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Journal of the Indian Society of Remote Sensing

, Volume 46, Issue 12, pp 2033–2044 | Cite as

Urban Slum Detection Approaches from High-Resolution Satellite Data Using Statistical and Spectral Based Approaches

  • R. Prabhu
  • R. A. Alagu Raja
Research Article
  • 34 Downloads

Abstract

This paper proposes a new technique to detect the urban slums from urban buildings using very high resolution data. Many cities in the Global South are facing the development and growth of highly dynamic slum areas, but often lack detailed spatial information. Unlike buildings, vegetation and other features, urban slums lack in their unique spectral signatures. Thus, accurate detection of slums using remote sensing data poses real challenge to researchers and decision-makers. In this work, gray-level co-occurrence matrix, Tamura-based statistical feature extraction and wavelet frame transform-based spectral feature extraction techniques are proposed for detecting the urban slums from urban buildings. The very high resolution data of Madurai city, South India, acquired by Worldview-2 sensor (1.84 m) proved the ability of the proposed approaches to identify urban slums from urban buildings. Experimental results demonstrate that the proposed wavelet frame transform-based approach can generate higher classification accuracy than other approaches.

Keywords

Wavelet frame transform GLCM Tamura Urban slums Urban buildings 

Notes

Acknowledgements

We are very grateful to the provider DigitalGlobe, for providing imagery for research purpose under 8-band proposal scheme.

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Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringSt. Joseph’s College of EngineeringChennaiIndia
  2. 2.Remote Sensing and GIS Lab, Department of Electronics and Communication EngineeringThiagarajar College of EngineeringMaduraiIndia

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