Mechanism of the Effect of Urban Form and Land Use on Transportation and Air Pollution in Tehran

Document Type : Research Article


1 Ph.D. Student in Transportation Planning, Department of Civil Engineering, Architecture and Art, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2 Professor, Transportation Planning and Engineering, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.

3 Assistant Professor,Transportation Engineering, Department of Civil Engineering, Architecture and Art, Science and Research Branch, Islamic Azad University, Tehran, Iran.

4 Assistant Professor, Industrial Engineering, Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.


Problem statement: Air pollution is one of the major challenges of urban management in Tehran. Nowadays, the problem of air pollution and traffic congestion in the metropolis of Tehran, like most major cities in the world, is quite concerning. Land use and transportation are two main sectors that have a maximum contribution to environmental pollution.
Research objective: The impetus of this article is to investigate the urban land use efficiency, the distribution of land use, and their impact on transportation and pollutants. For this purpose, the following question was raised: What has been the impact of urban land-use efficiency and distribution of land use in Tehran on transportation and air pollution over the last two decades?
Research method: The present paper is a real-life case study for which data was collected through documentary-library, municipal data, and satellite images. In this study, Landsat satellite images, ENVI 5.3, ArcGIS 10.8, Google Earth Pro, and SPSS 24 were used.
Conclusion: The results of this study indicate the expansion of Tehran, the loss of vegetation,and their transformation into built lands. Over the past two decades, the growth of the built-up area in Tehranhas exceeded the population growth which indicates the inefficiency of the land during this period. In other words, the expansion of the city has been more towards the suburbs with low population density. The study of the correlation between land use types during the period 2004-2016 indicates the scattered growth of Tehran. In such situations, residents use more private cars, which increases traffic congestion, fuel consumption, and air pollution.


