title: Remote Sensing of Agro-droughts in Guangdong Province of China Using MODIS Satellite Data.
abstract: A practical approach was developed in the study for drought monitoring in Guangdong province of China on the basis of vegetation supply water index (VSWI) and precipitation distance index (PDI). A comprehensive index for assessment of agro-drought severity (SADI) was then established from the normalized VSWI and PDI. Using MODIS satellite images and precipitation data from ground-observed meteorological stations, we applied the approach to Guangdong for drought monitoring in 2006. The monitoring results showed that the drought severity on average was very low in the province during the main growing season from May to September in 2006. However, seasonal variation of the severity was also obvious in difference counties of the province. Higher severity of drought could be seen in the periods of late-June (In China each month is traditionally divided into 3 periods. Each is with 10 days and has different names. This division system is mainly with consideration of farming seasons hence has been widely used as the basis of drought monitoring periods in China. In order to keep this tradition, we define, for example, for June, the early-June as the period from 1stto 10thof June, the mid-June as the period from 11thto 20th, and the late-June as the period from 21stto 30th. So mid-August denotes the period from 11thto 20thof August, and early-July the period from 1stto 10th of July, and so on.), early-July, mid-August and late-September. Regionally, Leizhou Peninsula in the west had the most serious drought before mid-May. Validation indicated that our monitoring results were generally consistent with the drought statistics data and the results from Chinese National Satellite Meteorological Center (CNSMC), which used only remote sensing data. This consistence confirmed the applicability of our approach for drought monitoring. Our better identification of drought severity in Leizhou Peninsula of western Guangdong than that of CNSMC might suggest that the approach developed in the study was able to provide a better alternative to increase the accuracy of drought monitoring for agricultural administration and farming.
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
authors.forename: Maofang
authors.initials: M
authors.lastname: Gao
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China. qinzh@caas.net.cn.|Guangdong Public Laboratory of Environmental Science and Technology, Guangzhou Institute of Geography, Guangzhou 510650, China. qinzh@caas.net.cn.|International Institute for Earth System Science, Nanjing University, Nanjing 210093, China. qinzh@caas.net.cn.
authors.forename: Zhihao
authors.initials: Z
authors.lastname: Qin
authors.affiliation: Guangdong Public Laboratory of Environmental Science and Technology, Guangzhou Institute of Geography, Guangzhou 510650, China.
authors.forename: Hong'ou
authors.initials: H
authors.lastname: Zhang
authors.affiliation: International Institute for Earth System Science, Nanjing University, Nanjing 210093, China.
authors.forename: Liping
authors.initials: L
authors.lastname: Lu
authors.affiliation: Guangdong Public Laboratory of Environmental Science and Technology, Guangzhou Institute of Geography, Guangzhou 510650, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Zhou
authors.affiliation: Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
authors.forename: Xiuchun
authors.initials: X
authors.lastname: Yang
keywords: Guangdong province; MODIS data.; agricultural drought; drought monitoring; remote sensing