Tinjauan Pustaka: Kuantifikasi Zona Kenyamanan Termal di Area Perkotaan Tropis Menggunakan Pendekatan Data Penginderaan Jauh
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Abstract
Eskalasi pengembangan wilayah perkotaan tropis telah memperburuk fenomena Urban Heat Island (UHI). Kondisi ini berdampak negatif pada kesehatan, produktivitas, dan konsumsi energi. Artikel ini merupakan tinjauan pustaka jenis bibliometrik tentang pemanfaatan penginderaan jauh untuk mengukur zona kenyamanan termal. Topik ini telah berkembang dari pengukuran anomali suhu secara fisik menjadi penilaian dengan pendekatan indeks kenyamanan termal. Hadirnya satelit seperti Landsat dan MODIS serta kerangka kerja Local Climate Zone (LCZ) menjadikan pengukuran dan penilaiannya semakin mencerminkan kondisi aktual. Meskipun demikian, tantangan terkait korelasi antara LST dari data satelit dan zona kenyamanan termal masih memerlukan penelitian lebih lanjut. Selain itu, ada keraguan tentang keakuratan indeks yang dikembangkan di iklim subtropis untuk diterapkan di wilayah tropis. Validasi model dengan pengukuran di lapangan juga masih perlu dikembangkan, terutama di wilayah yang kekurangan data. Untuk menjembatani kesenjangan tersebut, penelitian masa depan perlu mengintegrasikan faktor non-fisik seperti psikologi dan budaya serta memanfaatkan fusi data dan teknologi seperti machine learning, digital twins, dan artificial realities untuk mendukung perencanaan kota yang adaptif dan layak huni.
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References
J. A. Voogt and T. R. Oke, “Thermal remote sensing of urban climates,” Remote Sens. Environ., vol. 86, no. 3, pp. 370–384, 2003, doi: 10.1016/S0034-4257(03)00079-8.
M. A. Lombardo, “Ilha de Calor nas Metrópoles: O exemplo de São Paulo,” São Paulo, 1985, p. 244.
R. L. Costa, G. M. M. Baptista, and F. D. S. Silva, “Use of remote sensing in the identification of Urban Heat Islands and in the evaluation of Human Thermal Comfort,” J. Hyperspectral Remote Sens. v, vol. 7, no. 7, pp. 408–422, 2017, [Online]. Available: www.periodicos.ufpe.br/revistas/jhrs
V. M. Jayasooriya, A. P. Sirimanne, R. M. Silva, and S. Muthukumaran, “Role of Urban Trees in Enhancing the Thermal Comfort of Rapidly Urbanizing Cities: An Analysis of Tropical Asian Tree Species Based on Physiological Equivalent Temperature (PET),” Arboric. Urban For., vol. 50, no. 5, pp. 326–345, 2024, doi: 10.48044/jauf.2024.014.
Y. M. Su and J. Antoni, “Outdoor Thermal Comfort Study on Urban Areas with Various Densities in Taipei †,” Eng. Proc., vol. 38, no. 1, 2023, doi: 10.3390/engproc2023038077.
T. Wati and R. I. Nasution, “Analysis of Climatological Thermal Comfort in Dki Jakarta Using Heat Index (Humidex),” Widyariset, vol. 4, no. 1, p. 89, 2018, doi: 10.14203/widyariset.4.1.2018.89-102.
N. Faridatussafura and Y. Yulfiah, “Analysis of the Relationship between Thermal Comfort Levels and Green Open Space in Semarang City, Using the Humidex Method,” J. Earth Mar. Technol., vol. 5, no. 1, pp. 91–100, 2025, doi: 10.31284/j.jemt.2024.v5i1.7005.
R. R. Gyimah, “The hot zones are cities: Methodological outcomes and synthesis of surface urban heat island effect in Africa,” Cogent Soc. Sci., vol. 9, no. 1, 2023, doi: 10.1080/23311886.2023.2165651.
A. W. Harzing, Book review - The publish or perish book: Your guide to effective and responsible citation analysis, vol. 13, no. 3. 2012. doi: 10.19173/irrodl.v13i3.1273.
