摘要
在MODIS火点检测算法基础上提出一种自适应火点检测的改进算法,并对改进算法进行的构建详细描述。改进的算法按照直方图统计来选择进行非火点排除的中红外通道亮温阂值,利用背景像素相对增温法判断疑似火点,提高了火点的识别能力。另外改进算法对云覆盖下的火点也有一定的识别能力。选择中国小火点发生频繁的广东地区进行改进算法的检验,结果表明火点检测效果理想。
Satellite remote sensing of active fires provide an important tool for monitoring and locating wild fires.At present,more and more satellites and sensors have been used to monitor the fires.The Moderate Resolution Imaging Spec- troradiometer(MODIS)sensor,on board the Terra and Aqua satellites in Earth Observing System(EOS)of National Aeronautics and Space Administration(NASA),have offered an improved combination of spectral,temporal and spatial resolution for global fire detection compared with previous sensors,and have become the major data source as the substi- tute for the Advanced Very High Resolution Radiometer(AVHRR)sensor,widely used for fire detection.MODIS global active fire detection algorithm,proposed by the MODIS fire team from NASA,and based on original MODIS detection algorithm and heritage algorithms which is developed for the AVHRR and the Visible and Infrared Scanner(VIRS),was designed for global active fire products.But the MODIS fire algorithm is imperfect for fire detection in China.There are two reasons which could cause mistakes in fire detection:one is the threshold of mid-infrared channel used to exclude the false fire pixels is so big that many fires with lower brightness temperature are eliminated,the other is some fires with higher brightness temperature,which could be identified easily with human eyes in 4μm band,are omitted for the errors of potential fire pixels during the selection of background contextual pixels.This paper introduces an improved algorithm of self-adaptive fire detection for MODIS data based on MODIS global fire detection algorithm,which makes use of the bright- ness temperature derived from the MODIS 4μm and 6μm channels to carry out fire detection,and the improved algorithm is described in detail.The active fire detection strategy is based on absolute detection of the fire.The latter test identifies pixels with values elevated above a background thermal emission obtained from the surrounding contextual pixels.This method accounts for variability of the surface
出处
《遥感学报》
EI
CSCD
北大核心
2008年第3期448-453,共6页
NATIONAL REMOTE SENSING BULLETIN
基金
广东省科技攻关项目(编号:20053050011)
