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ЖУРНАЛЫ // Компьютерная оптика // Архив

Компьютерная оптика, 2016, том 40, выпуск 5, страницы 752–758 (Mi co297)

Эта публикация цитируется в 8 статьях

IMAGE PROCESSING, PATTERN RECOGNITION

Vulnerability analysis on Hyderabad city, India

M. Booriabc, K. Choudharya, A. V. Kupriyanovad

a Samara National Research University, Samara, Russia
b Bonn University, Bonn, Germany
c American Sentinel University, Colorado, USA
d Image Processing Systems Institute оf RAS, – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

Аннотация: City vulnerability is an assessment of priorities for implementation in a city. Thus, it is imperative to determine vulnerable regions in the city to identify priority areas that may require immediate intervention. Several methods used for national, international and local level vulnerability assessment are based on remote sensing and GIS technology. This paper aims to determine the vulnerability of Hyderabad city using a geospatial based vulnerability index for sustainable development of the city. We use an urbanization and vulnerability concept for the development of city policy measures. We assessed the city vulnerability using a conceptual diagram composed of exposure, sensitivity and adaptive capacity. For Exposure, we considered the elevation (contour), watershed, waterway, roads, railways and airport thematic layers. For Sensitivity, the built-up area, industry, manages (?) system such as farmland and land use/cover map from GIS data were used. To examine the adaptive capacity, we addressed the natural vegetation layer, economic points and infrastructure. Results show that the center and northern part of the city are highly and extremely vulnerable due to industry and high socio-economic activities when compared with the southern part of the city. We divided the whole city into 5 types of vulnerability: Resilient 2.24 %, at risk 13.20 %, vulnerable 46.15 %, highly vulnerable 7.26 % and extremely vulnerable 31.15 % , in terms of the city area percentage. The vegetation area (50.51 %) has the maximum vulnerable area and the vulnerable class covers the maximum area (46.15 %) of the city. All this information is very indispensable and can be used to address management issues, such as resource prioritization and optimization.

Ключевые слова: city vulnerability, landsat data, remote sensing, GIS.

Поступила в редакцию: 19.02.2016
Принята в печать: 21.10.2016

Язык публикации: английский

DOI: 10.18287/2412-6179-2016-40-5-752-758



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