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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 NameAffiliation
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.