Pemantauan intensitas lahan terbangun dan dampaknya terhadap albedo dan suhu permukaan lahan di Jakarta
DOI:
https://doi.org/10.24843/JAL.2025.v11.i02.p10Keywords:
albedo, land surface temperature, modified built-up index, remote sensing, urban climateAbstract
Urban expansion significantly alters surface characteristics, leading to changes in albedo and land surface temperature (LST) that contribute to the urban heat island phenomenon. This study aims to monitor the intensity of built-up land in Jakarta using the Modified Built-up Index (MBUI) and to analyze its relationship with surface albedo and LST over a ten-year period (2014–2024). Landsat-8 data were processed in Google Earth Engine to retrieve MBUI, albedo, and LST. The results reveal that MBUI and LST are negatively correlated, as expected, while MBUI–albedo and LST–albedo exhibit positive correlations, which contradict many previous studies. These findings suggest that built-up materials in Jakarta generally have higher albedo compared to vegetation and water bodies, a condition that may differ from other urban contexts. This highlights the unique role of material composition and urban morphology in shaping the city’s thermal environment. Overall, the study demonstrates the effectiveness of MBUI for monitoring urban built-up intensity and highlights the importance of integrating material properties, vegetation, and urban form to better understand and mitigate UHI impacts.
References
Andrés-Anaya P, Sánchez-Aparicio M, del Pozo S, Lagüela S. 2021. Correlation of Land Surface Temperature with IR Albedo for the Analysis of Urban Heat Island. Di dalam: The 16th International Workshop on Advanced Infrared Technology & Applications. Basel Switzerland: MDPI. hlm 9.
Baniassadi A, Sailor DJ, Crank PJ, Ban-Weiss GA. 2018. Direct and indirect effects of high-albedo roofs on energy consumption and thermal comfort of residential buildings. Energy Build. 178:71–83. doi:10.1016/j.enbuild.2018.08.048.
Barletta C, Capolupo A, Tarantino E. 2023. Extracting Land Surface Albedo from Landsat 9 Data in GEE Platform to Support Climate Change Analysis. Geomatics and Environmental Engineering. 17(6):35–75. doi:10.7494/geom.2023.17.6.35.
Bonafoni S, Baldinelli G, Rotili A, Verducci P. 2017. Albedo and surface temperature relation in urban areas: Analysis with different sensors. Di dalam: 2017 Joint Urban Remote Sensing Event (JURSE). IEEE. hlm 1–4.
BPS Provinsi DKI Jakarta. 2024. Provinsi DKI Jakarta dalam Angka (DKI Jakarta Province in Figures). Volume ke-54. BPS Provinsi DKI Jakarta, editor. DKI Jakarta: BPS Provinsi DKI Jakarta.
Chen H, Huang JJ, Dash SS, McBean E, Wei Y, Li H. 2022. Assessing the impact of urbanization on urban evapotranspiration and its components using a novel four-source energy balance model. Agric For Meteorol. 316:108853. doi:10.1016/j.agrformet.2022.108853.
Danniswari D, Honjo T, Furuya K. 2020. Land Cover Change Impacts on Land Surface Temperature in Jakarta and Its Satellite Cities. IOP Conf Ser Earth Environ Sci. 501(1). doi:10.1088/1755-1315/501/1/012031.
Danniswari D, Honjo T, Kato A, Furuya K. 2021. Utilizing Open-Source Satellite Data for the Relationship between Building Height and Land Surface Temperature. Journal of Environmental Information Science. 2021:1–10. doi:10.11492/ceispapersen.2021.2_1.
Fauzi R, Arifin HS, Perdinan. 2025. Study of Urban Temperature Profiles on Various Land Covers in The Greater Jakarta Region, Indonesia. Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan. 15(2):243–254. doi:10.29244/jpsl.15.2.243.
Fitri R, Fauzi R, Seanders O, Danniswari D. 2023 Nov 13. Land use changes and residential area expansion in South Tangerang City, Indonesia. Southeast Asia: A Multidisciplinary Journal., siap terbit.
García Mainieri JJ, Sen S, Roesler J, Al-Qadi IL. 2022. Albedo Change Mechanism of Asphalt Concrete Surfaces. Transportation Research Record: Journal of the Transportation Research Board. 2676(7):763–772. doi:10.1177/03611981221082567.
Gawlikowski J, Ebel P, Schmitt M, Zhu XX. 2022. Explaining the Effects of Clouds on Remote Sensing Scene Classification. IEEE J Sel Top Appl Earth Obs Remote Sens. 15:9976–9986. doi:10.1109/JSTARS.2022.3221788.
Glogowska M. 2025. Comparison of indexes for automatic mapping of built-up areas – a case study of Gliwice. Mining Machine. 43:31–43. doi:10.32056/KOMAG2025.4.
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ. 202:18–27. doi:10.1016/j.rse.2017.06.031.
Huang X, Wang Y. 2019. Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China. ISPRS Journal of Photogrammetry and Remote Sensing. 152:119–131. doi:10.1016/j.isprsjprs.2019.04.010.
Krishnaveni KS, Anilkumar PP. 2021. A Fully Automated Approach to Extract Landcover Features from Landsat Imageries. Di dalam: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. IEEE. hlm 6669–6672.
Liu W, Wang Y. 2007. Temporal comparison of land surface albedo for three different landuse cover types in the Beijing area. Di dalam: Gao W, Ustin SL, editor. hlm 66790H.
Lufilah SN, Makalew AD, Sulistyantara B. 2017. Pemanfaatan Citra Landsat 8 untuk Analisis Indeks Vegetasi di DKI Jakarta. Jurnal Lanskap Indonesia. 9(1):73–80. doi:10.29244/jli.v9i1.15173.
