摘要
秸秆焚烧给我国城乡生态环境造成巨大损害,利用遥感手段监测秸秆焚烧能够为禁烧治理工作提供有效的数据支持。"背景对比火点探测算法"(the Contextual Fire Detection Algorithm)是目前精度较高的自动探测算法,但固定的阈值参数难以适用于不同地区和不同的监测对象,因此依据实际观测情况对其中的关键参数和阈值进行了适当调整,以更好地监测中国地区的火点。基于EOS/Terra卫星的MODIS数据,利用调整阈值后的算法对我国华北地区2007年5月至8月的秸秆焚烧状况进行了遥感监测,监测精度能够满足实际业务化监测的需要。进一步结合IGBP地表分类数据,将火点像元分成秸秆焚烧、林火和草原火等3种生物焚烧类型,并分别对其亮度温度等多个参数进行了统计分析,在此基础上讨论了根据火点辐射特性判断火点类别的可行性,提出在目前,地表分类数据对于判断火点类别仍是必要的。
Crop residue burning has a great negative impact on the ecosystem and environment in China. Remote sensing can provide abundant information of surface fire and thus support the government to forbid the crop residue burning effectively. Although "Contextual Fire Detection Algorithm" is an automatic firedetecting algorithm with good accuracy,its fixed parameters and thresholds can not perform well in detecting fires of different kinds or in varied situations. Therefore some of the key parameters are adjusted according to the practical observations, in order to better monitor the surface fire in China. On the basis of data from EOS/Terra-MODIS,the crop residue burning in North China has been monitored from May to August in 2007 ,the accuracy of which can satisfy the requirement of practical applications. In addition,based on the IGBP classification data, the detected fire pixels are separated into 3 types of biomass burning, namely crop residue burning, forest fire and grass fire. Then the statistics and analysis of several parameters of the 3 types of fire are implemented respectively,on the basis of which the possibility of identifying the type of fire pixels according to their radiant characteristics is discussed. It is concluded that surface classification data is still necessary when identifying the fire pixels.
出处
《遥感技术与应用》
CSCD
2008年第6期611-617,I0001,I0002,共9页
Remote Sensing Technology and Application
基金
863重大项目“多源卫星遥感大气污染综合监测技术(2006AA06A303)”资助
关键词
秸秆焚烧
MODIS
背景对比火点算法
阈值调整
火点分类
MODIS
Crop residue burning
Contextual fire detection algorithm
Adjustment of threshold Classification of fire.