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Application of five atmospheric correction models for Landsat TM data in vegetation remote sensing.

Keywords: 大气校正,黑体减法模型,6S模型,植被遥感,影像,大气,校正模型,植被遥感,应用,remote,sensing,vegetation,data,Landsat,TM,models,atmospheric,correction,选择,分析,比较,区域,遥感研究,信息量最大,精度,结果,评价

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Based on the Landsat TM image of northeast Guangzhou City and north Huizhou City on July 18, 2005, and compared with apparent reflectance model, five atmospheric correction models including four dark object subtraction models and 6S model were evaluated from the aspects of vegetation reflectance, surface reflectance, and normalized difference vegetation index (NDVI). The results showed that the dark object subtraction model DOS4 produced the highest accurate vegetation reflectance, and had the largest information loads for surface reflectance and NDVI, being the best for the atmospheric correction in the study areas. It was necessary to analyze and to compare different models to find out an appropriate model for atmospheric correction in the study of other areas.


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