Modeling and Mapping of Urban Sprawl Pattern in Cairo Using Multi-Temporal Landsat Images, and Shannon’s Entropy


Cairo city, being the Egypt’s industrial and cultural center, has a problem of rapid urban sprawl. The city has an extremely high population density which is continuously increasing through informal settlements that grow by sprawling due to migration from the Nile Delta villages and the high population growth rates. The present study attempts to understand, detect and quantify the spatial pattern of Cairo’s urban sprawl using Shannon’s entropy and multi-temporal Landsat TM and ETM images acquired for the period from 1984 to 2013. Supervised classification was applied to extract the built-up areas and to measure the changes in the urban land-use class among the city wards. Shannon’s entropy was applied to model the city’s urban sprawl, trend and spatial change. The entropy values for the city’s electoral wards were modeled and used in an interpolation function to create an entropy surface (index) for each acquired temporal image. Such index indicates the spatial pattern of the urban sprawl and provides a visual comparison of the entropy phenomenon in such wards. Results indicate that Shannon’s entropy index increased from (1.4615) in year 1984 to (2.1023) in year 2013, indicating more dispersed urban growth, a sign of urban sprawl. The maximum entropy values are found in the eastern wards namely El Nozha, Awal Nasr District, Thany Nasr-District, El Salam, El Marg and El Bassatein. A regression analysis was carried for the population growth rate and the built-up areas. Findings help in understanding the sprawl patterns and dynamics among Cairo’s electoral wards and provide a visual comparison. The applied methodology provides explanations and facilitates tracing and measuring the urban sprawl which is needed by decision makers and city planners of mega cities.

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Effat, H. and El Shobaky, M. (2015) Modeling and Mapping of Urban Sprawl Pattern in Cairo Using Multi-Temporal Landsat Images, and Shannon’s Entropy. Advances in Remote Sensing, 4, 303-318. doi: 10.4236/ars.2015.44025.

Conflicts of Interest

The authors declare no conflicts of interest.


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