Spatio-temporal assessment of urban growth using multi-stage satellite imageries in Faisalabad, Pakistan

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Arslan Saleem
Shakeel Mahmood


Today, urban growth is a multidimensional spatial and temporal process. The analysis of urban growth using spatial and attribute data is regarded as one of the basic requirements of urban geographical studies, future planning as well as the establishment of political policies for urban development. The current study is an effort to spatially and temporally assess the urban growth in district Faisalabad from 1991 to 2019. Landsat images, population and registered industries data were utilized carryout spatial analysis. Supervised image classification and linear regression model has been applied to visualize the results. The result inferred from the classified images revealed that the in 1991 the total built-up area of Faisalabad was 1219 km2 (20.81 percent) while year 2010 classified Landsat image depicts that the total built-up area was 3358 km2 (57.34 percent) of the district. The total areal change for 28 years research span was 36 per cent in built up land, contrary to this non built-up /open area decreased to 35 percent during the same period. The results of current study can facilitate district government and Faisalabad Development Authority (FDA) in decision making regarding haphazard growth of urban areas.

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Saleem, A. ., & Mahmood, S. (2023). Spatio-temporal assessment of urban growth using multi-stage satellite imageries in Faisalabad, Pakistan. Advanced Remote Sensing, 3(1), 10–18. Retrieved from


Gull, A., & Mahmood, S. (2022). Spatio-Temporal Analysis and Trend Prediction of Land Cover Changes using Markov Chain Model in Islamabad, Pakistan. Advanced GIS, 2(2), 52-62

Dadras, M., Shafri, H. Z., Ahmad, N., Pradhan, B., & Safarpour, S. (2015). Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 35-52.

Seto, K. C., Fragkias, M., Güneralp, B., & Reilly, M. K. (2011). A meta-analysis of global urban land expansion. PloS one, 6(8), e23777.

Abbas, I. I., Muazu, K. M., & Ukoje, J. A. (2010). Mapping land use-land cover and change detection in Kafur local government, Katsina, Nigeria (1995-2008) using remote sensing and GIS. Research journal of environmental and Earth Sciences, 2(1), 6-12.

Harish, B., Manjulavani, K., Shantosh, M., & Supriya, V. M. (2017, September). Change detection of land use and land cover using remote sensing techniques. In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI) (pp. 2806-2810). IEEE.

Shafiq, M., & Mahmood, S. (2022). Spatial Assessment of Forest Cover Change in Azad Kashmir, Pakistan. Advanced GIS, 2(2), 63-70

Bayo, B., Habib, W., & Mahmood, S. (2022). Spatio-temporal assessment of mangrove cover in the Gambia using combined mangrove recognition index. Advanced Remote Sensing, 2(2), 74-84.

Metzger, M. J., Rounsevell, M. D., Acosta-Michlik, L., Leemans, R., & Schröter, D. (2006). The vulnerability of ecosystem services to land use change. Agriculture, ecosystems & environment, 114(1), 69-85.

Araya, Y. H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2(6), 1549-1563.

Zhang, J., Fu, M., Tao, J., Huang, Y., Hassani, F. P., & Bai, Z. (2010). Response of ecological storage and conservation to land use transformation: A case study of a mining town in China. Ecological Modelling, 221(10), 1427-1439.

Basse, R. M., Omrani, H., Charif, O., Gerber, P., & Bódis, K. (2014). Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale. Applied Geography, 53, 160-171.

Kavzoglu, T., & Reis, S. (2008). Performance analysis of maximum likelihood and artificial neural network classifiers for training sets with mixed pixels. GIScience & Remote Sensing, 45(3), 330-342.

Ustuner, M., Sanli, F. B., & Dixon, B. (2015). Application of support vector machines for landuse classification using high-resolution rapideye images: A sensitivity analysis. European Journal of Remote Sensing, 48(1), 403-422.

Bhalli, M. N. (2012). Remote sensing and GIS applications for monitoring and assessment of the urban sprawl in Faisalabad-Pakistan. Pakistan Journal of Science, 64(3), 203-208

Rasool, A. (2019). Economy of Faisalabad- Origins, transformation and prospects. Faisalabad Chamber of Commerce and Industry.

Cheema, M. A., Farooq, M., Ahmad, R., & Munir, H. (2006). Climatic trends in Faisalabad (Pakistan) over the last 60 years (1945-2004). Journal of Agriculture and Social Sciences, 2(1), 42-45.

Imran, A., & Saleh, S. Crop Development in Central Punjab (Faisalabad) (2016–2017).

Mafi-Gholami, D., Mahmoudi, B., & Zenner, E. K. (2017). An analysis of the relationship between drought events and mangrove changes along the northern coasts of the Pe rsian Gulf and Oman Sea. Estuarine, Coastal and Shelf Science, 199, 141-151.

Pakistan Bureau of Statistics, Punjab (2019). Population Data.

Safder, Q., & Babar, U. (2019). Assessment of Urbanization and Urban Sprawl Analysis through Remote Sensing and GIS: A Case Study of Faisalabad, Punjab Pakistan. International journal of academic research in business and social sciences, 9(4), 16-36

Singh, R. K., Singha, M., Singh, S. K., Debjeet, P. A. L., Tripathi, N., & SİNGH, R. S. (2018). Land use/land cover change detection analysis using remote sensing and GIS of Dhanbad distritct, India. Eurasian Journal of Forest Science, 6(2), 1-12.

Abubakar, B. (2014). Assessment of land use/land cover changes in the Upper Benue Region Adamawa State, Nigeria. International Journal of Environment, Ecology, Family and Urban Studies (IJEEFUS), 4, 1-8.

Adewumi, A. S. (2013). Analysis of land use/land cover pattern along the River Benue channel in Adamawa State, Nigeria. Academic Journal of Interdisciplinary Studies, 2(5), 95-107

Marcus, L., Berghauser Pont, M., & Barthel, S. (2020). Towards a socio-ecological spatial morphology: a joint network approach to urban form and landscape ecology. Urban morphology, 24(1), 21-34.

Xing, Z., & Guo, W. (2022). A New Urban Space Analysis Method Based on Space Syntax and Geographic Information System Using Multisource Data. ISPRS International Journal of Geo-Information, 11(5), 297.

Yamamoto, T., Hanaizumi, H., & Chino, S. (2001). A change detection method for remotely sensed multispectral and multitemporal images using 3-D segmentation. IEEE transactions on geoscience and remote sensing, 39(5), 976-985.

Bruzzone, L., & Prieto, D. F. (2002). An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images. IEEE Transactions on image processing, 11(4), 452-466.

Pacifici F (2007). Change detection algorithms: State of the art. URL: (Accessed on 4 March, 2023).

Pacifici, F., Del Frate, F., Solimini, C., & Emery, W. J. (2007). An innovative neural-net method to detect temporal changes in high-resolution optical satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 45(9), 2940-2952.

Ahmad, F. (2012). A review of remote sensing data change detection: Comparison of Faisalabad and Multan Districts, Punjab Province, Pakistan. Journal of Geography and Regional Planning, 5(9), 236-251.

Jensen, J. R., Cowen, D., Narumalani, S., & Halls, J. (1997). Principles of change detection using digital remote sensor data. Integration of geographic information systems and remote sensing, 37-54.

Singh, A. (1989). Review article digital change detection techniques using remotely-sensed data. International journal of remote sensing, 10(6), 989-1003.