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| Modeling to Predict Lead and Nickel Contents in Soil of the Mid- and Lower Reaches of Shiting River Using RS and GIS |
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| KeyWord:lead; nickel; RS; prediction modeling; GIS; spatial distribution |
| Author Name | Affiliation | | YAO Ping | College of Resources and Environment, Sichuan Agricultural University, Chengdu 611130, China
Key Laboratory of Soil Environment Protection of Sichuan Province, Chengdu 611130, China | | ZHANG Dong | Agricultural Bureau of Deyang, Deyang 618000, China | | ZHANG Shi-rong | College of Resources and Environment, Sichuan Agricultural University, Chengdu 611130, China
Key Laboratory of Soil Environment Protection of Sichuan Province, Chengdu 611130, China | | XU Xiao-xun | College of Resources and Environment, Sichuan Agricultural University, Chengdu 611130, China
Key Laboratory of Soil Environment Protection of Sichuan Province, Chengdu 611130, China | | LI Ting | College of Resources and Environment, Sichuan Agricultural University, Chengdu 611130, China
Key Laboratory of Soil Environment Protection of Sichuan Province, Chengdu 611130, China |
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| Abstract: |
| Predicting soil heavy metal contents is critical for soil pollution assessment and early warming management. In this work, the remote sensing spectral data from Landsat7 ETM+, soil Pb and Ni contents（70 samples from 0~20 cm soil layer） and the related ground parameters in the mid- and lower reaches of Shiting River were integrated to construct a model for predicting soil Pb and Ni contents in this area. The space inversion was employed to check the model reliability. Results indicated that the high prediction accuracy for Pb and Ni contents could be achieved by the constructed model using remote sensing spectral data only（P=0.000）, implying its reliability to predict soil heavy metal contents. When taking ground parameters such as soil parent materials and elevation or pH into consideration, the R2 values of the model were significantly increased（P=0.000）, with R2 values for Pb being increased from 0.276 to 0.571 and 0.606, and R2 values for Ni from 0.304 to 0.513 and 0.551, indicating the involvement of prediction accuracy by including ground parameters. The predicted values were in good agreement with the observed Pb and Ni contents in most cases. |
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