Climate smart agriculture strategy for drought-prone areas: The role of land surface temperature data

Abstract

Abstract Climate change is a severe environmental problem worldwide, affecting many sectors, particularly agriculture. Monitoring climate fluctuation in agricultural areas is a substantial way to maintain food security, especially in Indonesia. The rise of surface temperature contributes to the drought phenomenon that triggers various agricultural problems, such as crop disease, production loss, land conversion, soil nutrient depletion, and biodiversity loss. With this sense, implementing climate-smart agriculture (CSA) schemes is necessary to secure food production, climate resiliency, and environmental sustainability. Land surface temperature (LST) derivation by using satellite-borne technology is an invaluable solution for monitoring climate dynamics in vast agricultural lands. This study were used temperature bands from the TIRS sensor of Landsat 8 and 9 data to estimate LST in the Middle Citarum watershed. This research aimed to estimate LST series during 2013-2023 dry seasons, which acts as an initial warning system for mitigating drought occurrence in Middle Citarum. This study revealed that the average of LST values during 2013-2023 spanned from 22.54°C to 33.14°C, which somewhat unsuits to optimal rice production. The highest temperature during these periods was 38.98°C, occurred in 2015. This condition was also associated with the 2015 drought event, which was an unparalleled warming worldwide. Based on the LST derivation in the study area, since 2018 to 2023, maximum land surface temperature has steadily been above 30°C. This suggests that drought probability has risen, and the figure should warn of potential failure in crop production during the season. With the development of LST time series, these data sets could contribute to an effective strategy as part of CSA adoption to understand and mitigate drought.