Potential Advantages and Disadvantages of Case Study as Methodological Approach in Streetscape Research

Main Article Content

Ferdy Sabono
Indah Widiastuti
Iwan Sudradjat


In recent decades, streetscape research has advanced quickly in tandem with societal understanding of the impact of urban environmental quality on aesthetic satisfaction and urban dwellers' well-being. The case study method is one of the methodological approaches that has grown in popularity in streetscape research. However, no researchers have yet conducted a comprehensive investigation into the efficacy of case studies when used in streetscape research. Based on the experiences and findings of other researchers using case studies as their research design, this study explores the potential advantages and drawbacks of using case studies in streetscape research. The study uses the systematic literature review method to collect and analyze past relevant streetscape research findings to identify the potential advantages and disadvantages researchers may face when doing their streetscape research, which comprises several stages, namely case selection, development of a theoretical framework, data gathering, data analysis, discussion, and conclusion. The research findings have shown that the case study approach can result in in-depth studies by creating a well-defined research protocol that aligns with the particular environmental situation under examination. However, adopting technology in streetscape research can pose difficulties and limitations for researchers, such as the challenge of accessing advanced technology and mastering the complexity of analytical tools with intricate requirements.

Article Details

How to Cite
Sabono, F., Widiastuti, I., & Sudradjat, I. (2024). Potential Advantages and Disadvantages of Case Study as Methodological Approach in Streetscape Research. Nakhara : Journal of Environmental Design and Planning, 23(2), Article 411. https://doi.org/10.54028/NJ202423411
Review Articles


Biljecki, F., & Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215, Article 104217. https://doi.org/10.1016/j.landurbplan.2021.104217

Boell, S. K., & Cecez-Kecmanovic, D. (2015). Debates and perspectives on being 'systematic' in literature reviews in is. Journal of Information Technology, 30(2), 161–173. https://doi.org/10.1057/jit.2014.26

Capitanio, A. (2019). Attractive streetscapes make pedestrians walk longer routes: The case of Kunitachi in Tokyo. Journal of Architecture and Urbanism, 43(2), 131–137. https://doi.org/10.3846/jau.2019.10359

Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE Publications.

Edirisinghe, T., & Hewawasam, C. (2020). An investigation of the relationship of streetscape visual enclosure and the pedestrian movement in selected case studies in Colombo. Journal of Engineering and Architecture, 8(1), 11–30. https://jea.thebrpi.org/vol-8-no-1-june-2020-abstract-2-jea

Hartanti, N. B. (2014). Karakter streetscape sebagai pembentuk identitas kota Bogor [Streetscape character as a shaper of the identity of the city of Bogor]. Seminar Nasional Riset Arsitektur dan Perencanaan (SERAP), Manusia Dan Ruang dalam Arsitektur dan Perencanaan, 3, 287–294. https://core.ac.uk/download/pdf/144967178.pdf

Harvey, C., & Aultman-Hall, L. (2016). Measuring urban streetscapes for livability: A review of approaches. Professional Geographer, 68(1), 149–158. https://doi.org/10.1080/00330124.2015.1065546

He, J., Zhang, J., Yao, Y., & Li, X. (2023). Extracting human perceptions from street view images for better assessing urban renewal potential. Cities, 134, Article 104189. https://doi.org/10.1016/j.cities.2023.104189

Jing, J. (2022). Seeing streetscapes as social infrastructure: A paradigmatic case study of Hornsbergs Strand. Stockholm Urban Planning, 7(4), 510–522. https://doi.org/10.17645/up.v7i4.5776

Kosztyán, Z. T., Csizmadia, T., & Katona, A. I. (2021). SIMILAR – Systematic iterative multilayer review method. Journal of Informetrics, 15(1), Article 101111. https://doi.org/10.1016/j.joi.2020.101111

Lee, J., & Park, S. (2023). Current design guidelines for streetscape improvement for visual perception and walkability: A case study of Sejong City, Republic of Korea. Frontiers of Architectural Research, 12(3), 423–443. https://doi.org/10.1016/j.foar.2022.11.002

Lesan, M., & Gjerde, M. (2020). A mixed methods approach to understanding streetscape preferences in a multicultural setting. Methodological Innovations, 13(2), 1–15. https://doi.org/10.1177/2059799120937233

Li, T., Jiang, C., Bian, Z., Wang, M., & Niu, X. (2020). Semantic segmentation of urban street scenes based on Convolutional Neural Networks. Journal of Physics: Conference Series, 1682, Article 012077. https://dx.doi.org/10.1088/1742-6596/1682/1/012077

Li, X., & Ratti, C. (2019). Using google street view for street-level urban form analysis: A case study in Cambridge. Massachusetts the Mathematics of Urban Morphology, 457–470 https://link.springer.com/chapter/10.1007/978-3-030-12381-9_20

