Landscape Dynamics and Land Surface Temperature in the Upper Citarum, Indonesia

¹ School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15-2TT, United Kingdom
² Cakrabuana Institute for Geoinformation, Environment and Social Studies, Cirebon Regency, West Java 45188, Indonesia
³ Faculty of Social Sciences Education, Universitas Pendidikan Indonesia, Bandung City, West Java 40154, Indonesia
⁴ Graduate School, Universitas Padjadjaran, Bandung, West Java 40132, Indonesia
⁵ Faculty of Geography, Universitas Gadjah Mada, Sleman Regency, Daerah Istimewa Yogyakarta 55281, Indonesia
⁶ Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, Bangi, Selangor Darul Ehsan 43600, Malaysia
⁷ Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang Regency, West Java 45360, Indonesia
⁸ Faculty of Social Studies, Universitas Negeri Semarang, Semarang City, Central Java 50237, Indonesia

^* Corresponding author: millary04@gmail.com & mxw445@student.bham.ac.uk
^† Corresponding author: m.dede.geo@upi.edu & moh19008@mail.unpad.ac.id

Abstract

The Citarum River Basin is a critical focus of the Indonesian government due to extensive landscape changes that cause environmental degradation. This study analyzes the landscape dynamics and land surface temperature (LST). A cloud computing platform and multivariate analysis were used to understand the phenomenon in the Cirasea Watershed, West Java, Indonesia, known as the Citarum River’s zero point. Landscape data refers to land use and land cover (LULC) resulting from random forests in Google Earth Engine, whereas LST is obtained from the radiative transfer mechanisms formula. Both data were obtained from Landsat series satellite images, which were validated using field surveys. The data were analyzed quantitatively to understand the differences and correlations between variables. This study shows that landscape dynamics are associated with significant changes in LST from 1993 to 2023, reaching 2.34 °C. The LST in forests and water bodies was highest compared to other LULC types. Road (0.42), elevation (0.72), and population (0.58) were also significantly related to LST. The relationship between LULC and LST is an indicator for further and comprehensive investigation in order to better understand the potential accumulative impacts in the future.