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Modeling the Probable Growth of Slums by using Geoinformatics


Affiliations
1 Central University of Karnataka, Gulbarga, India
 

In both territorial and demographic terms, the world is becoming more and more urban. The consequence of urbanization in most of the developing countries, is characterized by informality, illegality and unplanned settlements in cities. The extension of slums in developing countries is a product of 20th and 21stcentury urban growth. A worldwide consensus on poverty has acknowledged slums and the living conditions of slum dwellers as a major challenge faced by humanity. Hence, it is essential to locate and map the slums for proper planning and improve their living conditions. In the present paper, an attempt has been made to study the growth of slums by using GIS and RS techniques. The study area selected for this analysis is Pune city. Seven criteria were selected along with land use layer (restricted to slum use), which made the model more reasonable and effective. Each criterion is processed with a specified method and forms one criterion layer. These criterion layers are regarded as the initial conditions in the CA generation courses. They are weighted equally in the probability analysis of MCE in ArcGIS. The probability layer is finally added with neighborhood map to get the final output. The results are very much similar to the ground reality. More than 85% of slums are concentrated in the zone of more and most favourable zones. Remaining 15% of slums are in less and least favourable zones. The area available for future growth also calculated and it shows that almost 35% of area for further slum growth can take place in this zone in the light of ongoing urbanisation. The results pertaining to slums are essential for future planning and sustainable management of available resources.

Keywords

Contourlet Transform, Maximum Likelihood Detector, Multiplicative Image Watermarking
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  • Modeling the Probable Growth of Slums by using Geoinformatics

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Authors

Sulochana Shekhar
Central University of Karnataka, Gulbarga, India

Abstract


In both territorial and demographic terms, the world is becoming more and more urban. The consequence of urbanization in most of the developing countries, is characterized by informality, illegality and unplanned settlements in cities. The extension of slums in developing countries is a product of 20th and 21stcentury urban growth. A worldwide consensus on poverty has acknowledged slums and the living conditions of slum dwellers as a major challenge faced by humanity. Hence, it is essential to locate and map the slums for proper planning and improve their living conditions. In the present paper, an attempt has been made to study the growth of slums by using GIS and RS techniques. The study area selected for this analysis is Pune city. Seven criteria were selected along with land use layer (restricted to slum use), which made the model more reasonable and effective. Each criterion is processed with a specified method and forms one criterion layer. These criterion layers are regarded as the initial conditions in the CA generation courses. They are weighted equally in the probability analysis of MCE in ArcGIS. The probability layer is finally added with neighborhood map to get the final output. The results are very much similar to the ground reality. More than 85% of slums are concentrated in the zone of more and most favourable zones. Remaining 15% of slums are in less and least favourable zones. The area available for future growth also calculated and it shows that almost 35% of area for further slum growth can take place in this zone in the light of ongoing urbanisation. The results pertaining to slums are essential for future planning and sustainable management of available resources.

Keywords


Contourlet Transform, Maximum Likelihood Detector, Multiplicative Image Watermarking

References