The Adaptation Research On Spatiotemporal Patterns Of Remote Sensing Drought Index

Drought is one of the severest nature disasters for its long duration, a wide range affect, disaster losses weight and other characteristics, and for the frequent occurrence of drought in China, the country's economic development and daily life suffered a great loss. Therefore, drought monitoring and control the relationship between the development and its influencing factors, forecast drought in scientific and reasonable, has important practical significance to the reduction of disaster losses and sustainable development of society. Remote Sensing is playing an increasingly important role in drought monitoring, with its wide range of monitoring and quickly data updates. Henan province was taken as the case, on the basis of MODIS image, Normalized Difference Vegetation Index (NDVI), Anomaly Vegetation Index (AVI), Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) was calculated separately, and compare and analyze precision of the indices under the same spatial and temporal patterns, to select the Remote Sensing of drought index of high precision under different spatial and temporal patterns, and improve the precision of remote sensing of drought monitoring.This paper process the meteorological data of each measure site from China monthly surface climate data set, select the meteorological data site of Henan province, calculate precipitation anomaly percentage of Henan province using site coordinates and monthly precipitation of meteorological data and other information, and analyze the drought condition of Henan province in nearly decade; re-project and cut the MODIS image(monthly vegetation index of lkm resolution, land surface temperature of lkm resolution) and other pretreatment by MRT and ENVI to obtain the image of Henan province, calculate popular Remote Sensing image of drought index base on the formula. According to administrative divisions, Henan Province is divided into five regions (mid Henan, eastern Henan, southern Henan, western Henan and northern Henan) to analyze the precision of popular Remote Sensing of drought index of different spatial and temporal condition, statistic Remote Sensing of drought index and precipitation anomaly percentage of sub area. Take month, quarter and year as time scale, each sub area as spatial condition to analyze the correlation of traditional drought index and Remote Sensing of drought index, and select the Remote Sensing of high precision in different spatial and temporal condition. From the research results, the best correlation with precipitation is AVI in eastern Henan while the other is NDVI, so the use of NDVI to predict drought conditions with high accuracy when research drought condition of each sub area with monthly Remote Sensing of drought index value of annual average, and when research drought condition by quarter, the highest correlation of Remote Sensing of drought index and precipitation in four seasons is VCI, VCI, TCI and TCI in mid Henan; the follow is AVI, VCI, TCI and NDVI in eastern Henan; VCI, AVI, AVI and NDVI in southern Henan; TCI, VCI, VCI and NDVI in western Henan; AVI, VCI, AVI and TCI in northern Henan.