DROUGHT MONITORING FROM 2001–2019 IN NORTHEAST THAILAND USING MODIS NDVI IMAGE TIME SERIES AND Savitzky-Golay APPROACH

Abstract

Abstract. Drought directly threatens food security and livelihoods, thereby increasing socioeconomic risks and remains a challenge for natural resource management, particularly in frequently affected regions. Earth observation (EO) satellites provide extensive spectral and temporal data for long-term drought monitoring. This study monitored droughts in Northeast Thailand from 2001 to 2019 using the MODIS normalised difference vegetation index (NDVI) image time series. The Savitzky-Golay (S-G) method was used to remove noise and fill gaps in the image datasets. Optimal indicators as the vegetation condition index (VCI) and the standard vegetation index (SVI) were used to monitor drought distribution patterns over the previous 19 years. S-G filtering effectively reduced the impact of undetected clouds and water vapour, while VCI had the highest accuracy coefficient of determination (R2) for rainfall data at 0.85. Long-term droughts occurred frequently in 2005, 2004, 2007, and 2001 with the northern and central regions most severely affected. Severe drought primarily impacted agricultural land, forest and miscellaneous areas. Inter-annual drought variability for one and three time steps was clearly demonstrated in May and April to June from 2001 to 2019. Overall, the VCI provided a high level of satisfaction for drought monitoring in this region and clearly displayed the spatial distribution of long-term drought regions. Our findings provide a valuable resource for drought mitigation planning and warning systems.