Abstract
Gas and particulate matter resulting from straw burning pollutes the atmospheric environment, threatening human health and traffic safety. Straw field distribution provides a basis for remote sensing monitoring of straw burning and the estimation of false fire points. In this paper, HJ-1B CCD and IRS data were used to study straw field identification and burning in Jiangsu Province, China. A Straw Multiplier Index (SMI) calculated from spectral characteristics was introduced to distinguish straw fields within farmland using HJ-1B CCD data. Then a classic fire-detection algorithm was used to extract fire points using HJ-1B IRS data. Finally, an overlay analysis was performed on the straw vector and fire vector files to extract straw-burning fire points. A comparison with the MODIS results shows that this straw-burning fire detection mode based on the HJ satellite is feasible and effective.
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