Analisis Perubahan Tutupan Lahan terhadap Distribusi Suhu Permukaan pada Wilayah Kota Pariaman

Land cover change is a key factor influencing land surface temperature (LST) dynamics, particularly in coastal urban areas such as Pariaman City. This study aims to: (1) analyze land cover changes in Pariaman City in 2016 and 2023; (2) examine the spatial distribution of LST in both periods; and (3) evaluate the impact of land cover change on LST. A quantitative descriptive method was employed, using a supervised classification approach for land cover mapping, the Mono-Window Brightness Temperature model for LST estimation, and Pearson’s correlation and regression analyses to assess their relationship. The results indicate substantial land cover changes, with a forest area reduction of 26.162 km² and an increase in residential and agricultural land by 16.444 km² and 12.373 km², respectively. In 2016, LST distribution was dominated by the moderate class (20–24 °C), whereas in 2023 it exhibited greater variability, with an expansion of both low-temperature classes (<17 °C and 17–20 °C) and high-temperature classes (24–29 °C). Pearson’s correlation yielded r = −0.523, indicating that forest cover loss correlates with LST increase. Regression analysis suggests that each 1 km² increase in forest cover is associated with a 0.028 °C decrease in LST. These findings underscore the critical role of land cover management in mitigating urban warming.

Authors

Institutions

Publication Details

Journal
TSAQOFAH
Published
2025-08-08
DOI
https://doi.org/10.58578/tsaqofah.v5i6.7098
Primary Topic
Geotechnical and construction materials studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analisis Perubahan Tutupan Lahan terhadap Distribusi Suhu Permukaan pada Wilayah Kota Pariaman

Deded Chandra, Mustafa El Faris
TSAQOFAH
Geotechnical and construction materials studies
article

Analisis Perubahan Tutupan Lahan terhadap Distribusi Suhu Permukaan pada Wilayah Kota Pariaman

Deded Chandra, Mustafa El Faris
article en

Abstract

Land cover change is a key factor influencing land surface temperature (LST) dynamics, particularly in coastal urban areas such as Pariaman City. This study aims to: (1) analyze land cover changes in Pariaman City in 2016 and 2023; (2) examine the spatial distribution of LST in both periods; and (3) evaluate the impact of land cover change on LST. A quantitative descriptive method was employed, using a supervised classification approach for land cover mapping, the Mono-Window Brightness Temperature model for LST estimation, and Pearson’s correlation and regression analyses to assess their relationship. The results indicate substantial land cover changes, with a forest area reduction of 26.162 km² and an increase in residential and agricultural land by 16.444 km² and 12.373 km², respectively. In 2016, LST distribution was dominated by the moderate class (20–24 °C), whereas in 2023 it exhibited greater variability, with an expansion of both low-temperature classes (<17 °C and 17–20 °C) and high-temperature classes (24–29 °C). Pearson’s correlation yielded r = −0.523, indicating that forest cover loss correlates with LST increase. Regression analysis suggests that each 1 km² increase in forest cover is associated with a 0.028 °C decrease in LST. These findings underscore the critical role of land cover management in mitigating urban warming.

TSAQOFAHVol. 5(6)
State University of Padang (ID)
Openalex Percentile: Top 79%
Geotechnical and construction materials studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.