Spatial Prediction of Heavy Metal Pollution for Soils in Peri-Urban Beijing, China Based on Fuzzy Set Theory

TAN Man-Zhi; XU Fang-Ming; CHEN Jie; ZHANG Xue-Lei; CHEN Jing-Zhong

首页> 外文期刊>土壤圈（英文版） >Spatial Prediction of Heavy Metal Pollution for Soils in Peri-Urban Beijing, China Based on Fuzzy Set Theory

【24h】

Spatial Prediction of Heavy Metal Pollution for Soils in Peri-Urban Beijing, China Based on Fuzzy Set Theory

机译：基于模糊集理论的北京周边城市土壤重金属污染空间预测

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

页面导航

摘要
著录项
相关主题

摘要

Fuzzy classification combined with spatial prediction was used to assess the state of soil pollution in the peri-urban Beijing area. Total concentrations of As, Cr, Cd, Hg, and Pb were determined in 220 topsoil samples (0-20 cm) collected using a grid design in a study area of 2 600 km2. Heavy metal concentrations were grouped into three classes according to the optimum number of classes and fuzziness exponent using the fuzzy c-mean (FCM) algorithm. Membership values were interpolated using ordinary kriging. The polluted soils of the study area induced by the measured heavy metals were concentrated in the northwest corner and eastern part, especially the southeastern part close to the urban zone, whereas the soils free of pollution were mainly distributed in the southwestern part. The soils with potential risk of heavy metal pollution were located in isolated spots mainly in the northern part and southeastern corner of the study region. The FCM algorithm combined with geostatistical techniques, as compared to conventional single geostatistical kriging methods,could produce a prediction with a quantitative uncertainty evaluation and higher reliability. Successful prediction of soil pollution achieved with FCM algorithm in this study indicated that fuzzy set theory had great potential for use in other areas of soil science.

机译：采用模糊分类与空间预测相结合的方法，对北京郊区的土壤污染状况进行了评估。在2 600 km2的研究区域中，使用网格设计确定了220个表土样品（0-20厘米）中As，Cr，Cd，Hg和Pb的总浓度。使用模糊c均值（FCM）算法根据最佳类别数和模糊指数将重金属浓度分为三类。使用普通克里金插值成员值。被测重金属诱导的研究区污染土壤主要集中在西北角和东部，特别是靠近市区的东南部，而无污染的土壤主要分布在西南部。具有重金属污染风险的土壤主要位于研究区域的北部和东南角的偏远地区。与传统的单一地统计克里金法相比，将FCM算法与地统计技术相结合，可以产生具有定量不确定性评估和更高可靠性的预测。通过FCM算法对土壤污染的成功预测表明，模糊集理论在土壤科学的其他领域具有巨大的潜力。

著录项

来源
《土壤圈（英文版）》 |2006年第5期|545-554|共10页
作者
TAN Man-Zhi; XU Fang-Ming; CHEN Jie; ZHANG Xue-Lei; CHEN Jing-Zhong;
展开▼
作者单位

State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,Nanjing 210008 (China);

Graduate school of the Chinese Academy of Sciences, Beijing 100039 (China);

Chengdu University of Technology, Chengdu 610059 (China);

State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,Nanjing 210008 (China);

State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,Nanjing 210008 (China);

Nanjing Station of Soil and Fertilizer, Nanjing 210036 (China);

展开▼
收录信息中国科学引文数据库(CSCD);
原文格式 PDF
正文语种 chi
中图分类农业基础科学;
关键词
continuous classification; fuzzy c-means; heavy metal; soil pollution; spatial prediction;

机译：连续分类;模糊C均值;重金属;土壤污染;空间预测;

Spatial Prediction of Heavy Metal Pollution for Soils in Peri-Urban Beijing, China Based on Fuzzy Set Theory

摘要

著录项

相关主题

期刊订阅