A locating method based on the Anselin elocal spatial autocorrelation model which researches in the heavy metal pollution source
- DOI
- 10.2991/icmemtc-16.2016.321How to use a DOI?
- Keywords
- Pollution source ;Cokriging ;Anselin spatial clustering
- Abstract
Based on the given data of As content in the soil ,using Log transformation, the Box-Cox transformation to exclude outlier for preprocessing data to meet the normal distribution.Using Anselin elocal spatial autocorrelation model to carry on local spatial clustering in order to cluster the similar attribute values to a class.Preliminary view is that the sources of pollution distribute within the region of tne distribution of these points.The thesis build Cokriging interpolation model to interpolate of the global by the ArcGis software in order to higher concentration of the surface domain.The similar points obtained by spatial clustering properties fall on the higher concentration of the surface domain obtained by Cokriging interpolation is the region for the location of pollution sources.We focus on the analysis of As,finalize two As sources of pollution of surface domain,one of the sources of pollution range is (9277,11121), (16148,16432)]andthe other is [(3573, 4777),(6213,4897)].Then the artical uses the cross validation error analysis methods to test Cokriging interpolation model and found that cross-validation result is very good, model checking has reached a certain accuracy.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jinming Fu AU - Yuanfan Li PY - 2016/04 DA - 2016/04 TI - A locating method based on the Anselin elocal spatial autocorrelation model which researches in the heavy metal pollution source BT - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control PB - Atlantis Press SP - 1694 EP - 1698 SN - 2352-5401 UR - https://doi.org/10.2991/icmemtc-16.2016.321 DO - 10.2991/icmemtc-16.2016.321 ID - Fu2016/04 ER -