Acheampong, R. A. & Silva, E. A. (2015). Land use–transport interaction modeling: A review of the literature and future research directions. Journal of Transport and Land use, 8(3), 11-38.
Alkaradaghi, K., Ali, S. S., Al-Ansari, N. & Laue, J. (2018). Evaluation of land use & land cover change using multi-temporal Landsat imagery: a case study Sulaimaniyah Governorate, Iraq. Journal of Geographic Information System, 10(3), 247-260.
Bakr, N. & Afifi, A. A. (2019). Quantifying land use/land cover changeand its potential impact on rice production in the Northern Nile Delta, Egypt. Remote Sensing Applications: Society and Environment, 13, 348-360.
Bertolini, L. (2017). Planning the mobile metropolis: Transport for people, places and the planet: Macmillan International Higher Education. p. 133.
Birhane, E., Ashfare, H., Fenta, A. A., Hishe, H., Gebremedhin, M. A. & Solomon, N. (2019). Land use land cover changes along topographic gradients in Hugumburda national forest priority area, Northern Ethiopia. Remote Sensing Applications: Society and Environment, 13, 61-68.
Cervero, R. & Sullivan, C. (2011). Green TODs: marrying transit-oriented development and green urbanism. International journal of sustainable development & world-ecology, 18(3), 210-218.
Dhakal, S. (2010). GHG emissions from urbanization and opportunities for urban carbon mitigation. Current Opinion in Environmental Sustainability, 2(4), 277-283.
Gong, J., Hu, Z., Chen, W., Liu, Y. & Wang, J. (2018). Urban expansion dynamics and modes in metropolitan Guangzhou, China. Land Use Policy, 72, 100-109.
Hickman, R., Ashiru, O. & Banister, D. (2010). Transport and climate change: Simulating the options for carbon reduction in London. Transport Policy, 17(2), 110-125.
Huang, R., Taubenböck, H., Mou, L. & Zhu, X. X. (2018). Classification of settlement types from Tweets using LDA and LSTM. Paper presented at the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium.
Karimi Moshaver, M., Mansouri, S.-A. & Adibi, A. A. (2010). Relationship between the Urban Landscape and Position of Tall Building in The City. Bagh-e Nazar, 7(13), 89-99.
Kheyroddin, R., Haghbayan, R., & Shokouhi Bidhendi, M. S. (2020). Verification of Failure Components of the 17th Shahrivar Pedestrian Zone Project in Tehran. Bagh-e Nazar, 16(81), 53-62.
Knox, P. L. (2008). Metroburbia, USA: Rutgers University Press. p. 42.
Koroso, N. H., Zevenbergen, J. A. & Lengoiboni, M. (2020). Urban land use efficiency in Ethiopia: An assessment of urban land use sustainability in Addis Ababa. Land Use Policy, 99, 117-105.
Litman, T. (2016). Transportation cost and benefit analysis, techniques, estimates,and implications, viewed 1 March 2010. Retrieved from p. 24./
McGrath, B. (2018). Intersecting disciplinary frameworks: the architecture and ecology of the city. Ecosystem Health and Sustainability, 4(6), 148-159.
Nery, T., Sadler, R., Solis Aulestia, M., White, B. & Polyakov, M. (2019). Discriminating native and plantation forests in a Landsat time-series for land use policy design. International Journal of Remote Sensing, 40(11), 4059-4082.
Panigrahi, S., Verma, K., & Tripathi, P. (2017). Data mining algorithms for land cover change detection: a review. Sādhanā, 42(12), 2081-2097.
Peña, J., Bonet, A., Bellot, J., Sánchez, J. R., Eisenhuth, D., Hallett, S., & Aledo, A. (2007). Driving forces of land-use change in a cultural landscape of Spain. In Modelling land-use change (pp. 97-116): Springer.
Ramaswami, A., Russell, A. G., Culligan, P. J., Sharma, K. R. & Kumar, E. (2016). Meta-principles for developing smart, sustainable, and healthy cities. Science, 352(6288), 940-943.
Rodrigue, J.-P. (2020). The geography of transport systems: Routledge. p. 321.
Schiller, P. L., & Kenworthy, J. R. (2017). An introduction to sustainable transportation: Policy, planning, and implementation. New York: Routledge.
Seto, K. C., Dhakal, S., Bigio, A., Blanco, H., Delgado, G. C., Dewar, D., . . . Lwasa, S. (2014). Human settlements, infrastructure and spatial planning. p. 975.
Shaharum, N. S. N., Shafri, H. Z. M., Gambo, J. & Abidin, F. A. Z. (2018). Mapping of Krau Wildlife Reserve (KWR) protected area using Landsat 8 and supervised classification algorithms. Remote Sensing Applications: Society and Environment, 10, 24-35.
Shoorcheh, M., Varesi, H., Mohammadi, J. & Litman, T. (2016). Urban Growth Structure and Travel Behaviorin Tehran City. Modern Applied Science, 10(8), 1-16.
Soliman, A., Soltani, K., Yin, J., Padmanabhan, A. & Wang, S. (2017). Social sensing of urban land use based on analysis of Twitter users’ mobility patterns. PloS one, 12(7), e0181657.
Tajbakhsh, K. (2020). Urban Change in Iran: Stories of Rooted Histories and Ever-accelerating Developments by Fatemeh Farnaz Arefian and Seyed Hossein Iradj Moeini, eds. In: SAGE Publications Sage CA: Los Angeles, CA.
Tehran Air Quality Control Company. Tehran Air Quality Online System. (2020). Retrieved from
Thanh Noi, P. & Kappas, M. (2018). Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery. Sensors, 18(1), 18-38.
Wentz, E. A., Anderson, S., Fragkias, M., Netzband, M., Mesev, V., Myint, S. W., . . . Seto, K. C. (2014). Supporting global environmental change research: A review of trends and knowledge gaps in urban remote sensing. Remote Sensing, 6(5), 3879-3905.
WorldEconomicForum. (2020). This is the global economic cost of air pollution. Retrieved from
Xian, G. & Homer, C. (2010). Updating the 2001 National Land Cover Database impervious surface products to 2006 using Landsat imagery change detection methods. Remote sensing of environment, 114(8), 1676-1686.
Xiao, P., Zhang, X., Wang, D., Yuan, M., Feng, X. & Kelly, M. (2016). Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 402-414.