Li, X., Beaucamp, B., Tourre, V., Leduc, T., & dan Servieres, M. (2023). Evaluation of urban perception using only image segmentation features. 9th International Conference on Geographical Information Systems Theory, Applications and Management (pp. 200-207). https://doi.org/10.5220/0011969700003473

Liu, Y., Chen, M., Wang, M., Hunag, J., Thomas, F., Rahimi, K., & dan Mamouei, M. (2023). An interpretable machine learning framework for measuring urban perceptions from panoramic street view images. iScience, 26(3), Article 106132. https://doi.org/10.1016/j.isci.2023.106132

Loodin, H., & Thufvesson, O. (2022). Which architectural style makes an attractive streetscape? Aesthetic preferences among city center managers. Journal of Urban Design, 28(1), 25–43. https://doi.org/10.1080/13574809.2022.2072716

Ma, X., Ma, C., Wu, C., Xi, Y., Yang, R., Peng, N., Zhang, C., & Ren, F. (2021). Measuring human perceptions of streetscapes to better inform urban renewal: A perspective of scene semantic parsing. Cities, 110, Article 103086. https://doi.org/10.1016/j.cities.2020.103086

Nagata, S., Nakaya, T., Hanibuchi, T., Amagasa, S., Kikuchi, H., & Inoue, S. (2020). Objective scoring of streetscape walkability related to leisure walking: A statistical modeling approach with semantic segmentation of Google Street View images. Health and Place, 66, Article 102428. https://doi.org/10.1016/j.healthplace.2020.102428

Qiu, W., Li, W., Zhang, Z., Xiaojiang, L., Xun, L., & Huang, X. (2021). Subjective or objective measures of street environment: Which are more effective in explaining housing prices? Landscape and Urban Planning, 221, Article 104358. https://doi.org/10.1016/j.landurbplan.2022.104358

Qiu, W., Li, W., Liu, X., Zhang, Z., Li, X., & Huang, X. (2023). Subjective and objective measures of streetscape perceptions: Relationships with property value in Shanghai. Cities, 132, Article 104037. https://doi.org/10.1016/j.cities.2022.104037

Rzotkiewicza, A., Pearsona, A.L., Doughertya, B.V., Shortridgea, A., & Wilson, N. (2018). Systematic review of the use of Google Street View in health research: Major themes, strengths, weaknesses, and possibilities for future research. Health and Place, 52, 240–246. https://doi.org/10.1016/j.healthplace.2018.07.001

Sehar, U., & Naseem, M.L. (2022). How deep learning is empowering semantic segmentation Traditional and deep learning techniques for semantic segmentation: A comparison. Multimedia Tools and Applications, 81, 30519–30544. https://link.springer.com/article/10.1007/s11042-022-12821-3

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039

Surinta, P. (2023). Measuring streetscape qualities in a car-dependent city: The case of three historical streets in Bangkok. Nakhara: Journal of Environmental Design and Planning. 22(1), Article 305. https://doi.org/10.54028/NJ202322305

Talen, E., Choe, K. W., Akcelik, G. N., Berman, M. G., & Meidenbauer, K. L. (2022). Street design preference: An online survey. Journal of Urban Design, 28(1), 1–24 https://doi.org/10.1080/13574809.2022.2066512

Tang, J., & Long, Y. (2019). Measuring the visual quality of street space and its temporal variation: methodology and its application in the Hutong area of Beijing. Landscape and Urban Planning, 191, Article 103436. https://doi.org/10.1016/j.landurbplan.2018.09.015

Tao, Y., Wang, Y., Wang, X., Tian, G., & Zhang, S. (2022). Measuring the correlation between human activity density and streetscape perceptions: An Analysis Based on Baidu Street View Images in Zhengzhou. China Land, 11(3), Article 400. https://doi.org/10.3390/land11030400

Wang, R., Lu, T., Wan, C., Sun, X., & Jiang, W. (2023). Measuring the effects of streetscape characteristics on perceived safety and aesthetic appreciation of pedestrians. Journal of Urban Planning and Development, 149(3), Article 05023020. https://doi.org/10.1061/jupddm.upeng-4314

Xiao, Y., & Waston, M. (2019). Guidance on conducting a systematic literature review. Journal of Planning Education and Research, 39(1) 93–112. https://doi.org/10.1177/0739456X17723971

Xu, X., Qiu, W., Li, W., Liu, X., Zhang, Z., Li, X., & Luo, D. (2022). Associations between street-view perceptions and housing prices: subjective vs. objective measures using computer vision and machine learning techniques. Remote Sensing, 14(4), Article 891. https://doi.org/10.3390/rs14040891

Ye, Y., Zeng, W., Shen, Q., Zhang, X., & Lu, Y. (2019). The visual quality of streets: A human-centered continuous measurement based on machine learning algorithms and street view images Environment and Planning. Urban Analytics and City Science, 46(8), 1–19. https://doi.org/10.1177/2399808319828734

Yin, R.K. (2018). Case study applications and research (6th ed.) British Empire Publishers, SAGE.