M. Imran H, Issa Shammas M, Rahman A, J. Jacobs S, W. M. Ng A, Muthukumaran S. 2021. Causes, Modeling and Mitigation of Urban Heat Island: A Review. Earth Sciences. 10(6):244. doi:10.11648/j.earth.20211006.11.
Nurwanda A, Honjo T. 2018. City expansion and urban heat island in Bogor. IOP Conf Ser Earth Environ Sci. 179(1). doi:10.1088/1755-1315/179/1/012007.
Otsu N. 1979. A Threshold Selection Method from Gray-Level Histograms. IEEE Trans Syst Man Cybern. 9(1):62–66. doi:10.1109/TSMC.1979.4310076.
Pisello AL. 2015. High-albedo roof coatings for reducing building cooling needs. Di dalam: Eco-Efficient Materials for Mitigating Building Cooling Needs. Elsevier. hlm 243–268.
Prasomsup W, Piyatadsananon P, Aunphoklang W, Boonrang A. 2020. Extraction technic for built-up area classification in Landsat 8 imagery. International Journal of Environmental Science and Development. 11(1):15–20. doi:10.18178/ijesd.2020.11.1.1219.
R Core Team. 2020. R: A language and environment for statistical computing. https://www.r-project.org/.
Ramadhan FD, Hariyanto T, Hapsari Handayani H. 2021. Analysis of Urban Built-up Expansion Based on Combination of Spectral Indices in Surabaya City. Geoid. 17(1):21–37.
Saher R, Stephen H, Ahmad S. 2021. Effect of land use change on summertime surface temperature, albedo, and evapotranspiration in Las Vegas Valley. Urban Clim. 39:100966. doi:10.1016/j.uclim.2021.100966.
Salim MZ, Rahman MH, Kafy A Al, Altuwaijri HA, Fattah MA, Choudhari N. 2025. Automated geospatial workflow for spatiotemporal assessment of urban expansion influence on deforestation in Northeast Florida. Kuwait Journal of Science. 52(4):100453. doi:10.1016/j.kjs.2025.100453.
Shaikh S, Paliwal R, Patil A, Panhalkar S, Palanisamy M. 2023. Modification of New Built-Up Index to Precisely Extract and Identify Changes in the Built-Up Area: A Case Study of Punjab State of India. Geodesy and cartography. 49(1):19–24. doi:10.3846/gac.2023.13523.
Sharma A, Phelan P, Neithalath N, Chopra D, Zhu Z. 2024. Assessing Energy Savings: A Comparative Study of Reflective Roof Coatings in Four US Climate Zones. ASME Journal of Engineering for Sustainable Buildings and Cities. 5(4). doi:10.1115/1.4066069.
da Silva BB, Braga AC, Braga CC, Oliveira LMM de, Montenegro SMGL, Barbosa Junior B. 2016. Procedures for calculation of the albedo with OLI-Landsat 8 images: Application to the Brazilian semi-arid. Revista Brasileira de Engenharia Agrícola e Ambiental. 20(1):3–8. doi:10.1590/1807-1929/agriambi.v20n1p3-8.
Trlica A, Hutyra LR, Schaaf CL, Erb A, Wang JA. 2017. Albedo, Land Cover, and Daytime Surface Temperature Variation Across an Urbanized Landscape. Earths Future. 5(11):1084–1101. doi:10.1002/2017EF000569.
Weng Q, Lu D, Schubring J. 2004. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ. 89(4):467–483. doi:10.1016/j.rse.2003.11.005.
Widyanti R, Nasrullah N, Sulistyantara B. 2025. Analisis Pengembangan Ruang Terbuka Hijau dengan Prioritas Tertinggi untuk Mencegah Urban Heat Island pada Lanskap Kota Depok, Jawa Barat. Jurnal Lanskap Indonesia. 17(1):43–49. doi:10.29244/jli.v17i1.55897.
Wolfe DM, Goossen KW. 2015. Initial Study on Controllable Roofing System to Tailor Building Solar Loads for Increased HVAC Efficiency. J Sol Energy Eng. 137(4). doi:10.1115/1.4030402.
Wu H, Huang B, Zheng Z, Ma Z, Zeng Y. 2022. Spatial Heterogeneity and Temporal Variation in Urban Surface Albedo Detected by High-Resolution Satellite Data. Remote Sens (Basel). 14(23):6166. doi:10.3390/rs14236166.
Xu K, Long E, Li J, Xu L. 2019. Field measurement and influence mechanism analysis of the albedo for a typical urban concrete surface. Indoor and Built Environment. 28(6):837–847. doi:10.1177/1420326X18799398.
Yin S, Liu J, Han Z. 2022. Relationship between urban morphology and land surface temperature—A case study of Nanjing City. PLoS One. 17 2 February:1–17. doi:10.1371/journal.pone.0260205.
Zhang Z, He G, Wang M, Long T, Wang G, Zhang X. 2016. Validation of the generalized single-channel algorithm using Landsat 8 imagery and SURFRAD ground measurements. Remote Sensing Letters. 7(8):810–816. doi:10.1080/2150704X.2016.1190475.
Zheng Z, Zhou W, Yan J, Qian Y, Wang J, Li W. 2019. The higher, the cooler? Effects of building height on land surface temperatures in residential areas of Beijing. Physics and Chemistry of the Earth. 110 November 2018:149–156. doi:10.1016/j.pce.2019.01.008.
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Copyright (c) 2025 Dibyanti Danniswari, Rian Adetiya Pratiwi, Olivia Seanders

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