The study of remote sensing quantitative model for soil moisture retrieval in coal mining area of Northern Shaanxi

Jinling Kong, Wenke Wang, Liang Chen, Zhiqiang Wei, Hongbin Yang, D. Guan, M. Pan, Keliang Zhou
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Abstract

The moisture storaged in soil-vadose zone is the important components of natural water cycles, which has a close relationship with water-soil-plant system and plays an important role for the healthy development of ecological environment. The study of the article developed the remote sensing quantitative model for soil moisture retrieval by statistics regression analysis based upon the soil sample parameters collected from the field, spectral data gathered simultaneously and simulated the bands of Landsat7 ETM in the typical fissure sites of coal mining area in the Northern of Shaanxi. The results showed that band4 of Landsat7 ETM is the most sensitive band for soil moisture retrieval using spectrum method. The quadratic model that was developed by remote sensing reflectance (Rrs4) (corresponding to the band4) as independent variable, is the best patterns. The root mean square error ( RMSE) is 0.59%.
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陕北煤矿区土壤水分遥感定量反演模型研究
土壤-渗透带所储存的水分是自然水循环的重要组成部分,与水-土壤-植物系统关系密切,对生态环境的健康发展具有重要作用。本文研究以陕北矿区典型裂隙点野外采集的土壤样品参数和同期采集的光谱数据为基础,模拟Landsat7 ETM波段,通过统计回归分析,建立了土壤水分遥感定量反演模型。结果表明,Landsat7 ETM波段4是光谱法反演土壤水分最敏感的波段。以遥感反射率(Rrs4)(对应波段4)为自变量建立的二次模型为最佳模式。均方根误差(RMSE)为0.59%。
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