<![CDATA[In Indonesia, drought disasters have been reoccurring more frequently in recent years. The 1997-1998 El Nino had caused the worst drought to Indonesia in the last 50 years and disrupted rice production. Remote sensing (RS) and geographic informa-tion system (GIS) provide good capability to achieve spatially distributed information over wide area coverage and multi-temporal data to give sufficient information to anticipate those situations. The study aimed to develop a method using GIS combined with satellite data for monitoring and assessing agri-cultural drought in Brantas Watershed, Indonesia. The drought factors were determined based on expert knowledge analysis. Risk assessment method was developed using weighting which is determined based on significant factors of drought, i.e. rainfall pattern, irrigation status, ground water capacity, soil drainage, and land cover. Satellite data were used to analyze the characteristics of temporal variations of normalized difference vegetation index (NDVI) against drought factors. Weighting scores were determined by analyzing NDVI character using changes in NDVI and normal line diagram of each factor. The accuracy of drought risk map was evaluated by comparing drought risk level and NDVI value. The results indicated that expert knowledge analysis of the drought factors showed significant influence on NDVI value. Drought risk and drought status showed a high positive correlation with R2 = 0.85 for NOAA AVHRR, meaning that there is a significant correlation between the two (r = 0.92). The results of this study can be used to determine spatially location of drought-prone areas based on bio-physical factor causes. Therefore, it can be make recom-mendation for prevention of agricultural drought in the future.]]>
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