PEMODELAN STRUKTUR DAN AKTIVITAS PERKOTAAN MELALUI PENDEKATAN CLOCKBOARD ZONING: STUDI KASUS KAWASAN CEKUNGAN BANDUNG

Aulia Rachma; Linda Wardani; Fadjar Iman Nugroho

doi:10.34147/crj.v12i01.475

Authors

Aulia Rachma Institut Teknologi Bandung https://orcid.org/0009-0001-2749-9783
Linda Wardani Institut Teknologi Bandung
Fadjar Iman Nugroho Institut Teknologi Bandung

DOI:

https://doi.org/10.34147/crj.v12i01.475

Keywords:

urban morphology, NDBI, nighttime lights, clockboard zoning

Abstract

The rapid development of metropolitan areas is often marked by an imbalance between the expansion of built-up areas and the intensity of urban activities, resulting in a partial understanding of urban structure and function when analyzed from a single dimension. This condition is evident in the Cekungan Bandung, which experiences intense urbanization pressure and uneven spatial dynamics. This study analyzes the physical structure and urban activities of the Bandung Basin using an integrated spatial modeling approach. The approach used in this study is quantitative spatial analysis with a descriptive-explanatory design. Physical structure was derived from the Normalized Difference Built-up Index (NDBI) using Sentinel-2 imagery, while urban activity was represented by Nighttime Lights (NTL) data from VIIRS Black Marble. Both indicators were standardized and analyzed using clockboard zoning. The results indicate that the maximum NDBI value reaches 0.552 and is concentrated in the metropolitan core, while the basin-scale average NDBI remains negative, reflecting the dominance of non-built-up areas. The highest NTL intensity was observed in Bandung City, with an average of 29.56 nW/cm²·sr and a density of 117.67/km², followed by a sharp decline toward peripheral areas. Bivariate NDBI–NTL classification across 45 clockboard zones is dominated by Transition and Dominant Developing Sectors, while the Core Sector accounts for only 26.67% of zones, indicating a polycentric, asymmetric, corridor-based metropolitan growth pattern.

Downloads

Download data is not yet available.

References

Adrian, A., Widiatmaka, W., Munibah, K., & Firmansyah, I. (2023). Pola Spasial Perubahan Tutupan Lahan/Penggunaan Lahan Menggunakan Google Earth Engine di Kabupaten Majalengka. Jurnal Pembangunan Wilayah Dan Kota, 19(4), 447–463. https://doi.org/10.14710/pwk.v19i4.46254

Afrianto, F., Hariyanto, A. D., & Tucunan, K. P. (2025). Nighttime Lights as Indicators of Energy Efficiency Across Urban Morphologies in Malang City. Journal of Regional and City Planning, 36(1), 68–91. https://doi.org/10.5614/jpwk.2025.36.1.5

Afrianto, F., & Rendra. (2023). Morfologi Kota Malang : Sebuah Tinjauan dari Nighttime Light Satellite Imagery. 3(2).

Andrade, C. (2021). Z Scores, Standard Scores, and Composite Test Scores Explained. Indian Journal of Psychological Medicine, 43(6), 555–557. https://doi.org/10.1177/02537176211046525

Batty, M. (2013). A proposal for a new way to understand cities and their design not as artifacts but as systems composed of flows and networks. The MIT Press.

BPS. (2025). Jawa Barat Dalam Angka Tahun 2025.

Fuadina, L. N., Rustiadi, E., & Pravitasari, A. E. (2021). Analisis Faktor-Faktor yang Mempengaruhi Urban Sprawl di Kawasan Cekungan Bandung. TATALOKA, 23(1), 105–114. https://doi.org/10.14710/tataloka.23.1.105-114

Gibson, J., Olivia, S., Boe-Gibson, G., & Li, C. (2021). Which night lights data should we use in economics, and where? Journal of Development Economics, 149, 102602. https://doi.org/10.1016/j.jdeveco.2020.102602

Lefebvre, A., Sannier, C., & Corpetti, T. (2016). Monitoring Urban Areas with Sentinel-2A Data: Application to the Update of the Copernicus High Resolution Layer Imperviousness Degree. Remote Sensing, 8(7), 606. https://doi.org/10.3390/rs8070606

Lefebvre, H. (1992). The Production Space. Wiley.

Levin, N., Kyba, C. C. M., Zhang, Q., Sánchez de Miguel, A., Román, M. O., Li, X., Portnov, B. A., Molthan, A. L., Jechow, A., Miller, S. D., Wang, Z., Shrestha, R. M., & Elvidge, C. D. (2020). Remote sensing of night lights: A review and an outlook for the future. Remote Sensing of Environment, 237, 111443. https://doi.org/10.1016/j.rse.2019.111443

Lovelace, R., Tennekes, M., & Carlino, D. (2021). ClockBoard: a zoning system for urban analysis. https://doi.org/10.31219/osf.io/vncgw

