Drought Detection of West Java's Paddy Field Using MODIS EVI Satellite Images (Case Study: Rancaekek and Rancaekek Wetan)

AbstractNowadays, drought phenomenon occurred in several area in Indonesia. The length of the dry season, especially in the southern equatorial allegedly caused by El Nino phenomenon. This causes crop failures in many center area of agriculture. West Java Province as one of the centers of agricultural activities in Indonesia experienced a severe drought within a period of 6 months (April-September in 2003). The monitoring of drought is useful to understanding the characterization of drought itself. In the next period, we can decide what should we do to decreased the impact of this phenomenon. The study aimed to implement Breaks for Additive Seasonal and Trend (BFAST) algorithm for detecting and monitoring paddy field areas experiencing drought in The West Java during the period 2000-2015. This study used remote sensing data to study the response of vegetation on the drought phenomenon. MODIS EVI time series were decomposed into seasonal, trend, and remainder component using BFAST which enables the detection of trend changes within the time series. The result of study shows that BFAST able to detect drought in MODIS EVI time series. The result also compared to a new drought index, called SPEI