Abstract
The Urban Heat Island (UHI) effect in tropical urban settings arises from interactions among built surfaces, vegetation, water bodies, and urban energy dynamics. This study modeled Land Surface Temperature (LST) in DKI Jakarta using Random Forest and XGBoost optimized with RandomizedSearchCV and 5-fold cross-validation. The analysis used 5,821 grid points at approximately 300 m resolution and five predictors: road density, NDVI, NDBI, NDWI, and distance to green open space. XGBoost slightly outperformed Random Forest, achieving R² = 0.507 and RMSE = 1.830°C compared with R² = 0.497 and RMSE = 1.849°C, although the difference was not statistically significant (Wilcoxon, p = 0.352). The RF-XGBoost ensemble did not improve performance due to very high residual correlation (r = 0.988) and a theoretical ensemble standard deviation reduction of only ~0.3%. SHAP analysis identified NDBI as the dominant predictor (mean|SHAP| = 0.986), with the strongest interaction between NDBI and road density (0.101). Hyperparameter tuning changed model ranking, statistical significance, and the leading SHAP interaction pair.
How to Cite
| Issue | Vol. 4 No. 2 (2026) |
| Section | Articles |
| DOI | 10.58477/cj.v4i2.501 |
| Publication Date | 2026-08-30 |
| Pages | 275-291 |
- Fajary, F. R., Lee, H. S., Kubota, T., Bhanage, V., Pradana, R. P., Nimiya, H., & Putra, I. D. G. A. (2024). Comprehensive spatiotemporal evaluation of urban growth, surface urban heat island, and urban thermal conditions on Java island of Indonesia and implications for urban planning. Heliyon, 10(13), e33708. https://doi.org/10.1016/j.heliyon.2024.e33708
- Li, X., Zhou, Y., Asrar, G., Imhoff, M., & Xuecao, L. (2017). The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States. Science of the Total Environment, 605–606, 426–435. https://doi.org/10.1016/j.scitotenv.2017.06.229
- Masson, V., Lemonsu, A., Hidalgo, J., & Voogt, J. (2021). Urban climates and climate change. [Informasi jurnal/penerbit perlu diverifikasi], 45(1), 411–444.
- McFeeters, S. K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425–1432. https://doi.org/10.1080/01431169608948714
- Muzaky, H., & Jaelani, L. M. (2019). Analisis pengaruh tutupan lahan terhadap distribusi suhu permukaan: Kajian urban heat island di Jakarta, Bandung dan Surabaya [PDF].
- Oke, T. R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455), 1–24. https://doi.org/10.1002/qj.49710845502
- Oke, T. R., Mills, G., Christen, A., & Voogt, J. A. (2017). Urban climates. Cambridge University Press.
- Sarker, T., Fan, P., Messina, J. P., Mujahid, N., Aldrian, E., & Chen, J. (2024). Impact of urban built-up volume on urban environment: A case of Jakarta. Sustainable Cities and Society, 105, 105346. https://doi.org/10.1016/j.scs.2024.105346
- Siswanto, S., Nuryanto, D. E., Ferdiansyah, M. R., Prastiwi, A. D., Dewi, O. C., Gamal, A., & Dimyati, M. (2023). Spatio-temporal characteristics of urban heat island of Jakarta metropolitan. Remote Sensing Applications: Society and Environment, 32, 101062. https://doi.org/10.1016/j.rsase.2023.101062
- Tahooni, A., Kakroodi, A. A., Kiavarz, M., & Mansourian, H. (2025). High-resolution urban LST downscaling via machine learning and SHAP: A case study in a rapidly urbanizing semi-arid region. Sustainable Cities and Society, 134, 106897. https://doi.org/10.1016/j.scs.2025.106897
- Wei, J., Li, Y., Jia, L., Liu, B., & Jiang, Y. (2025). The impact of spatiotemporal effect and relevant factors on the urban thermal environment through the XGBoost-SHAP model. Land, 14(2). https://doi.org/10.3390/land14020394
- Yang, J., Li, H., Xin, J., Yu, W., Ren, J., Yu, H., Xiao, X., Xia, C., Li, J., & Xiao, H. (2026). Investigating the effect of urban form on land surface temperature at block and grid scales based on XGBoost-SHAP. Environmental Modelling & Software. https://doi.org/10.1016/j.envsoft.2025.106738
- Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583–594. https://doi.org/10.1080/01431160304987
- Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., & Sobrino, J. A. (2019). Satellite remote sensing of surface urban heat islands: Progress, challenges, and perspectives. Remote Sensing, 11(1), 48. https://doi.org/10.3390/rs11010048
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.