MODIS现有火点检测算法的基础上,对算法相关阈值及参数进行适当调整,同时考虑火灾前后NDVI的变化,以及林火燃烧过程中伴生烟羽使火点下风方气溶胶光学厚度明显增加的特点,构建了基于亮温—植被指数—气溶胶光学厚度的火点识别算法,并应用多次火灾个例对本算法进行验证。结果表明:算法提高了对高温热点和低温焖烧火点的识别能力,有效降低了高温热点的误报率和低温火点的漏报率,使火点检测算法在不同环境的适应性有所增强。The traditional Moderate Resolution Imaging Spectroradiometer （MODIS） fire detection algo- rithm relies primarily on hot spot detection using brightness temperature data derived from the 4 and 11 channels.There are limitations to the effectiveness of this algorithm when it is applied to monitor forest fires in different regions and four seasons. In response to these problems, a detailed description of an im- proved algorithm based on brightness temperature,vegetation index and Aerosol Optical Depth （AOD） is offered by adjusting the corresponding potential fire thresholds and contextual thresholds in the traditional algorithm,by exploring the differences in the post-fire and pre-fire values of the Normalized Difference Vegetation Index（NDVI） ,and by analysing the obvious increase in the AOD on the leeward side caused by the spread of a smoke plume.This approach is confirmed by several fire events in China.The study reveals that the improved algorithm achieves significantly lower false alarm rates and is more sensitive to cool fires.Then the adaptability of this algorithm in all environment is also enhanced.

关 键 词：森林火灾 算法 气溶胶光学厚度 归一化植被指数 

分 类 号：P407[天文地球—大气科学及气象学] TP79[自动化与计算机技术—检测技术与自动化装置]