N. Van Eck and L. Waltman, “Bibliometric Mapping of the Computational Intelligence Field ERIM Report Series reference number,” Int. J. Uncertain., vol. 15, no. 5, pp. 1–24, 2008, [Online]. Available: http://hdl.handle.net/1765/11811
N. J. van Eck and L. Waltman, “Software survey: VOSviewer, a computer program for bibliometric mapping,” Scientometrics, vol. 84, no. 2, pp. 523–538, 2010, doi: 10.1007/s11192-009-0146-3.
M. H. Elnabawi and N. Hamza, “Review on Gaps and Challenges in Prediction Outdoor Thermal Comfort Indices: Leveraging Industry 4.0 and ‘Knowledge Translation,’” Buildings, vol. 14, no. 4, 2024, doi: 10.3390/buildings14040879.
N. M. Sari et al., “A Bibliometric Analysis of Urban Environment Quality Studies Based on Satellite Remote Sensing Data,” AIP Conf. Proc., vol. 2941, no. 1, 2023, doi: 10.1063/5.0183687.
Y. Kara and V. Yavuz, “Urban Microclimates in a Warming World: Land Surface Temperature (LST) Trends Across Ten Major Cities on Seven Continents,” Urban Sci., vol. 9, no. 4, 2025, doi: 10.3390/urbansci9040115.
A. A. Farag, S. Badawi, and R. M. Doheim, “Digital Simulation for the Outdoor Thermal Comfort Assessment,” no. January 2021, pp. 33–46, 2019, doi: 10.4018/978-1-5225-9238-9.ch003.
Z. Zhang and G. He, “Generation of Landsat surface temperature product for China, 2000-2010,” Int. J. Remote Sens., vol. 34, no. 20, pp. 7369–7375, 2013, doi: 10.1080/01431161.2013.820368.
T. D. Mushore, J. Odindi, R. Slotow, and O. Mutanga, “Remote sensing-based outdoor thermal comfort assessment in local climate zones in the rural–urban continuum of eThekwini municipality, South Africa,” 2023, mdpi.com. [Online]. Available: https://www.mdpi.com/2072-4292/15/23/5461
X. Chen, Y. Xu, J. Yang, Z. Wu, and H. Zhu, “Remote sensing of urban thermal environments within local climate zones: A case study of two high-density subtropical Chinese cities,” Urban Clim., vol. 31, no. October 2019, p. 100568, 2020, doi: 10.1016/j.uclim.2019.100568.
X. Xu, W. Qiu, W. Li, D. Huang, X. Li, and S. Yang, “Comparing satellite image and GIS data classified local climate zones to assess urban heat island: A case study of Guangzhou,” Front. Environ. Sci., vol. 10, no. November, pp. 1–18, 2022, doi: 10.3389/fenvs.2022.1029445.
N. A. H. Hanapiah, “Urban Heat Island Phenomenon in Penang Island, Malaysia,” J. Adv. Res. Appl. Sci. (ISSN 2208-2352), vol. 6, no. 7, pp. 01–13, 2019, doi: 10.53555/nnas.v6i7.764.
M. T. Abebe and T. L. Megento, “The city of addis ababa from ‘forest city’ to ‘urban heat island’: Assessment of urban green space dynamics,” J. Urban Environ. Eng., vol. 10, no. 2, pp. 254–262, 2016, doi: 10.4090/juee.2016.v10n2.254262.
M. I. Stathopoulou, C. Cartalis, I. Keramitsoglou, and M. Santamouris, “Thermal remote sensing of Thom’s discomfort index (DI): comparison with in-situ measurements,” Remote Sens. Environ. Monit. GIS Appl. Geol. V, vol. 5983, no. October, p. 59830K, 2005, doi: 10.1117/12.627541.
J. C. Fahy, “Beyond land surface temperature: Identifying areas of daytime thermal discomfort in cities by combining remote sensing and field measurements,” Urban Clim., vol. 61, 2025, doi: 10.1016/j.uclim.2025.102460.
Y. Al Horr, M. Arif, A. K. Kaushik, H. Arsalan, A. Mazroei, and M. Q. Rana, “Thermal Comfort in Buildings: Scientometric Analysis and Systematic Review,” J. Archit. Eng., vol. 29, no. 2, 2023, doi: 10.1061/jaeied.aeeng-1490.