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 ARS  Vol.4 No.4 , December 2015
Modeling and Mapping of Urban Sprawl Pattern in Cairo Using Multi-Temporal Landsat Images, and Shannon’s Entropy
Abstract: 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.
Cite this paper: 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.
References

[1]   Brueckner, J.K. (2000) Urban Sprawl, Diagnosis and Remedies. International and Regional Science Review, 23, 160-171.
http://dx.doi.org/10.1177/016001700761012710

[2]   Frenkel, A. and Ashkenazi, M. (2007) The Integrated Sprawl Index: Measuring the Urban Landscape in Israel. Annals of Regional Science, 42, 99-121.
http://dx.doi.org/10.1007/s00168-007-0137-3

[3]   Knaap, G., Talen, E., Olshansky, R. and Forrest, C. (2013) Government Policy and Urban Sprawl. Illinois Department of Natural Resources, Office of Realty and Environmental Planning, Chicago.

[4]   Sudhira, H.S., Ramachandra, T.V. and Jagadish, K.S. (2004) Urban Sprawl: Metrics, Dynamics and Modeling Using GIS. International Journal of Applied Earth Observation and Geoinformatics, 5, 29-39.
http://dx.doi.org/10.1016/j.jag.2003.08.002

[5]   Kayhko, N. and Skanes, H. (2005) Change Trajectories and key biotopes Assessing landscape dynamics and sustainability. Landscape and Urban Planning, 75, 300-321.
http://dx.doi.org/10.1016/j.landurbplan.2005.02.011

[6]   Junge, B., Alabi, T., Sonder, K., Marcus, S., Abaidoo, R., Chikoye, D. and Stahr, K. (2009) Use of Remote Sensing and GIS for Improved Natural Resources Management: Case Study from Different Agro Ecological Zones of West Africa. International Journal of Remote Sensing, 31, 6115-6141.

[7]   Verzosa, L. and Gonzalez, R. (2010) Remote Sensing and GIS in Monitoring Urban Sprawl: The Case of Baguio City, Philippines. Paper presented at the 1st Seminar on Asian Water Environments. DRMII_05 in CD-ROM, Manila.

[8]   Bhatta. B., Saraswati, S. and Bandyopadhyay, D. (2010) Urban Sprawl Measurement from Remote Sensing Data. Applied Geography, 30, 731-740.
http://dx.doi.org/10.1016/j.apgeog.2010.02.002

[9]   Pocas, I., Cunha, M. and Pereira, L.S. (2011) Remote Sensing Based Indicators of Changes in a Mountain Rural Landscape of Northeast Portugal. Applied Geography, 31, 871-880.
http://dx.doi.org/10.1016/j.apgeog.2011.01.014

[10]   Batty, M., Xie, Y. and Sun, Z. (1999) The dynamics of urban sprawl. Working Paper Series. Paper 15. Centre for Advanced Spatial Analysis. University College London.
http://www.casa.ac.uk/working_papers/

[11]   Torrens, P.M. and Alberti, M. (2000) Measuring Sprawl. Working Paper No. 27, Centre for Advanced Spatial Analysis, University College London, London.
http://www.casa.ac.uk/working_papers/

[12]   Yeh, A.G.O. and Li, X. (2001) Measurement and Monitoring of Urban Sprawl in a Rapidly Growing Region Using Entropy. Photogrammetric Engineering and Remote Sensing, 67, 83-90.

[13]   Theobald, D.M. (2001) Quantifying Urban and Rural Sprawl Using the Sprawl Index. Proceedings of the Annual Conference of the Association of American Geographers, New York, 2 March 2001.

[14]   Barnes, K.B., Morgan III, J.M., Roberge, M.C. and Lowe, S. (2001) Sprawl Development: Its Patterns, Consequences, and Measurement. Towson University.
http://pages.towson.edu/morgan/files/Sprawl_Development.pdf

[15]   Wei, J., Ma, J., Twibell, R.W. and Underhill, K. (2006) Characterizing Urban Sprawl Using Multi-Stage Remote Sensing Images and Landscape Metrics. Computers, Environment and Urban Systems, 30, 861-879.
http://dx.doi.org/10.1016/j.compenvurbsys.2005.09.002

[16]   Yu, X.J. and Ng, C.N. (2007) Spatial and Temporal Dynamics of Urban Sprawl along Two Urban-Rural Transects: A Case Study of Guangzhou, China. Landscape and Urban Planning, 79, 96-109.
http://dx.doi.org/10.1016/j.landurbplan.2006.03.008

[17]   Schneider, A. and Woodcock, C.E. (2008) Compact, Dispersed, Fragmented, Extensive? A Comparison of Urban Growth in Twenty-Five Global Cities Using Remotely Sensed Data, Pattern Metrics and Census Information. Urban Studies, 45, 659-692.
http://landcoverchange.com/wp-content/uploads/2014/09/schneider__woodcock_2008.pdf
http://dx.doi.org/10.1177/0042098007087340


[18]   Singh, B. (2014) Urban Growth Using Shannon Entropy, a Case Study of Rohtak City. International Journal of Advanced Remote Sensing and GIS International, 3, 544-552.

[19]   Denis, E. (1996) Urban Planning and Growth in Cairo. Middle East Report, 202, 7-12.
http://dx.doi.org/10.2307/3013031

[20]   Denis, E. and Sejourne, M. (2002) ISIS: Information System for Informal Settlements. Ministry of Planning, GTZ, CEDEJ, Cairo.

[21]   Fahmi, W. and Sutton, K. (2008) Greater Cairo’s Housing Crisis: Contested Spaces from Inner City Areas to New Communities. Cities, 25, 277-297.
http://dx.doi.org/10.1016/j.cities.2008.06.001

[22]   Central Agency for Public Mobilization and Statistics (2006) General Census of Population, Housing and Buildings 2006: Final Results. CAPMAS, Cairo.

[23]   Central Agency for Public Mobilization and Statistics (2007) Statistical Year Book 2007. CAPMAS, Cairo.

[24]   Howeidy, A., Shehayeb, D.K., Goll, E., Abdel Halim, K.M., Séjourné, M., Gado, M., Piffero, E., et al. (2009) Cairo’s Informal Areas between Urban Challenges and Hidden Potentials.
s%20Between%20Urban%20Challenges%20and%20Hidden%20Potentials/CairosInformalAreas_fulltext.pdf'>http://www.citiesalliance.org/sites/citiesalliance.org/files/CA_Docs/resources/Cairo's%20Informal%20Area
s%20Between%20Urban%20Challenges%20and%20Hidden%20Potentials/CairosInformalAreas_fulltext.pdf


[25]   World Bank (2008) Egypt Urban Sector: Towards and Urban Sector Strategy. Washington DC.
http://books.google.com.eg/books

[26]   Shekhar, S. (2004) Urban Sprawl Assessment Entropy Approach. GIS Development, 8, 43-48.

[27]   ESRI (2008) Arc GIS, Release 9.3. Environmental Systems Research Institute, Redlands, CA.

[28]   United Nations (1983) Manual X: Indirect Techniques for Demographic Estimation. United Nations Sales No. E. 83. XIII. 2, New York.
http://www.un.org/esa/population/unpop.htm

[29]   United Nations Population Fund-India (2011) Training Manual on Demographic Techniques.

 
 
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