An Assessment of Drought Stress in Tea Plantation Areas in Bangladesh Using Optical and Thermal Remote Sensing: A Climate Change Perspective

Drought is one of the deleterious climatic events that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought severity in tea plantation areas using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) image data were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), leaf area index (LAI), and yield maps were developed from Sentinel-2 satellite image data. The drought frequency was measured from the classification of droughts employing the SPI. The results of this study demonstrate that the drought frequency for the Sylhet meteorological station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal meteorological station showed frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020, and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The yield prediction results with respect to drought stress in tea plantation areas show that 61%, 60%, and 60% of tea estates in the study area had lower predicted yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. The outcome of this research suggests that satellite remote sensing with the SPI could be a valuable tool for land policy makers, land use planners, and scientists to measure drought stress in tea estates.