Distribution prediction of soil PAHs based on random forest and geostatistics methods in urban area
LI Fu-fu1, CHEN Dong-xiang3, WANG Yuan-min1, YAN Dao-hao1, WU Shao-hua2,4
1. School of Geography and Ocean science, Nanjing university, Nanjing 210046, China;
2. Institute of land and urban-rural development, Zhejiang university of Finance & Economics;Hangzhou 310018, China;
3. School of Dongfang, Zhejiang university of Finance & Economics, Hangzhou 314408;
4. The Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China
Based on the locational and environmental vairables collected at sampling points in Nanjing city, the Geostatistics and Random forest models were combined to predict the distribution of soil PAHs. Results showed that combination of these two could improve the prediction accuracy of PAHs in the research area. The model fitness achieved by the combined model was 74.8% higher than that from the traditional Kriging method. The generated map also characterized the spatial variation pattern better, and identified the high and low polluted areas. The importance of environmental variables in the output from the random forest model showed that soil carbon, soil texture and plant density were the main controlling factors for PAHS distribution. This study could provide a methodology framework for high-resolution and high-precision mapping of urban pollutants, such as PAHs.
李富富, 陈东湘, 王院民, 颜道浩, 吴绍华. 基于随机森林与地统计预测城市土壤PAHs分布[J]. 中国环境科学, 2019, 39(12): 5240-5247.
LI Fu-fu, CHEN Dong-xiang, WANG Yuan-min, YAN Dao-hao, WU Shao-hua. Distribution prediction of soil PAHs based on random forest and geostatistics methods in urban area. CHINA ENVIRONMENTAL SCIENCECE, 2019, 39(12): 5240-5247.
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