Detecting Slums from SPOT Data in Casablanca Morocco Using an Object Based Approach

Hassan Rhinane, Atika Hilali, Aziza Berrada, Mustapha Hakdaoui

.

DOI: 10.4236/jgis.2011.33018                

Abstract

Casablanca, Morocco's economic capital continues today to fight against the proliferation of informal settle- ments affecting its urban fabric illustrated especially by the slums. Actually Casablanca represents 25% of the total slums of Morocco [1]. These are the habitats of all deprived of healthy sanitary conditions and judged precarious from the perspective humanitarian and below the acceptable. The majority of the inhabi- tants of these slums are from the rural exodus with insufficient income to meet the basic needs of daily life. Faced with this situation and to eradicate these habitats, the Moroccan government has launched since 2004 an entire program to create cities without slums (C.W.S.) to resettle or relocate families. Indeed the process control and monitoring of this program requires first identifying and detecting spatial habitats. To achieve these tasks, conventional methods such as information gathering, mapping, use of databases and statistics often have shown their limits and are sometimes outdated. It is within this framework and that of the great German Morocco project “Urban agriculture as an integrative factor of development that fits our project de- tection of slums in Casablanca. The use of satellite imagery, particulary the HSR, has the advantage of providing the physical coverage of urban land but it raises the difficulty of choosing the appropriate method to apply.This paper is actually to develop new approaches based mainly on object-oriented classification of high spatial resolution satellite images for the detection of slums.This approach has been developed for mapping the urban land through by integration of several types of information (spectral, spatial, contextual ...) (Hofmann, P ., 2001, Herold et al. 2002b; Van Der Sande et al., 2003, Benz et al., 2004, Nobrega et al., 2006). In order to refine the result of classification, we applied mathematical morphology and in particular the closing filter. The data from this classification (binary image), which then will be used in a spatial data- base (ArcGIS).

