{"title":"结合MODIS、NCEP/NCAR和DEM数据估算近地表大气水汽","authors":"Shanzhen Yi, Wenhao Xie, Wenxia Yu","doi":"10.1109/GEOINFORMATICS.2018.8557043","DOIUrl":null,"url":null,"abstract":"Near land surface atmospheric water vapor content is an import factor for land-atmosphere exchange, evapotranspiration and environment assessment. Currently it is lack of effective method for estimation of near land surface atmospheric water vapor content with a high spatial resolution and a large coverage area. This paper has proposed methods combining MODIS, NCEP/NCAR reanalysis data and DEM data for estimation of the near surface water vapor content. The proposed methods take advantage of NCEP/NCAR stratified pressure level data, MODIS high spatial resolution data, and DEM terrain analysis data for the estimation of near surface water vapor content. The methods are effectiveness and viable for water vapor estimation in high spatial resolution and large coverage area. An example is given for the illustration of the methods.","PeriodicalId":142380,"journal":{"name":"2018 26th International Conference on Geoinformatics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Combining MODIS, NCEP/NCAR and DEM Data for Near Land Surface Atmospheric Water Vapor Estimation\",\"authors\":\"Shanzhen Yi, Wenhao Xie, Wenxia Yu\",\"doi\":\"10.1109/GEOINFORMATICS.2018.8557043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Near land surface atmospheric water vapor content is an import factor for land-atmosphere exchange, evapotranspiration and environment assessment. Currently it is lack of effective method for estimation of near land surface atmospheric water vapor content with a high spatial resolution and a large coverage area. This paper has proposed methods combining MODIS, NCEP/NCAR reanalysis data and DEM data for estimation of the near surface water vapor content. The proposed methods take advantage of NCEP/NCAR stratified pressure level data, MODIS high spatial resolution data, and DEM terrain analysis data for the estimation of near surface water vapor content. The methods are effectiveness and viable for water vapor estimation in high spatial resolution and large coverage area. An example is given for the illustration of the methods.\",\"PeriodicalId\":142380,\"journal\":{\"name\":\"2018 26th International Conference on Geoinformatics\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 26th International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEOINFORMATICS.2018.8557043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 26th International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2018.8557043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining MODIS, NCEP/NCAR and DEM Data for Near Land Surface Atmospheric Water Vapor Estimation
Near land surface atmospheric water vapor content is an import factor for land-atmosphere exchange, evapotranspiration and environment assessment. Currently it is lack of effective method for estimation of near land surface atmospheric water vapor content with a high spatial resolution and a large coverage area. This paper has proposed methods combining MODIS, NCEP/NCAR reanalysis data and DEM data for estimation of the near surface water vapor content. The proposed methods take advantage of NCEP/NCAR stratified pressure level data, MODIS high spatial resolution data, and DEM terrain analysis data for the estimation of near surface water vapor content. The methods are effectiveness and viable for water vapor estimation in high spatial resolution and large coverage area. An example is given for the illustration of the methods.