首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于时空不确定性分析的北京市农田土壤重金属镉含量等级划分
引用本文:李晓岚,高秉博,周艳兵,潘瑜春,郜允兵,李斌,胡茂桂.基于时空不确定性分析的北京市农田土壤重金属镉含量等级划分[J].农业环境科学学报,2019,38(2):307-316.
作者姓名:李晓岚  高秉博  周艳兵  潘瑜春  郜允兵  李斌  胡茂桂
作者单位:北京市农业物联网工程技术研究中心, 北京 100097;农业部农业信息技术重点实验室, 北京 100097,北京市农业物联网工程技术研究中心, 北京 100097;农业部农业信息技术重点实验室, 北京 100097,北京市农业物联网工程技术研究中心, 北京 100097;农业部农业信息技术重点实验室, 北京 100097,北京农业信息技术研究中心, 北京 100097;国家农业信息化工程技术研究中心, 北京 100097,北京农业信息技术研究中心, 北京 100097;国家农业信息化工程技术研究中心, 北京 100097,北京农业信息技术研究中心, 北京 100097;国家农业信息化工程技术研究中心, 北京 100097,中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101
基金项目:国家重点研发计划课题(2016YFD0800904);北京市科技创新基地培育与发展工程专项项目(Z161100005016110);北京市农林科学院科技创新能力建设专项(KJCX20170407);北京市优秀人才培养资助项目(2016000020060G123)
摘    要:为了从时空角度探讨耕地土壤环境质量的类别划分并为差别化利用和管理土地提供可参考信息,针对多年期采样数据,采用基于时空指示克里金的方法对北京市2013年农田土壤重金属镉含量进行等级划分。其中通过自适应方法确定了等级划分最适宜的概率阈值,并基于等级错划指数估计了等级划分的不确定性。结果表明:相较于基于时空普通克里金的方法,基于时空指示克里金方法划分的等级具有更高的准确率。2013年北京市镉含量等级为超过背景值的农田区域主要分布在昌平大部分地区、平谷中部地区、大兴南部地区、房山南部等靠近城镇中心的地带,等级为低于背景值的农田区域则主要分布在延庆西部地区、怀柔北部等远离城镇中心的地带。镉含量等级的错划指数分布反映了北京市农田土壤重金属镉含量等级划分的不确定性程度。等级划分的不确定性在一定程度上受点位分布及概率阈值的影响。基于时空指示克里金的等级划分方法可为开展耕地土壤环境质量类别划分工作提供辅助支撑。

关 键 词:时空指示克里金  等级划分  概率阈值  不确定性
收稿时间:2018/4/26 0:00:00
修稿时间:2018/8/8 0:00:00

Classification of soil heavy metal cadmium content grade in Beijing farmland based on spatio-temporal uncertainty analysis
LI Xiao-lan,GAO Bing-bo,ZHOU Yan-bing,PAN Yu-chun,GAO Yun-bing,LI Bin and HU Mao-gui.Classification of soil heavy metal cadmium content grade in Beijing farmland based on spatio-temporal uncertainty analysis[J].Journal of Agro-Environment Science( J. Agro-Environ. Sci.),2019,38(2):307-316.
Authors:LI Xiao-lan  GAO Bing-bo  ZHOU Yan-bing  PAN Yu-chun  GAO Yun-bing  LI Bin and HU Mao-gui
Institution:Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China;Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China,Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China;Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China,Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China;Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China,Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China,Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China,Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China and State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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.
Keywords:spatio-temporal Indicator Kriging  grade classification  probability threshold  uncertainty
本文献已被 CNKI 等数据库收录!
点击此处可从《农业环境科学学报》浏览原始摘要信息
点击此处可从《农业环境科学学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号