Keywords

Slums, Urban Remote Sensing, SPOT 5, Object Based Image Analysis, ArcGis

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Banque mondial, “Rapport de L’Analyse D’lmpact Social et Sur la Pauvreté,” 2006, p. 62.
[2]	K. Busgeeth, J. Whisken and A. Brits, “Potential Application of Remote Sensing in Monitoring Informal Settlements in Developing Countries Where Complimentary Data Does Not Exist,” Planning Africa Conference— Shaping the Future, Johannesburg, 4-16 April 2008, pp. 314-328.
[3]	M. Laoudi, “Casablanca a travers ses petits entrepreneurs de lapauvrté. Apprécu sur les micro-activités marchandes de rue dans une métropole maghrébine. Série thèse et mémoire N 8. Université Hassan II A?n Chock, Faculté des lettres et sciences humaines Casablanca, 2001, p. 319, 320.
[4]	S. Gadal, “Urbanisation et Dynamiques de Peuplements: Casablanca, 1994-2002, UMR 63 IRD-UVSQ,” Ver- sailles Saint-Quentin-en-Yvelines University, Ver- sailles, 2005.
[5]	S. Mason, C. Fraser, “Image Sources For Informal Settlement Management,” Photogrammetric Record, Vol. 16, No. 92, 1998, pp. 313-330.
[6]	P. Hofmann, “Detecting Informal Settlements from IKONOS Image Data Using Methods of Object Oriented Image Analysis: An Example from Cape Town, South Africa,” In: C. Jrgens, Ed., Remote Sensing of Urban Areas, Regensburger Geographische Schriften, Regensburg, 2001, pp. 107-118.
[7]	P. Hurskainen and P. Pellikka, “Change Detection Of Informal Settlements Using Multi-Temporal Aerial Photographs—The Case of Voi, SE-Kenya,” Proceedings of the 5th AARSE Conference, 18-21 October 2004, Nairobi, pp. .
[8]	T. Lemma, “A Comparison of Methodologies for Monitoring Slum Conditions within Millennium Development Goals, the Case Study of Addis ababa, Ethiopia, Thesis for Master,” International Institute for Geo-information Scinces and Earth Observation, Enschde, 2005.
[9]	P. Hofmann, J. Strobl, T. Blaschke and H. Kux, “Detecting Informal Settlements from Quickbird Data in Rio de Janeiro Using an Object Based Approach,” Accessed 25 September 2007.
[10]	G. Skupinski, D. BinhTran and C. Weber, (2009). “Lesimages Satellites Spot Multi-Dates et la Métrique Spatiale dans L’etude du Changement Urbain Et Suburbain—Le Cas de la Basse Vallée de la Bruche (Bas-Rhin, France),” Cybergeo: European Journal of Geography, Systèmes, Modélisation, Géostatistiques, article 439, mis en ligne le 12 mars 2009, modifié le 03 juin 2009. http://cybergeo.revues.org/index21995.html.
[11]	W. K. Pratt, “Digital Image Processing,” Willey inter-sciences, New York, 1978, p. 743. M. Robin, “La télédétection,” Nathan, Paris, 1995, p. 318
[12]	Y. Baudot, “Télédétection Aérospatiale et Analyse Géographique de la Population des Villes dans les Pays en Développement,” Thèse de doctorat, Université Catho- lique de Louvain, Louvain-la-Neuve, 1994.
[13]	P. Terrettaz “Délimitation des agglomérations et segmentation urbaine à l’aide d’images satellites Spot HRV,” Thèse de Doctorat, Université de Fribourg, Fri- bourg, 1998.
[14]	J. A. Benediktsson, M. Pesaresi and K. Amason, “Classification and Feature Extraction for Remote Sensing Images From Urban Areas Based on Morphological Transformations,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 9, 2003, pp. 1940-1949.
[15]	D. Sheeren, S. Lefèvre and J. Weber, “La Morpho- Logiemathématique Binaire Pour L’extraction Auto- matique des Batiments dans les Images THRS,” Revue Internationale de Géomatique, Vol. 17, No. 3-4, 2007, pp. 333-352.
[16]	J. G. Masek, F. E. Lindsay and S. N. Goward, “Dynamics of Urban Growth in the Washington D.C. Metropolitan Area, 1973-1996, from Landsat Observations,” International Journal of Remote Sensing, Vol. 21, No. 18, 2000, pp. 3473-3486. doi:10.1080/014311600750037507
[17]	T. Fung, “An Assessment of TM Imagery for Land Cover Change Detection,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 28, No. 4, 1990, pp. 681-684. doi:10.1109/TGRS.1990.572980
[18]	X. Chen, X. Li and J. Ma, “Urban Change Detection Based on Self-Organizing Feature Map Neural Network,” Proceedings of the IEEE International Symposium on Geoscience and Remote Sensing, Vol. 5, 20-24 September 2004, pp. 3428-3431.
[19]	P. Gamba, F. Dell’Acqua, “Increased Accuracy Multiband Urban Classification Using a Neuro-Fuzzy Classifier,” International Journal of Remote Sensing, Vol. 24, No. 4, 2003, pp. 827-834.
[20]	M. Stasolla and P. Gamba, “Exploiting Spatial Patterns For Informal Settlement Detection Inarid Environments Using Optical Spaceborne Data,” International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 36, 2007, pp. .
[21]	C. H. William, F. C. Williamand and K. Gyimah, “High- Resolution Lidar-Based Landslide Hazard Mapping and Modeling, UCSF Parnassus Campus, San Francisco, USA,” Bulletin of Engineering Geology and the Environment, Vol. 68, No. 2, 2009, pp. 263-276.
[22]	V. Walter, “Object-Based Classification of Remote Sensing Data for Change Detection,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, No. 3-4, 2004, pp. 225-238.
