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| Statistical inference and the additional sampling optimization method for soil environmental quality grade classification: A review |
| Received:October 19, 2020 |
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| KeyWord:environmental quality;grade classification;additional sampling;statistical inference |
| Author Name | Affiliation | | GAO Bing-bo | College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Key Laboratory of Agri-informatics, Ministry of Agriculture and Rural Affairs, Beijing 100083, China | | HAO Zhao-zhan | College of Land Science and Technology, China Agricultural University, Beijing 100083, China | | LI Fa-dong | Institute of Geographic Sciences and Natural Resources, Chinese Academy of Sciences, Beijing 100011, China | | HU Mao-gui | Institute of Geographic Sciences and Natural Resources, Chinese Academy of Sciences, Beijing 100011, China | | LI Xiao-lan | National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | GAO Yun-bing | National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China | | PAN Yu-chun | National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China |
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| Abstract: |
| Environmental quality grade classification is one crucial goal of soil surveying and monitoring. Unlike global mean estimation and spatial interpolation, environmental quality grade classification only focuses on estimating the relationship between pollutant concentration and grading threshold. Due to spatial autocorrelation, soil environmental quality grades are usually spatially continuous. Thus, to improve the classification precision of environmental quality grades, more sampling points should be laid in the transition area for environmental quality grades. However, because the primary survey sampling points are usually sparse and produce large errors and uncertainty in the estimated result, it is difficult to reflect the transition area of true grades. Additionally, applications have different requirements for the two types of errors in grade classification. The particularity of environmental quality grade classification needs special inference and sampling optimization design methods. This study analyzed the inference and additional sampling optimization design method for environmental quality grade classification locally and globally. The method framework is also summarized, and future research is discussed. This work's outcome can provide a method selection basis for several agricultural soil environmental management applications, such as soil environmental quality grade classifications of agricultural land and definition of polluted areas for soil environmental remediation. |
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