Exploring The Correlation Between NDVI, LST, And Soil Moisture in The Context of Climate Change

Abstract

This paper analyzes the relationship between vegetation, surface temperature (LST), and soil dampness and their influence on climate change. This research uses 2022 Landsat 8 data to investigate the complex interactions between the three variables. The research results show that NDVI has a moderate correlation in dry months with LST (r=0.4085) and a frail correlation in wet months (r=0.0288), while NDVI and SMI have a weak positive correlation (R=0.02). This research found that changes in soil moisture and vegetation cover can affect land surface temperatures, affecting climate. Understanding the relationship between vegetation cover, surface temperature, and soil moisture or soil dampness is critical to predicting and mitigating the impacts of climate change.