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comparisonofarcgisandsasgeostatisticalanalysttoestimatepopulationweightedmonthlytemperatureforuscounties
Qi Xiaopeng1; Wei Liang2; Barker Laurie2; Lekiachvili Akaki3; Zhang Xingyou4
2012
Source Publicationjournalofresourcesandecology
ISSN1674-764X
Volume3Issue:3Pages:220
AbstractTemperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature's association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly—or 30-day—basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R~2, mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS's merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects.
Language英语
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/100790
Collection中国科学院地理科学与资源研究所
Affiliation1.中国科学院地理科学与资源研究所
2.Division of Oral Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention
3.Office of Informatics and Information Resources Management, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention
4.Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention
First Author Affilication中国科学院地理科学与资源研究所
Recommended Citation
GB/T 7714
Qi Xiaopeng,Wei Liang,Barker Laurie,et al. comparisonofarcgisandsasgeostatisticalanalysttoestimatepopulationweightedmonthlytemperatureforuscounties[J]. journalofresourcesandecology,2012,3(3):220.
APA Qi Xiaopeng,Wei Liang,Barker Laurie,Lekiachvili Akaki,&Zhang Xingyou.(2012).comparisonofarcgisandsasgeostatisticalanalysttoestimatepopulationweightedmonthlytemperatureforuscounties.journalofresourcesandecology,3(3),220.
MLA Qi Xiaopeng,et al."comparisonofarcgisandsasgeostatisticalanalysttoestimatepopulationweightedmonthlytemperatureforuscounties".journalofresourcesandecology 3.3(2012):220.
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