Assessing Agricultural Drought Conditions in Bangladesh Using Vegetation Indices Derived From Remote Sensing

Abstract

Drought evaluation is essential for food security and sustainable resource management in the face of changing climatic patterns and agricultural production. This study analyzes Bangladeshi agricultural drought patterns using multiple indices, such as Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI) to detect drought stress and assess their ability to capture drought conditions of different intensities. Secondary data have been used to carry out this research. Spatial Analyst tools in ArcGIS and Pearson correlation analysis in SPSS were used to analyze and represent data. This study shows that "Extreme Drought" declined from 2005 to 2020. VCI drought class shows that "Extreme Drought" declined from 57.05% in 2005 to 83.28% in 2020, and VHI shows that it declined from 75.67% in 2005 to 4.57% in 2020. However, "Moderate drought" shows an increasing trend from 2005 to 2020 in the VHI drought class, which accounted for 6.29% in 2005 to 7.62% in 2020. Results from the study revealed fluctuations in drought severity in the Rabi season over the examined years, reflecting the dynamic nature of climate impacts on vegetation. This research helps stakeholders reduce drought's detrimental effects on crop productivity and rural livelihoods by providing policy-making, resource allocation, and adaptive agricultural strategies.