Monitoring of Crop Residue Burning in North China on the Basis of MODIS Data
基于MODIS数据的华北地区秸秆焚烧监测

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 fire-detecting 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.