Environmental Challenges (Aug 2021)
Assessment and prediction of seasonal land surface temperature change using multi-temporal Landsat images and their impacts on agricultural yields in Rajshahi, Bangladesh
Abstract
Climate change threatens agricultural productivity. Understanding climate change, especially its effects on land surface temperature (LST), is critical for policymakers, agriculturalists, and crop breeders if global food security is to be assured. Rajshahi produces substantial agricultural yields (e.g., crops, vegetables, and fruits) in the country each year. The average LST increase in this region, especially in the winter season, poses a significant threat to winter agricultural productivity. Therefore, the study used Landsat images to evaluate seasonal (summer and winter) LST transitions, distribution over Land Use/Land Cover (LULC) changes (from 2000 to 2020 at 10-year intervals), and predict these two variables (for 2030 and 2040) using Cellular Automata (CA) and Artificial Neural Network (ANN) algorithms. Furthermore, studies of Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs) were conducted to determine the effects of temperature rise on agricultural production, and an analytic hierarchy process (AHP) based suitability analysis was performed to determine the most productive areas. The results showed that agricultural land and water bodies were reduced by 24.53 % and 39.71%, respectively. During the summer season, high temperatures of more than 35°C are expected to hit more than 27% (2030) and 37% (2040) of the total area. The high-temperature zone (≥ 35°C) will likely cover more than 1% and 3% of the area in 2030 and 2040, respectively, for estimated winter LST. The validation of CA model showed outstanding precision, with a kappa value of 0.84. Similarly, validation of the ANN model with Mean Square Error (0.59 and 0.66 for summer) and Correlation coefficient (0.832 and 0.827 for winter) values showed strong prediction accuracy. Furthermore, as an agricultural productive region, only 40% of the total area was defined as a highly suitable zone for agriculture. This study offers useful guidance for urban planners, agricultural officers, and environmental engineers in developing effective policy initiatives to preserve agricultural land for environmental sustainability.
