Typology of Urban Sprawl Based on Its Characteristics and Intensity in Mijen Subdistrict, Semarang City, Indonesia

Authors

  • Hilmy Abiyyu Nirwana Faculty of Engineering, Universitas Semarang, Semarang - Indonesia Author

Keywords:

urban sprawl, peri-urban development, land-use change, Land Change Modeler, GIS, Mijen Subdistrict

Abstract

Mijen District has experienced rapid urban expansion driven by population growth and infrastructure development, resulting in the conversion of non-built-up land into built-up areas. While urban sprawl has been widely studied, research integrating sprawl typology assessment with future land-use prediction in peri-urban areas remains limited. This study aims to identify the driving factors of urban sprawl, classify its typologies and intensity, and predict land-use changes in 2032. A quantitative approach was employed using descriptive, spatial, and inferential analyses supported by ArcMap and the Land Change Modeler in TerrSet 2020. The results indicate three levels of urban sprawl: low (Jatisari), moderate (Wonoplumbon and Cangkiran), and high (Bubakan and Karangmalang). The main driving factors include infrastructure expansion, population growth, and uncontrolled migration. Land-use prediction for 2032 indicates the continued expansion of built-up areas, particularly in zones with high urban sprawl intensity. This study contributes to urban sprawl research by integrating spatial typology analysis with future land-use modeling and provides a basis for spatial planning policies aimed at controlling urban expansion and promoting sustainable peri-urban development.

References

Angel, S., Parent, J., Civco, D. L., Blei, A. M., & Potere, D. (2011). The dimensions of global urban expansion: Estimates and projections for all countries, 2000-2050. Progress in Planning, 75(2), 53-107. https://doi.org/10.1016/j.progress.2011.04.001.

Badan Pusat Statistik Kota Semarang. (2012). Kota Semarang dalam angka 2012. BPS Kota Semarang.

Badan Pusat Statistik Kota Semarang. (2017). Kota Semarang dalam angka 2017. BPS Kota Semarang.

Badan Pusat Statistik Kota Semarang. (2022). Kota Semarang dalam angka 2022. BPS Kota Semarang.

Bhatta, B. (2010). Analysis of urban growth and sprawl from remote sensing data. Springer. https://doi.org/10.1007/978-3-642-05299-6

Bhatta, B., Saraswati, S., & Bandyopadhyay, D. (2010). Urban sprawl measurement from remote sensing data. Applied Geography, 30(4), 731-740. https://doi.org/10.1016/j.apgeog.2010.02.002.

Clark Labs. (2024). Land Change Modeler. Center for Geospatial Analytics, Clark University. https://www.clarku.edu/geospatial-analytics/terrset-liberagis-features/land-change-modeler/.

Congalton, R. G., & Green, K. (2019). Assessing the accuracy of remotely sensed data: Principles and practices (3rd ed.). CRC Press.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.

Ewing, R., & Hamidi, S. (2015). Measuring urban sprawl and validating sprawl measures. Journal of Planning Education and Research, 35(1), 35-50. https://doi.org/10.1177/0739456X14565247.

Ewing, R., Pendall, R., & Chen, D. (2002). Measuring sprawl and its impact. Smart Growth America.

Frenkel, A., & Ashkenazi, M. (2008). Measuring urban sprawl: How can we deal with it? Environment and Planning B: Planning and Design, 35(1), 56-79. https://doi.org/10.1068/b32155.

Galster, G., Hanson, R., Ratcliffe, M. R., Wolman, H., Coleman, S., & Freihage, J. (2001). Wrestling sprawl to the ground: Defining and measuring an elusive concept. Housing Policy Debate, 12(4), 681-717. https://doi.org/10.1080/10511482.2001.9521426.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Hasse, J. E., & Lathrop, R. G. (2003). A housing-unit-level approach to characterizing residential sprawl. Photogrammetric Engineering & Remote Sensing, 69(9), 1021-1029. https://doi.org/10.14358/PERS.69.9.1021.

Jaeger, J. A. G., Bertiller, R., Schwick, C., & Kienast, F. (2010). Suitability criteria for measures of urban sprawl. Ecological Indicators, 10(2), 397-406. https://doi.org/10.1016/j.ecolind.2009.07.007.

Jensen, J. R. (2015). Introductory digital image processing: A remote sensing perspective (4th ed.). Pearson.

Lambin, E. F., & Geist, H. J. (Eds.). (2006). Land-use and land-cover change: Local processes and global impacts. Springer. https://doi.org/10.1007/3-540-32202-7.

McGee, T. G. (1991). The emergence of desakota regions in Asia: Expanding a hypothesis. In N. Ginsburg, B. Koppel, & T. G. McGee (Eds.), The extended metropolis: Settlement transition in Asia (pp. 3-25). University of Hawai'i Press.

Pemerintah Kota Semarang. (2011). Peraturan Daerah Kota Semarang Nomor 14 Tahun 2011 tentang Rencana Tata Ruang Wilayah Kota Semarang Tahun 2011-2031.

Pontius, R. G., Jr., Huffaker, D., & Denman, K. (2004). Useful techniques of validation for spatially explicit land-change models. Ecological Modelling, 179(4), 445-461. https://doi.org/10.1016/j.ecolmodel.2004.05.010.

Seto, K. C., Gueneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083-16088. https://doi.org/10.1073/pnas.1211658109.

United States Geological Survey. (2022). Landsat 9. https://www.usgs.gov/landsat-missions/landsat-9.

Wu, Q., Li, H., Wang, R., Paulussen, J., He, Y., Wang, M., Wang, B., & Wang, Z. (2006). Monitoring and predicting land use change in Beijing using remote sensing and GIS. Landscape and Urban Planning, 78(4), 322-333. https://doi.org/10.1016/j.landurbplan.2005.10.002.

Yeh, A. G. O., & Li, X. (2001). Measurement and monitoring of urban sprawl in a rapidly growing region using entropy. International Journal of Geographical Information Science, 15(5), 423-437. https://doi.org/10.1080/13658810110046034.

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Published

2026-06-30