Studies on estimation of soil resistivity based on remote sensing
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    Abstract:

    Soil resistivity of Nanjing and its surrounding 15 cities/counties in the middle and lower reaches of Yangtze River is estimated,using an integrated method of field survey,laboratory chemical analysis and remote sensing retrieval.Four main influencing factors of soil resistivity,including soil moisture,soil temperature,soil soluble salt content and cation exchange capacity (CEC),were chosen to be the main factors of the estimation model.Spatial distribution of soil moisture and soil temperature were retrieved from MODIS data.A partial least squares quadratic model (PLSQM) is established to estimate soil resistivity under different land cover types.The correlation coefficient between estimated and observed soil resistivity values is 0.85,with mean relative error (MRE) being 19.02% and root mean square error (RMSE) being 7.79.Soil resistivity,estimated by PLSQM method,differs obviously under land cover of grass,crop,or forest.The proposed PLSQM method can estimate soil resistivity with high accuracy,thus has a good application potential.

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LI Bolun, SHEN Runping, YAN Jing, LIU Lei, HUANG Xiaolong. Studies on estimation of soil resistivity based on remote sensing[J]. Journal of Nanjing University of Information Science & Technology,2013,5(5):432-438

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  • Received:May 13,2012
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