Assessing the drought monitoring characteristic of timeseries NDVI indices in crop growing season

Abstract

Many methods are generally recognized as good indicators of drought condition which are based on a transformation of normalized difference vegetation index (NDVI) data i.e. the Vegetation Condition Index (VCI) and phenology metric called Percent of Average Seasonal Greenness (PASG). Because of the immense spatial and temporal variability exhibited by each drought event, the relationship between vegetation condition and precipitation, however, is complex and has not been adequately examined with remote sensing data and meteorological drought index. The objective of this paper is assessing the drought monitoring characteristic of VCI and PASG in crop growing season which are based on 10 years (1999–2008) time-series SPOT VGT-S NDVI sequence. Multi-scale SPI (1-month, 2-month, 3-month, 6-month, 9-month and 12-month) was calculated to detect occurrence of drought using the ten-day precipitation (1960–2008) data set. By analyzing the correlation coefficients between VCI, PASG and multi-scale SPIs, three periods i.e. the time from the last ten-day of May to the middle ten-day of June, the mid-to-late August and the mid-to late September were found to be the best stages using VCI and PASG for drought monitoring. VCI, PASG and 1-month SPI-scale have a better correlation on the whole. VCI presents the better ability of drought monitoring, but PASG maintains a smooth effect on drought monitoring during the crop growing season. Besides, both of them have a very good complementary for each other.