CoChat
Sign Up
Cited by 65Land Use and Ecosystem ServicesRemote Sensing and Land UseUrban Development and Societal Issues

The DOI matches its Crossref record.

Analyzing the Driving Factors Causing Urban Expansion in the Peri-Urban Areas Using Logistic Regression: A Case Study of the Greater Cairo Region

Open access
Salem, Muhammad, Tsurusaki, Naoki, Divigalpitiya, Prasanna·2019·Infrastructures
DOI 10.3390/infrastructures4010004
Open this paper in CoChat — free accountOpen PDF

Abstract

The peri-urban area (PUA) of the Greater Cairo Region (GCR) in Egypt has witnessed a rapid urban expansion during the last few years. This urban expansion has led to the loss of wide, areas of agriculture lands and the annexation of many peripheral villages into the boundary of the GCR. This study analyzed the driving factors causing the urban expansion in the GCR during the period 2007–2017 using the logistic regression model (LRM). Eight independent variables were applied in this model: distance to the nearest urban center, distance to the nearest center of regional services, distance to water streams, distance to the main agglomeration, distance to industrial areas, distance to nearest road, number of urban cells within a 3 × 3 cell window and population density. The analysis was conducted using LOGISTICREG module in Terrset software. This research showed that the population density and distance to the nearest road have the highest regression coefficients, 0.540 and 0.114, respectively, and were the most significant driving factors of urban expansion during the last 10 years (2007–2017). Moreover, based on the results of the LRM, a probability map of urban expansion in the PUA was created, which shows that most urban expansion would be around the existing urban areas and near roads. The relative operating characteristic (ROC) value of 0.93 indicates that the probability map of urban expansion is valid.

Overview

Integrity signals

Registry

Crossref · 10.3390/infrastructures4010004

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Still being checked.

