Monitoring urban expansion using SVM classification approach in Khenifra city (Morocco)

Abstract

Urban expansion is a major process in developing countries such as Morocco. Since their appearance in the 1970s, digital remote-sensing space sensors have been used to provide images with spatial and spectral resolutions that are adequate to comprehend the phenomenon of urban expansion. Become real tools for cities management and planning, through the many applications. Using Landsat images, we studied Khenifra’s (Moroccan city) urban area evolution and extension to quantify its impact on current landscape. A supervised classification using support vector machines (SVM) was employed to extract the urban state in three periods 1991, 2000 and 2017. The results reveal a clear progression of total occupied urban space from 12% in 2000 until 36% in 2017. This expansion is unevenly distributed in space, and at slightly different rates depending on the period considered. This phenomenon of significant urban expansion is largely related to population growth and the rural exodus.

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References

  1. Aghababaee H, Amini J, Tzeng YC (2013) Contextual PolSAR image classification using fractal dimension and support vector machines. Eur J Remote Sens 46:317–332

    Article  Google Scholar 

  2. Alberti M, Weeks R, Booth D, Hill K, Coe S, Stromberg E (2002) Land cover change analysis for the Central Puget Sound Region 1991–1999. Final Report. Urban Ecology Research Laboratory, University of Washington, 2002.

  3. Baojuan Z, Soe WM, Prasad ST, Rimjhim MA (2015) A support vector machine to identify irrigated crop types using time-series Landsat NDVI data. Int J Appl Earth ObsGeoinf 34:103–112

    Article  Google Scholar 

  4. Barles S, Breysse D, Guillerme A, Leyval C (1999) Le sol urbain, economica, anthropos collection villes, Paris

  5. Ben-Hur A, Weston J (2010) A user’s guide to support vector machine. In: Carugo, O, Eisenhaber F (Eds) Data mining techniques for the life sciences. Humana Press, pp. 223–239.

  6. Clergeau P. (2007) Une écologie du paysage urbain, Editions Apogée

  7. Cosinschi M, Racine J-B. (1998) Géographie urbaine. In: Bailly A, Les Concepts de la géographie urbaine, Paris, Armand Colin

  8. Foody GM, Mathur A (2004) Toward intelligent training of supervised image clas-sifications: directing training data acquisition for SVM classificatio. Remote Sens Environ 93:107–117

    Article  Google Scholar 

  9. Germaine S, Wakeling BF (2001) Lizard species distributions and habitat occupation along an urban gradient in Tucson, Arizona, USA. Biol Cons 97(2):229–237

    Article  Google Scholar 

  10. Huang C, Davis DS, Townshend JRG (2002) An assessment of support vector machines for land covers classification. Int J Remote Sens 23(4):725–749

    Article  Google Scholar 

  11. Jensen JR, Cowen DC (1999) Remote sensing of urban/suburban infrastructure and socio-economic attributes. PhotogrammEng Remote Sens 65:611–622

    Google Scholar 

  12. Jürgens C (ed) (2003) Remote sensing of urban areas. In: Proceedings of the ISPRS WG VII/4 symposium, Regensburg, 27–29 June 2003, vol XXXIV-7/W9. The international archives of the photogrammetry, remote sensing and satellite information sciences.

  13. McKinney M-L (2006) Urbanization as major cause of biotic homogenisation. Biol Cons 127(3):247–260

    Article  Google Scholar 

  14. Melgani F, Bruzzone L (2004) Classification of hyperspectral remote sensing images with support vector machines. IEEE Trans Geosci Remote Sens 42(8):1778–1790

    Article  Google Scholar 

  15. Mountrakis G, Im J, Ogole C (2011) Support vector machines in remote sensing: a review. ISPRS J Photogram Remote Sens 66:247–259

    Article  Google Scholar 

  16. Pal M, Mathur PM (2005) Support vector machines for classification in remote sensing. Int J Remote Sens 26(5):1007–1011

    Article  Google Scholar 

  17. Pumain D (2006) Systèmes de villes et niveaux d’organisation. In: Bourgine P, Lesne A (dir.) Morphogenèse, l'origine des formes, Paris, Belin, Collection Echelles.

  18. RGPH (2014) Note on the first results of the General Population and Housing Census 2014, Khenifra province.

  19. Sassan M, Mahmoud RD (2016) Urban sprawl assessment and modeling using landsat images and GIS. Model Earth Syst Environ 2:155

    Article  Google Scholar 

  20. Vapnik VN (1999) The nature of statistical learning theory, 2nd edn. Springer, New York

    Google Scholar 

  21. Weber C (1995) Satellite images and urban environment. Hermès-Lavoisier, Paris

    Google Scholar 

  22. Wu J (2008) (2008) Making the case for landscape ecology: an effective approach to urban sustainability. Landsc J 27(1):41–50. https://doi.org/10.3368/lj.27.1.41

    Article  Google Scholar 

  23. Xiaojun Y (2011) Urban remote sensing: monitoring synthesis and modeling in the urban environment. Willey-Blackwell, Oxford, p 388

    Google Scholar 

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Acknowledgements

The authors are pleased to acknowledge the Khenifra region for providing the facilities for the research. The authors wish to thank the governor of Khenifra province and the president of the Atlas group. They also thank the staff of the company SEMGAT for their help and coordination.

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Correspondence to Driss Elhamdouni.

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Elhamdouni, D., Arioua, A. & Karaoui, I. Monitoring urban expansion using SVM classification approach in Khenifra city (Morocco). Model. Earth Syst. Environ. (2021). https://doi.org/10.1007/s40808-021-01092-w

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Keywords

  • Urban expansion
  • SVM classification
  • Landsat
  • Khenifra city