Investigating land cover changes and their impact on land surface temperature in Tay Ninh province, Vietnam

Abstract

Land surface temperature (LST) serves as a crucial indicator for evaluating the effects of different environmental factors on the ecosystem, including alterations in land use, climate variations, and emissions of greenhouse gases. This comprehensive study used remote sensing data to analyze changes and effects of land use/land cover (LULC) on LST in Tay Ninh province, Vietnam, from 1988–2023. Landsat satellite images in 1988, 2004, and 2023 were preprocessed and supervised classification on ArcGIS 10.8 software. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and LST in the study area were determined using the Landsat image data. The classification results showed a decrease in the area of agricultural land, barren land, and forest classes by 8.30%, 8.82%, and 15.93%, respectively, from 1988 to 2023. Conversely, the area of built-up and waterbodies classes indicated an increase of 33.00% and 0.06%, respectively, during the same period. In terms of LST, the study area exhibited temperature ranges of approximately 19.75 °C—35.28 °C, 26.26 °C—46.33 °C, and 21.05 °C—40.60 °C in 1988, 2004, and 2023, respectively. Contribution Index (CI) and multiple regression analysis evaluated the relationship between land cover, LST, NDVI, and NDBI. The regression analysis preliminary showed a negative correlation between NDVI and LST, while a positive correlation was observed between NDBI and LST. The CI of built-up areas has increased from 0.01 in 1988 to 0.77 in 2023, which shows that this coating has contributed to rising temperatures in the study area. Meanwhile, the forest and water body classes have consistently negative CI throughout the period 1988–2023, which has contributed to the decrease in temperature. This comprehensive study provides policymakers with valuable information regarding LULC and LST, instilling confidence in developing effective policies for land resource management.