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| Classification of soil heavy metal cadmium content grade in Beijing farmland based on spatio-temporal uncertainty analysis |
| Received:April 26, 2018 Revised:August 08, 2018 |
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| KeyWord:spatio-temporal Indicator Kriging;grade classification;probability threshold;uncertainty |
| Author Name | Affiliation | E-mail | | LI Xiao-lan | Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China
Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China | | | GAO Bing-bo | Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China
Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China | | | ZHOU Yan-bing | Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China
Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China | zhouyb@nercita.org.cn | | PAN Yu-chun | Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | GAO Yun-bing | Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | LI Bin | Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | | HU Mao-gui | State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China | |
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| Abstract: |
| For differential use and management of land, it is important to explore the category classification of farmland soil environmental quality from a spatio-temporal perspective. In this study, based on multi-year sample data, we used the spatio-temporal Indicator Kriging method to classify the grade of farmland soil heavy metal cadmium content in Beijing in 2013. The self-adaptive determination method was adopted to determine the optimal probability threshold of grade classification, and a classification error index was utilized to evaluate grade classification uncertainty. The results showed that the method based on the spatio-temporal Indicator Kriging had better performance with higher accuracy than the spatio-temporal Ordinary Kriging method. The regions where the cadmium content grade was higher than the background value were mainly located in most areas of Changping, the central area of Pinggu, and the southern area of Daxing, which are all near the urban center. In contrast, the regions where the cadmium content grade was lower than the background value were mainly located in the west part of Yanqing and the northern part of Huairou, which are at some distance from the urban center. The classification error index distribution reflected the uncertainty degree of the grade classification of soil cadmium content. The uncertainty is, to an extent, affected by the distribution of sample points and probability threshold. A grade classification method based on spatio-temporal Indicator Kriging can be used to support the classification of soil environmental quality categories. |
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