Analysis Of the Relationship Between Vegetation and Surface Temperature in Pishdar District, During the Years (1994-2024) Using Remote Sensing

Abstract

The analysis of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) is very important for understanding the relationship between vegetation and land surface temperature in Pshdar District. Changes in vegetation cover can be a factor for temperature rise due to the replacement of barren or green lands with urban areas. The objective of this research is to understand the change in vegetation cover and land surface temperature using remote sensing, and to investigate the relationship between LST changes and vegetation cover changes. In this study, Sentinel-2 satellite images were used for seasonal vegetation comparison, and Landsat-5 satellite images for the years (1994-2004) and Landsat-8 satellite images for the years (2014-2024), including OLI and TIRS sensors, were used for calculating Land Surface Temperature (LST) and vegetation cover mapping in the study area through the use of ENVI 5.3, ArcGIS 10.4, Google Earth Engine, and Python 3.9.15 programming software. We classified our study area into four categories: bare land areas, low vegetation areas, medium vegetation areas, and dense vegetation areas. The results show that a moderate inverse relationship with a value of R = -0.590 was found between NDVI and LST, where increased NDVI corresponds to decreased temperature in vegetation areas. This study utilises satellite data to understand the relationship between vegetation and surface temperature in Pishdar district, which is useful for environmental planning and climate change mitigation.