Mukhoriyah, M., Arifin, S., Dewi, E. K., & Silvia, S. (2021). Analysis of Development Patterns of Built Land and Spatial Structure in Bandung City Using Landsat 8 Image Data. Jurnal Ilmu Lingkungan, 19(1), 36–42. https://doi.org/10.14710/jil.19.1.36-42

Murtadho, A., Pravitasari, A. E., Munibah, K., Saizen, I., & Rustiadi, E. (2022). Controlling the Urban Physical Development in Karawang and Purwakarta Regencies using Quantitative Zoning Approach. Indonesian Journal of Geography, 54(2). https://doi.org/10.22146/ijg.70358

Njambi, R. (2022). An Introduction to Zonal Statistics. Tech. https://up42.com/blog/an-introduction-to-zonal-statistics

Prasetiyo, P., Listyawati, R. N., Alfiah, R., Wahyuningtyas, L., & Rambe, S. S. U. (2025). Urban Morphology and Nighttime Lights: A Spatial Modelling Study in Pasuruan Regency (pp. 14–23). https://doi.org/10.2991/978-94-6463-920-9_3

Putro, D. H., Pramana, S., & Hendrawan, D. (2025). Socioeconomic impact of COVID-19 restrictions in Bali: A nighttime light analysis. Jurnal Ekonomi Indonesia, 14(1), 93–110. https://doi.org/10.52813/jei.v14i1.220

Sakti, A. D., Deliar, A., Hafidzah, D. R., Chintia, A. V., Anggraini, T. S., Ihsan, K. T. N., Virtriana, R., Suwardhi, D., Harto, A. B., Nurmaulia, S. L., Aritenang, A. F., Riqqi, A., Hernandi, A., Soeksmantono, B., & Wikantika, K. (2024). Machine learning based urban sprawl assessment using integrated multi-hazard and environmental-economic impact. Scientific Reports, 14(1), 13385. https://doi.org/10.1038/s41598-024-62001-6

Solihin, I. P. S., & Kurniyanto, R. (2021). Pemanfaatan Citra Landsat 8 Untuk Estimasi Luas Lahan Terbangun dan Tidak Terbangun pada Kota Bandung. Jurnal Indonesia Sosial Teknologi, 2(5), 816–827. https://doi.org/10.36418/jist.v2i5.150

Somantri, L. (2022). Pemetaan mobilitas penduduk di kawasan pinggiran Kota Bandung. Majalah Geografi Indonesia, 36(2), 95. https://doi.org/10.22146/mgi.70636

Sunarta, I. N., & Saifulloh, M. (2022). COASTAL TOURISM: IMPACT FOR BUILT-UP AREA GROWTH AND CORRELATION TO VEGETATION AND WATER INDICES DERIVED FROM SENTINEL-2 REMOTE SENSING IMAGERY. GeoJournal of Tourism and Geosites, 41(2), 509–516. https://doi.org/10.30892/gtg.41223-857

Ulimaz, M., Dewancker, B. J., & Harfadli, M. M. (2025). City branding through spatial popularity: a data-driven perspective from Balikpapan City as a satellite city of Nusantara Capital City of Indonesia. City and Built Environment, 3(1), 19. https://doi.org/10.1007/s44213-025-00058-3

Wang, J., Georganos, S., Kuffer, M., Abascal, A., & Vanhuysse, S. (2022). On the knowledge gain of urban morphology from space. Computers, Environment and Urban Systems, 95, 101831. https://doi.org/10.1016/j.compenvurbsys.2022.101831

Whitehand, J. W. R. (2007). Conzenian urban morphology and urban landscapes. 6 Th International Space Syntax Symposium, ii-1-ii–9. http://www.spacesyntaxistanbul.itu.edu.tr/papers/invitedpapers/Jeremy_whitehand.pdf

Wijaya, R. P., Susilo, B., & Widayani, P. (2020). POLA PERKEMBANGAN MORFOLOGI FISIK KOTA DI CEKUNGAN BANDUNG PERIODE 2009 – 2018. Jurnal Teknosains, 10(1), 19. https://doi.org/10.22146/teknosains.45051

Wu, J., Tu, Y., Chen, Z., & Yu, B. (2022). Analyzing the Spatially Heterogeneous Relationships between Nighttime Light Intensity and Human Activities across Chongqing, China. Remote Sensing, 14(22). https://doi.org/10.3390/rs14225695

Yu, B., Tang, M., Wu, Q., Yang, C., Deng, S., Shi, K., Peng, C., Wu, J., & Chen, Z. (2018). Urban Built-Up Area Extraction From Log- Transformed NPP-VIIRS Nighttime Light Composite Data. IEEE Geoscience and Remote Sensing Letters, 15(8), 1279–1283. https://doi.org/10.1109/LGRS.2018.2830797

Zhao, M., Zhou, Y., Li, X., Zhou, C., Cheng, W., Li, M., & Huang, K. (2020). Building a Series of Consistent Night-Time Light Data (1992–2018) in Southeast Asia by Integrating DMSP-OLS and NPP-VIIRS. IEEE Transactions on Geoscience and Remote Sensing, 58(3), 1843–1856. https://doi.org/10.1109/TGRS.2019.2949797