{"title":"利用MODIS垂直干旱指数进行干旱监测","authors":"Yuanyuan Chen, Li Sun, Kai Liu, Zhiyuan Pei","doi":"10.1109/Agro-Geoinformatics.2019.8820606","DOIUrl":null,"url":null,"abstract":"Drought is one of the most complex natural hazards that can produce devastating impacts on many aspects, especially on agricultural production. Insufficient site observation data for drought monitoring makes remote sensing technique a key issue for global and regional drought assessment with high spatial and temporal resolutions. Some agricultural drought indexes have been developed during the last decade. Perpendicular drought index (PDI) and modified perpendicular drought index (MPDI) have received considerable attention because of their simplicity and efficacy. In this paper, PDI and MPDI were calculated using MODIS data and applied to assess the 2018 spring drought under dense vegetation cover condition in the south of Hebei Province. The validation was carried out using in situ relative soil water content from 0 to 10 cm and the consistency between perpendicular drought indexes, including PDI and MPDI, and in situ soil water content was analyzed. Result shows a good agreement between the drought information extracted by PDI and MPDI and the field measurement of soil water content, with the correlation coefficients of –0.62 and –0.74.","PeriodicalId":143731,"journal":{"name":"2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Drought monitoring using MODIS derived perpendicular drought indexes\",\"authors\":\"Yuanyuan Chen, Li Sun, Kai Liu, Zhiyuan Pei\",\"doi\":\"10.1109/Agro-Geoinformatics.2019.8820606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Drought is one of the most complex natural hazards that can produce devastating impacts on many aspects, especially on agricultural production. Insufficient site observation data for drought monitoring makes remote sensing technique a key issue for global and regional drought assessment with high spatial and temporal resolutions. Some agricultural drought indexes have been developed during the last decade. Perpendicular drought index (PDI) and modified perpendicular drought index (MPDI) have received considerable attention because of their simplicity and efficacy. In this paper, PDI and MPDI were calculated using MODIS data and applied to assess the 2018 spring drought under dense vegetation cover condition in the south of Hebei Province. The validation was carried out using in situ relative soil water content from 0 to 10 cm and the consistency between perpendicular drought indexes, including PDI and MPDI, and in situ soil water content was analyzed. Result shows a good agreement between the drought information extracted by PDI and MPDI and the field measurement of soil water content, with the correlation coefficients of –0.62 and –0.74.\",\"PeriodicalId\":143731,\"journal\":{\"name\":\"2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Agro-Geoinformatics.2019.8820606\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Agro-Geoinformatics.2019.8820606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drought monitoring using MODIS derived perpendicular drought indexes
Drought is one of the most complex natural hazards that can produce devastating impacts on many aspects, especially on agricultural production. Insufficient site observation data for drought monitoring makes remote sensing technique a key issue for global and regional drought assessment with high spatial and temporal resolutions. Some agricultural drought indexes have been developed during the last decade. Perpendicular drought index (PDI) and modified perpendicular drought index (MPDI) have received considerable attention because of their simplicity and efficacy. In this paper, PDI and MPDI were calculated using MODIS data and applied to assess the 2018 spring drought under dense vegetation cover condition in the south of Hebei Province. The validation was carried out using in situ relative soil water content from 0 to 10 cm and the consistency between perpendicular drought indexes, including PDI and MPDI, and in situ soil water content was analyzed. Result shows a good agreement between the drought information extracted by PDI and MPDI and the field measurement of soil water content, with the correlation coefficients of –0.62 and –0.74.