Analysis of The Effect of Land Use Change Using Random Forest Algorithm on Surface Temperature and Its Relationship With Urban Heat Island Phenomenon

Alpina Damayanti; Budhi Agung Prasetyo; Mika Alvionita Sitinjak

doi:10.25299/jgeet.2026.11.1.22002

Authors

Alpina Damayanti Data Science. Dept., Faculty of Science, Sumatera Institute of Technology, Lampung, Indonesia
Budhi Agung Prasetyo Marine Science, Faculty of Science, Sumatera Institute of Technology, Lampung, Indonesia
Mika Alvionita Sitinjak Data Science. Dept., Faculty of Science, Sumatera Institute of Technology, Lampung, Indonesia

DOI:

https://doi.org/10.25299/jgeet.2026.11.1.22002

Keywords:

Land Use, Random Forest, Surface Temperature, Urban Heat Island

Abstract

Bandar Lampung City is one of the cities experiencing rapid population growth. Its strategic location for development and infrastructure has made it a prime target for urbanisation. This urbanisation process has increased built-up land areas and surface temperature, triggering the emergence of the urban heat island (UHI) phenomenon. This study aims to analyse land use changes and surface temperature to determine the spatial distribution of the urban heat island phenomenon in Bandar Lampung City using Landsat 8 remote sensing data. The analysis was carried out through several extraction stages, one involved examining land use changes using the random forest algorithm as an ensemble learning method to address classification problems. The classification results showed an accuracy level of 85%, with the most significant changes occurring in built-up and vegetated areas. The shift in land function from natural or vegetative conditions to built-up areas such as residential zones, commercial areas, and urban infrastructure is driven by population growth and increased economic activity. This transformation has resulted in reduced green spaces and agricultural land, increased surface temperature, decreased groundwater absorption capacity, and intensified the urban heat island phenomenon, affecting ecosystem balance and urban environmental comfort. Based on data processing results, the average surface temperature distribution in 2013 and 2023 was 22.62°C and 26.65°C, respectively, with the UHI distribution increasing by 762.95 hectares.

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