Spatio-Temporal Analysis of NDVI-Based Drought Conditions Using Precipitation Data in Lamongan Regency, Indonesia

Abstract

Drought is a recurring challenge in agricultural regions that are highly dependent on seasonal Precipitation, including Lamongan Regency, East Java, Indonesia. This study aims to analyze drought conditions based on vegetation dynamics using the Normalized Difference Vegetation Index (NDVI) and its relationship with Precipitation variability. Monthly NDVI data for 2024 were derived from Landsat 8 imagery and analyzed using a spatio-temporal approach in conjunction with observed Precipitation data. Seasonal NDVI patterns were used to identify vegetation stress, while a time-lagged regression analysis was applied to evaluate the influence of Precipitation and antecedent vegetation conditions on current NDVI dynamics. The results indicate a notable decline in NDVI values during the dry season (May–September), reflecting increased vegetation stress in rainfed agricultural areas. Regression analysis confirms that Precipitation plays an important role in shaping vegetation conditions, with evidence of vegetation memory represented by the contribution of lagged NDVI. This study provides practical insights for local-scale drought monitoring and supports agricultural planning and water resource management in regions vulnerable to climate variability. This method offers valuable support for agricultural planning and water resource management in regions that face significant risks from seasonal drought. By utilizing this approach, stakeholders can better prepare for and mitigate the impacts of water scarcity on crops and ecosystems. Looking ahead, future research could enrich drought evaluations by incorporating a wider array of climatic variables and analyzing data with greater temporal resolution, thereby improving the accuracy and reliability of drought assessments.