Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery
Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery
This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.
urban, developing countries, identification, high resolution, multitemporal
130-137
Kit, Oleksandr
48dd3a17-16ef-4682-82c8-24950abc0681
Luedeke, Matthias
e6aee3bc-2237-40f8-a701-03a0b7e9a5a7
September 2013
Kit, Oleksandr
48dd3a17-16ef-4682-82c8-24950abc0681
Luedeke, Matthias
e6aee3bc-2237-40f8-a701-03a0b7e9a5a7
Kit, Oleksandr and Luedeke, Matthias
(2013)
Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery.
ISPRS Journal of Photogrammetry and Remote Sensing, 83, .
(doi:10.1016/j.isprsjprs.2013.06.009).
Abstract
This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.
Text
Multitemporal_slums_manuscript.pdf
- Accepted Manuscript
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Published date: September 2013
Keywords:
urban, developing countries, identification, high resolution, multitemporal
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GeoData
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Local EPrints ID: 354907
URI: http://eprints.soton.ac.uk/id/eprint/354907
ISSN: 0924-2716
PURE UUID: 55896ab0-dd49-439c-8b09-d89f7232e3fb
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Date deposited: 07 Aug 2013 11:31
Last modified: 14 Mar 2024 14:26
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Author:
Matthias Luedeke
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