Author:
Dimyati Muhammad,Aginta Friscila,Damayanti Astrid
Abstract
Abstract
The land surface temperature (LST) is a crucial component of the earth’s energy balance system. The temperature differences between the earth’s surface and the atmosphere are reflected in LST. Conversion of land, including vegetated land, may result in changes to LST. Using the vegetation index approach—NDVI and EVI—this study seeks to ascertain how variations in vegetation density impact LST. Using Landsat 7 ETM+ satellite imagery from 2003 and Landsat 8 OLI-TIRS from 2015 and 2020, this research combines remote sensing technologies and GIS to get vegetation density and LST values, which were then subjected to field verification and spatiotemporal analysis. According to the study’s findings, variations in vegetation density and soil surface temperature have an inverse or opposing relationship. The study’s findings suggest that variations in vegetation density and soil surface temperature have an opposing or inverse connection. In South Badung Regency, places with low vegetation density vary more in proximity to metropolitan areas, resulting in higher soil surface temperatures. These findings suggest that several additional factors, including population density and size, land use, urban planning, rainfall, and season, influence variations in land surface temperature in South Badung Regency.
Reference38 articles.
1. Application of NDVI in vegetation monitoring using GIS and remote sensing in northern Ethiopian highlands;Ahmed;Abyssinia Journal of Science and Technology,2016
2. Assessing the relationship of LST, NDVI, and EVI with land cover changes in the Lagos lagoon environment;Alademomi;Quaestiones Geographicae,2020
3. Normalized difference spectral indices and urban land cover as indicators of land surface temperature (LST);Alexander;International Journal of Applied Earth Observation and Geoinformation,2020
4. Vegetation cover density and land surface temperature interrelationship using satellite data, case study of Wadi Bisha, South KSA;Alshaikh;Advances in Remote Sensing,2015
5. Analisis Sebaran Vegetasi dengan Citra Satelit Sentinel Menggunakan Metode NDVI dan Segmentasi;Andini;Jurnal Geodesi Undip,2018