Use of remotely sensed data in determining vegetation cover change and its impact on land surface temperature

October 2025 , Pages 269 - 282

Authors

ا.م.د. جيلان رسول فقيه فقيه 1 ; د. شوان أحمد علي عەلی 1

1 قسم الجغرافيا، كلية الآداب، جامعة سوران

DOI logo 10.17656/11769

Keywords

Abstract

Understanding the relationship between vegetation cover and Land Surface Temperature (LST) is fundamental for assessing environmental changes and developing sustainable land-use plans. This study aims to monitor changes in vegetation cover using remote sensing data over a specified period and, through statistical analysis, evaluate the impact of vegetation cover on LST. For this purpose, the Normalized Difference Vegetation Index (NDVI) was used as a measure of vegetation density, and its relationship with LST was analyzed based on 39 data points. The absolute value of the correlation coefficient (-0.8409) is negative and very close to -1, indicating a very strong linear relationship between the two variables. According to standard measures, any correlation above 0.7 is considered "strong" or "very strong." Furthermore, linear regression analysis revealed a negative (inverse) and statistically significant relationship between the two variables. The coefficient of determination (R²) was 0.707, meaning that 70.7% of the variations in LST can be explained by changes in NDVI. Specifically, the influence coefficient of NDVI was -0.01197 (P < 0.001), clearly demonstrating that an increase in vegetation density has a significant effect in lowering land surface temperature, and vice versa. This process confirms the crucial role of vegetation in regulating environmental temperature, particularly through the process of evapotranspiration.

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  • First online20 October 2025
  • Published at20 October 2025

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