Random agricultural burning such as crop straw fire, especial during the harvest seasons of summer and autumn, is a very common phenomenon in rural or suburban cities in China. However, several pollutions may caused by this kind of biomass burning including climate-destructive aerosols and carbon fluxes which decrease seriously regional air quality and may have an negative impact on public human health leading to respiratory illness. Using remote sensing is an available method to detect and monitor agricultural burning arbitrarily with its better time and spatial effectiveness. As a part of EOS mission, MODIS was suitable for fire detection as some high-temperature-sensitive bands of the sensor had been improved. A hybrid algorithm presented by the paper had archived two major advancements on adjusting the potential thresholds to suit lower temperature of crop straw burning than forest fires and introducing latest land cover data to exclude fake agriculture burning fire points which not located in croplands. The results had been validated by FIRMS's active fire production suggesting that the modified algorithm works well for agriculture burning under complex land characteristic of eastern China, especially in Zhejiang province. A very large potential for satellite data as an efficient method to detect agriculture burning was also demonstrated in the study.
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