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基于6S模型的可见光、近红外遥感数据的大气校正
引用本文:阿布都瓦斯提·吾拉木,秦其明,朱黎江.基于6S模型的可见光、近红外遥感数据的大气校正[J].北京大学学报(自然科学版),2004,40(4):611-618.
作者姓名:阿布都瓦斯提·吾拉木  秦其明  朱黎江
作者单位:北京大学遥感与地理信息系统研究所,北京,100871
基金项目:国家高技术研究发展计划(863计划),国家重点基础研究发展计划(973计划)
摘    要:受大气吸收与散射的影响,电磁波在大气-目标物-遥感器途径传输过程中发生失真, 造成目标地物反射辐射能量到达遥感器时被衰减.给计算地表反照率/反射率和地表温度等关键参数带来较大的误差.选择陆地卫星7号ETM 遥感影像的可见光、近红外波段数据 ,利用6S模型,进行大气辐射校正和反射率反演.同步气象数据用于遥感器所接受的大气顶部辐射的模拟、验证和评价6S对大气校正的可靠性.最后对ETM 可见光和近红外波段数据大气校正前后的反射辐射和均一化植被指数(NDVI)的变化进行了对比研究.

关 键 词:6S模型  遥感数据的大气校正  定量遥感  可见光和近红外波段数据

6S Model Based Atmospheric Correction of Visible and Near-Infrared Data and Sensitivity Analysis
GHULAM Abduwasit,QIN Qiming,ZHU Lijiang.6S Model Based Atmospheric Correction of Visible and Near-Infrared Data and Sensitivity Analysis[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2004,40(4):611-618.
Authors:GHULAM Abduwasit  QIN Qiming  ZHU Lijiang
Abstract:Due to the distortions and noises caused by the presence of the atmosphere on the Sun target Sensor path, the space-based and airborne remote sensing information in the solar spectral range do not directly characterize the surface objects. It becomes serious impediments for the quantitative analysis and measurement of resources and environment. Ergo, the atmospheric effects are necessary to be removed, especially in land surface remote sensing and applications. An operational method of correcting visible and near infrared data for atmospheric effects is presented. The method, which is based on 6S (Second Simulation of Satellite Signal in the Solar Spectrum) and isochronous meteorological information on sensing time, is used to atmospheric correction of ETM visible and near infrared bands. Sensitivity analysis is conducted by comparisons of corrected and uncorrected reflectance data including spectral brightness and normalized difference vegetation index (NDVI). The research shows that 6S atmospheric simulation model reduces the uncertainties in the process of electromagnetic wave transmission and eliminates effectively the perturbation from geometric and system corrected remote sensing imagery.
Keywords:S model  atmospheric correction  quantitative remote sensing  visible and near  infrared data
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