Spatio-Temporal Analysis of Vegetation Index Change on Land Surface Temperature in Yogyakarta Special Region Using MODIS Imagery (2000-2023)

Rheza Tri Nugroho

doi:10.21831/inersia.v20i1.72179

Spatio-Temporal Analysis of Vegetation Index Change on Land Surface Temperature in Yogyakarta Special Region Using MODIS Imagery (2000-2023)

Rheza Tri Nugroho, Department of Civil Engineering and Planning, Faculty of Engineering, Universitas Negeri Yogyakarta, 55281, Indonesia

10.21831/inersia.v20i1.72179

Abstract

Yogyakarta has become a province renowned for its abundance of tourist destinations and learning opportunities for students from all over Indonesia. Temperature and vegetation density are key factors contributing to comfort in both academic pursuits and recreational activities. This study utilizes NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) to determine these crucial parameters. MODIS imagery serves as a vital data source for analyzing NDVI and LST. The aim of this research is to comprehend the environmental dynamics of DIY (Yogyakarta Special Region) by exploring the relationship between NDVI and LST. Through the Pearson correlation method, the relationship between these variables is deeply evaluated. The analysis reveals a significant correlation between changes in NDVI and LST, indicating a complex interaction between vegetation and land surface temperature. However, these significant findings have minimal impact on Yogyakarta City and Sleman, which serve as the focal points of community activities in Yogyakarta. These changes can be attributed to various factors, including changes in land use, urbanization, and climate variability, which show weak correlation values when associated with vegetation. Another finding is that Yogyakarta City exhibits the most distinct response in vegetation density and surface temperature compared to the surrounding four cities. This is attributed to Yogyakarta City being the administrative center and economic hub of DIY. These findings provide a deeper understanding of the environment's response to these factors in DIY. By employing spatial and temporal analysis, this study offers valuable insights for climate change mitigation efforts and adaptation to the evolving environmental dynamics.

Keywords

Google Earth Engine; LST; NDVI; MODIS

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DOI: https://doi.org/10.21831/inersia.v20i1.72179