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五种TM影像大气校正模型在植被遥感中的应用 被引量:7

Application of five atmospheric correction models for Landsat TM data in vegetation remote sensing.
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摘要 基于2005年7月18日广州市东北部和惠州市北部的TM影像,以表观反射率模型为参照,从植被反射率光谱、地物反射率统计特征、规一化植被指数三方面对4种黑体减法模型和6S模型在植被遥感中的应用进行了评价.结果表明:黑体减法模型DOS4获得了精度较高的植被反射率,其地物反射率与规一化植被指数的信息量最大,适用于研究区的植被遥感研究.对于不同区域的植被遥感研究需要进行具体的比较分析,才能选择到合适的大气校正模型. 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.
出处 《应用生态学报》 CAS CSCD 北大核心 2008年第4期769-774,共6页 Chinese Journal of Applied Ecology
基金 国家"985"工程科技创新平台资助项目(105203200400006)
关键词 大气校正 黑体减法模型 6S模型 植被遥感 atmospheric correction dark object subtraction model 6S model vegetation remote sensing.
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参考文献24

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