[23]	U. C. Benz, P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen, “Multi-Resolution, Object-Oriented Fuzzy Analysis of Remote Sensing Data for GIS-ready information,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 58, No. 3-4, January 2004, pp. 239-258.
[24]	G. Sartori, G. Nembrini and F. Stauffer, “Monitoring of Urban Growth of Informal Settlements and Population Estimation from Aerial Photography and Satellite Imaging,” 2002. Occasional paper-thirstycitiesinwar.com.
[25]	J. Abbott, “The Use of GIS in Informal Settlement Upgrading: Its Role and Impact on The Community and on Local Government,” Habitat International, Vol. 27, No. 4, 2003, pp. 575-593. doi:10.1016/S0197-3975(03)00006-7
[26]	A. Michel and B. Lortic, “Typologies Urbaines Et Télédétection Satellitaire: La Notion de Zones en Milieu Urbain,” Espace Géographique (FRA), Vol. 21, No. 2, 1992, pp. 167-178.
[27]	T. Bauer and K. Steinccocher, “Per_Parcel Land Classification in Urban Areas Applying a Rule-Based Technique,” GeoBIT/GIS, Vol. 6, 2001, pp. 24-27.
[28]	A. Puissant and C. Weber, “Démarche Orientée ‘Objets-Attributs’ et Classification D'images THRS,” Revue Fran?aise de Photogrammétrie et De Télé- détection, Vol. 173-174, 2004, pp. 123-134.
[29]	M. Herold, M. Gardner, B. Hadley and D. Roberts, 2002b. “The Spectral Dimension in Urban Land Cover Mapping from High-Resolution Optical Remote Sensing Data,” Proceedings of the 3rd Symposium on Remote Sensing of Urban Areas, June 2002, Istanbul, on CD Rom. http://www.lavieeco.com/news/economie/Bidonvillesencore-45-villes-a-traiter-d-ici-2012-17135.html (12/7/2010).
[30]	C. J. Van Der Sande, S. M. De Jong, A. P. J. De Roo, “A Segmentation and Classification Approach of IKONOS-2 Imagery for Land-Cover Mapping to Assist Flood Risk and Flood Damage Assessment,” International Journal of Applied Earth Observation and Geoinformation, Vol. 4. No. 3, 2003, pp. S217-S229. doi:10.1016/S0303-2434(03)00003-5
[31]	R. A. A. Nobrega, C. G. O’Hara, J. A. Quintanilha, “Detecting Roads in Informal Settlements Surrounding, Saopaulo City by Using Object_Based Classification,” Proceedings of the 1st International Conference on Object- Based Image Analysis, Salzburg, 2006, pp. .
[32]	M. Baatz and A. Sch?pe, “Multiresolution Segmentation —An Optimization Approach for High Quality Multi- Scale Image Segmentation,” Angewandte geographische Informationsverarbeitung XII: Beitr?ge zum AGIT-Symposium, Salzburg, 2000, pp. 12-23.
[33]	J. Schieve, “Segmentation of High-Resolution Remotely Sensed Data—Concepts, Applications and Problems,” Symposium on Geospatial Theory, Processings and Applications, Ottawa, 2002.
[34]	T. Esch, A. Roth, S. Dech, “Robust Approach Towards an Automated Detection of Built-up Areas from High Resolution Radar Imagery,” Proceedings of the ISPRS WG VII/1 “Human Settlements and Impact Analysis” 3rd International Symposium Remote Sensing and Data Fusion Over Urban Areas and the 5th International Symposium Remote Sensing of Urban Areas. Tempe, 14-16 March 2005.
[35]	A. Karsenty, Antunes, B. A-F, Centeno, J-Silva. (2007) “Classification Orientée Objet de la Perméabilité des Sols en Zone Urbaine a L’aide D’imagerie Très Haute Résolution et de Données Laser Scanner à Curitiba (Brésil)” Anais XIII Simpósio Brasileiro de Sensoriamento Remoto, Florianópolis, INPE, p. 565-572
[36]	E. Freauman, E. Wolf, “Segmentation of Very High Spatial Resolution Satellite Images in Urban Areas for Segments-Based Classification,” Proceedings of the 3rd International Symposium Remote Sensing and Data Fusion Over Urban Areas, Tempe, 2005, pp. .
[37]	L. Sparfel, F. Gourmelon and I. Le Berre, “Approch Orienté-Objet de L’occupation des Sols en Zone Cotière,” Revue Télédétection, Vol. 8, No. 4, 2008, pp. 237-256.
[38]	G. Willhauck, “Comparison of Object Oriented Classification Techniques and Standard Image Analysis for the Use of Change Detection between SPOT Multispectral Satellite Images and Aerial Photos,” International Archives of Photogrammetry and Remote Sensing, Vol. 33, 2000, pp. 214-221.
[39]	R. Caloz and C. Collet, “Précis de Télédétection,” Traite- ments numériques d’images de télédétection, Presses de l’Université du Québec/AUPELF, Sainte Foy, Vol. 3, 2001.
[40]	SDAU (2004) “Plan de développement stratégique et Schéma Directeur d’Aménagement urbain de la Wilaya du Grand Casablanca, Projet de diagnostic et Enjeux du développement, rapport N°3.
[41]	R. G. Congalton “Eview of Assessing the Accuracy of Classifications of Remotely Sensed Data,” Remote Sensing of Environment, Vol. 37, 1991, pp. 35-46. doi:10.1016/0034-4257(91)90048-B
[42]	R.-G. Conglaton and K. Green, “Assessing the Accuracu of Remotely Sensed Data: Principles and Practices,” Lewis Publishers, New York, 1999.
[43]	M. Aminipouri, “Objected-Oriented Analysis of very High Resolution Orthophotos for Estimating the Population of Slum Areas,” Case of Dar-Es-Salam, Tanzania, 2009.