Lin Li, Jing Dong, Jiageng Dong, Bo Yu, Jichang Peng, Jianbin He
{"title":"用普通克里格法预测牛地方性氟中毒的空间分布","authors":"Lin Li, Jing Dong, Jiageng Dong, Bo Yu, Jichang Peng, Jianbin He","doi":"10.1515/BVIP-2015-0024","DOIUrl":null,"url":null,"abstract":"Abstract The aim of the studies was to develop an alternative method which could overcome the lack of sampling to improve the efficiency of control efforts for bovine endemic fluorosis. The spatial distribution characteristics of the disease were analysed and a prediction model for the estimation of fluorosis distribution in some districts in northwest Liaoning province in China was established. The model used ordinary kriging, and was evaluated using cross-validation. Analysis showed that the distribution of the disease was spatial autocorrelation. The prediction error of the cross-validation (ME = -0.0092, PMSE = 0.627, AKSE = 0.597, and RMSP = 1.007) and comparison with the actual disease distribution indicated that the prediction map accurately distributed bovine endemic fluorosis. It is feasible to predict bovine endemic fluorosis in the area by using ordinary kriging and limited data.","PeriodicalId":9462,"journal":{"name":"Bulletin of The Veterinary Institute in Pulawy","volume":"59 1","pages":"161 - 164"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/BVIP-2015-0024","citationCount":"1","resultStr":"{\"title\":\"Prediction of the Spatial Distribution of Bovine Endemic Fluorosis Using Ordinary Kriging\",\"authors\":\"Lin Li, Jing Dong, Jiageng Dong, Bo Yu, Jichang Peng, Jianbin He\",\"doi\":\"10.1515/BVIP-2015-0024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The aim of the studies was to develop an alternative method which could overcome the lack of sampling to improve the efficiency of control efforts for bovine endemic fluorosis. The spatial distribution characteristics of the disease were analysed and a prediction model for the estimation of fluorosis distribution in some districts in northwest Liaoning province in China was established. The model used ordinary kriging, and was evaluated using cross-validation. Analysis showed that the distribution of the disease was spatial autocorrelation. The prediction error of the cross-validation (ME = -0.0092, PMSE = 0.627, AKSE = 0.597, and RMSP = 1.007) and comparison with the actual disease distribution indicated that the prediction map accurately distributed bovine endemic fluorosis. It is feasible to predict bovine endemic fluorosis in the area by using ordinary kriging and limited data.\",\"PeriodicalId\":9462,\"journal\":{\"name\":\"Bulletin of The Veterinary Institute in Pulawy\",\"volume\":\"59 1\",\"pages\":\"161 - 164\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/BVIP-2015-0024\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin of The Veterinary Institute in Pulawy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/BVIP-2015-0024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of The Veterinary Institute in Pulawy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/BVIP-2015-0024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of the Spatial Distribution of Bovine Endemic Fluorosis Using Ordinary Kriging
Abstract The aim of the studies was to develop an alternative method which could overcome the lack of sampling to improve the efficiency of control efforts for bovine endemic fluorosis. The spatial distribution characteristics of the disease were analysed and a prediction model for the estimation of fluorosis distribution in some districts in northwest Liaoning province in China was established. The model used ordinary kriging, and was evaluated using cross-validation. Analysis showed that the distribution of the disease was spatial autocorrelation. The prediction error of the cross-validation (ME = -0.0092, PMSE = 0.627, AKSE = 0.597, and RMSP = 1.007) and comparison with the actual disease distribution indicated that the prediction map accurately distributed bovine endemic fluorosis. It is feasible to predict bovine endemic fluorosis in the area by using ordinary kriging and limited data.