首页|Integration of Multiple Spectral Data via a Logistic Regression Al-gorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China
Integration of Multiple Spectral Data via a Logistic Regression Al-gorithm for Detection of Crop Residue Burned Areas:A Case Study of Songnen Plain,Northeast China
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The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both cru-cial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area map-ping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating mul-tiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38％to 86.90％and 73.47％to 97.14％for the 52TCQ and 51TYM cases,respectively.In comparison,the ac-curacy of the burned area map was improved to 87.14％and 98.33％for the 52TCQ and 51TYM cases,respectively by multiple vari-able logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.
crop residue burningburned areaSentinel-2 Multi Spectral Instrument(MSI)logistic regressionSongnen Plain,China
ZHANG Sumei、ZHANG Yuan、ZHAO Hongmei
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College of Mining and Engineering,Taiyuan University of Technology,Taiyuan 030024,China
Key Laboratory of Wetland Eco-logy and Environment,Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun 130102,China
国家自然科学基金Natural Science Found for Outstanding Young Scholars in Jilin Province
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