Research works printed but not linked: 36

  1. Bhatta, B. (2010). Remote Sensing, GIS, and Urban Analysis. Analysis of Urban Growth and Sprawl from Remote Sensing, Springer. · DOI
  2. Dutta, 2012, Land Use Dynamics and Peri-Urban Growth Characteristics: Reflections on Master Plan and Urban Suitability from a Sprawling North Indian City, Environ. Urban. Asia, 3, 277, 10.1177/0975425312473226 · DOI
  3. Ramachandra, 2015, Monitoring Urbanization and Its Implications in a Mega City from Space: Spatiotemporal Patterns and Its Indicators, J. Environ. Manag., 148, 67, 10.1016/j.jenvman.2014.02.015 · DOI
  4. Das, N.D. (2017). Land-Use Dynamics of Peri-Urban Areas of Metropolitan Cities with Special Focus on Delhi. Marginalization in Globalizing Delhi: Issues of Land, Livelihoods and Health, Springer. No. Issues of Land, Livelihoods and Health. · DOI
  5. Chirisa, I., Mazhindu, E., and Bandauko, E. (2016). Peri-Urban Developments and Processes in Africa with Special Reference to Zimbabwe, Springer International Publishing. · DOI
  6. Allen, 2003, Environmental Planning and Management of the Peri-Urban Interface: Perspectives on an Emerging Field, Environ. Urban., 15, 135, 10.1177/095624780301500103 · DOI
  7. Dupont, V.E., and Centre, D.S.H. (2006). Peri—Urban Dynamics: Population, Habitat and Environment on the Peripheries of Large Indian Metropolises. Population (English Edition), CSH.
  8. Sassen, 2009, Peri-Urbanization: Zones of Rural-Urban Transition, Human Settlement Development Volume 1, Volume 1, 281
  9. Salem, 2015, Peri-Urban Dynamics and Land-Use Planning for the Greater Cairo Region in Egypt, WIT Transactions on The Built Environment, Volume 168, 109, 10.2495/SD150101 · DOI
  10. Sarkar, 2013, Dynamics of the Peri Urban Interface: Issues and Perspectives for Management, Trans. Inst. Indian Geogr., 35, 49
  11. Iaquinta, 2000, Defining the Peri-Urban: Rural-Urban Linkages and Institutional Connections, Land Reform, 2, 8
  12. 2012, Land Use Planning for Sustainable Development of Peri-Urban Zones, Spatium, 28, 15
  13. Aguilar, 2008, Peri-Urbanization, Illegal Settlements and Environmental Impact in Mexico City, Cities, 25, 133, 10.1016/j.cities.2008.02.003 · DOI
  14. Bhatta, B. (2010). Causes and Consequences of Urban Growth and Sprawl. Analysis of Urban Growth and Sprawl from Remote Sensing Data, Springer. · DOI
  15. Ju, 2016, Driving Forces and Their Interactions of Built-up Land Expansion Based on the Geographical Detector—A Case Study of Beijing, China, Int. J. Geogr. Inf. Sci., 30, 2188, 10.1080/13658816.2016.1165228 · DOI
  16. Siddiqui, 2018, Urban Growth Dynamics of an Indian Metropolitan Using CA Markov and Logistic Regression, Egypt. J. Remote Sens. Space Sci., 21, 229
  17. Osman, 2016, Driving Factors of Urban Sprawl in Giza Governorate of the Greater Cairo Metropolitan Region Using a Logistic Regression Model, Int. J. Urban Sci., 20, 206, 10.1080/12265934.2016.1162728 · DOI
  18. Lawanson, 2012, An Investigation of Rural-Urban Linkages of The Lagos Megacity, Nigeria, J. Constr. Proj. Manag. Innov., 2, 464
  19. Braimoh, 2007, Spatial Determinants of Urban Land Use Change in Lagos, Nigeria, Land Use Policy, 24, 502, 10.1016/j.landusepol.2006.09.001 · DOI
  20. Appiah, 2014, Determinants of Peri-Urbanization and Land Use Change Patterns in Peri-Urban Ghana, J. Sustain. Dev., 7, 95, 10.5539/jsd.v7n6p95 · DOI
  21. Mahamud, M.A., Samat, N., and Mohd Noor, N. (2016). Identifying Factors Influencing Urban Spatial Growth for The George Town Conurbation. Plan. Malays. J., 14. · DOI
  22. Helbich, 2013, Integration of Logistic Regression, Markov Chain and Cellular Automata Models to Simulate Urban Expansion, Int. J. Appl. Earth Obs. Geoinf., 21, 265
  23. Mohamed, 2012, Analysis of Urban Growth at Cairo, Egypt Using Remote Sensing and GIS, Nat. Sci., 4, 355
  24. Sims, D. (2011). Understanding Cairo: The Logic of a City Out of Control, The American University in Cairo Press. · DOI
  25. Salem, M., Tsurusaki, N., Divigalpitiya, P., and Osman, T. (2018). Driving Factors of Urban Expansion in Peri-Urban Areas of Greater Cairo Region. REAL CORP 2018–EXPANDING CITIES–DIMINISHING SPACE. Are “Smart Cities” the Solution or Part of the Problem of Continuous Urbanisation Around the Globe? Proceedings of 23rd International Conference on Urban Planning, Regional Development and Information, Vienna, Austria, 4–6 April 2018, REAL CORP.
  26. Poelmans, 2010, Complexity and Performance of Urban Expansion Models, Comput. Environ. Urban Syst., 34, 17, 10.1016/j.compenvurbsys.2009.06.001 · DOI
  27. Hamdy, O., Zhao, S., Osman, T., Salheen, M., and Eid, Y. (2016). Applying a Hybrid Model of Markov Chain and Logistic Regression to Identify Future Urban Sprawl in Abouelreesh, Aswan: A Case Study. Geosciences, 6. · DOI
  28. Tobergte, D.R., and Curtis, S. (2013). Logistic Regression, A Self-Learning Text, Springer Science & Business Media.
  29. Clark, W.A.V., and Hosking, P.L. (1986). Statistical Methods for Geographers, Wiley.
  30. Nong, 2011, Urban Growth Pattern Modeling Using Logistic Regression, Geo-Spat. Inf. Sci., 14, 62, 10.1007/s11806-011-0427-x · DOI
  31. Liao, 2014, Modeling Determinants of Urban Growth in Dongguan, China: A Spatial Logistic Approach, Stoch. Environ. Res. Risk Assess., 28, 801, 10.1007/s00477-012-0620-y · DOI
  32. Shu, 2014, Spatiotemporal Variation Analysis of Driving Forces of Urban Land Spatial Expansion Using Logistic Regression: A Case Study of Port Towns in Taicang City, China, Habitat Int., 43, 181, 10.1016/j.habitatint.2014.02.004 · DOI
  33. Chen, L., Ren, C., Zhang, B., Wang, Z., and Liu, M. (2018). Quantifying Urban Land Sprawl and Its Driving Forces in Northeast China from 1990 to 2015. Sustainbility, 10. · DOI
  34. Huang, 2007, Modeling the Spatial Pattern of Farmland Using GIS and Multiple Logistic Regression: A Case Study of Maotiao River Basin, Guizhou Province, China, Environ. Model. Assess., 12, 55, 10.1007/s10666-006-9052-8 · DOI
  35. Hu, 2007, Modeling Urban Growth in Atlanta Using Logistic Regression, Comput. Environ. Urban Syst., 31, 667, 10.1016/j.compenvurbsys.2006.11.001 · DOI
  36. Lam, 1992, On the Issues of Scale, Resolution, and Fractal Analysis in the Mapping Sciences, Prof. Geogr., 44, 88, 10.1111/j.0033-0124.1992.00088.x · DOI

Cited by

Sorted by citations

See all 65

Metadata

Authors
Salem, M., Tsurusaki, N., & Divigalpitiya, P.
Affiliations
Kyushu University (JP)
Corresponding author
Salem, Muhammad
ORCID
Venue
Infrastructures
Publisher
MDPI AG
Published
2019-01-05
Volume
4
Issue
1
Pages
4
ISSN
2412-3811 (ISSN-L)
DOI
10.3390/infrastructures4010004
OpenAlex
W2906992378
Cited by
65
References
0
Citations by year
2026: 3 · 2025: 14 · 2024: 12 · 2023: 8 · 2022: 7 · 2021: 10 · 2020: 10 · 2019: 1
FWCI
3.60
Type
journal article
Language
en
Open access
Licence
Locations
  • Infrastructures (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
  • Social Sciences › Geography, Planning and Development › Remote Sensing and Land Use
  • Social Sciences › Urban Studies › Urban Development and Societal Issues
Keywords
urban expansion, peri-urban areas, driving factors, Greater Cairo Region, population density, road proximity, land use change, agricultural land loss, urbanization

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Analyzing the Driving Factors Causing Urban Expansion in the Peri-Urban Areas Using Logistic Regression: A Case Study of the Greater Cairo Region. https://app.cochat.ai/papers/10.3390/infrastructures4010004
The paper
Salem, M., Tsurusaki, N., & Divigalpitiya, P. (2019). Analyzing the Driving Factors Causing Urban Expansion in the Peri-Urban Areas Using Logistic Regression: A Case Study of the Greater Cairo Region. Infrastructures. https://doi.org/10.3390/infrastructures4010004