Vulnerability analysis on Hyderabad city, India
M.S. Boori, K. Choudhary, A.V. Kupriyanov

 

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

Full text of article: English language.

Abstract:

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.

Keywords:
city vulnerability, landsat data, remote sensing, GIS.

Citation:
Boori MS, Choudhary K., Kupriyanov AV. Vulnerability analysis on Hyderabad city, India. Computer Optics 2016: 40(5): 752-758. DOI: 10.18287/2412-6179-2016-40-5-752-758.

References:

  1. Chadchan J, Shankar R. An analysis of urban growth trends in the post-economic reforms period in India. Int J Sustainable Built Environ. 2012; 1(1), 36-49. DOI: 10.1016/j.ijsbe.2012.05.001.
  2. Boori MS, Vozenilek V, Choudhary K. Land use/cover disturbance due to tourism in Jeseniky Mountain, Czech Republic: A remote sensing and GIS based approach. The Egyptian Journal of Remote Sensing and Space Sciences, 2015; 18(1): 17-26. DOI: 10.1016/j.ejrs.2014.12.002.
  3. El Bastawesy M. Hydrological Scenarios of the Renaissance Dam in Ethiopia and Its Hydro-Environmental Impact on the Nile Downstream. J Hydro Engin 2014; 20(7). DOI: 10.1061/(ASCE)HE.1943-5584.0001112.
  4. Boori MS, Vozenilek V, Choudhary K. Exposure intensity, vulnerability index and landscape change assessment in Olomouc, Czech Republic, ISPRS: Int. Arch. Photogramm. Remote Sens. Spatial Inf Sci 2015; XL-7/W3: 771-776, DOI: 10.5194/isprsarchives-XL-7-W3-771-2015.
  5. Kaly UL, Pratt CR, Mitchell J. The Demonstration Environmental Vulnerability Index (EVI) 2004. SOPAC Technical Report 384.
  6. Adger WN. Vulnerability. Global Environmental Change 2006; 16 (3), 268-281. DOI: 10.1016/j.gloenv­cha.2006.02.006.
  7. Boori MS, Vozenilek V. Land-cover disturbances due to tourism in Jeseniky mountain region: A remote sensing and GIS based approach. Proc SPIE 2014; 9245: 92450T. DOI: 10.1117/12.2065112.
  8. Metzger MJ, Leemans R, Schroter D. A multidisciplinary multi-scale framework for assessing vulnerability to global change. International journal of applied earth observation and geo-information 2005; 7(4): 253-267. DOI: 10.1016/j.jag.2005.06.011.
  9. Boori MS, Choudhary K, Kupriyanoy A, Kovelskiy V. Four decades urban growth and land use change in Samara Russia through remote sensing and GIS techniques. Proc SPIE: Remote Sensing and Image Formation 2015; 9817: 98171A. DOI: 10.1117/12.2227992.
  10. Schröter D, Cramer W, Leemans R, Prentice IC, Araújo MB, Arnell NW, Bondeau A, Bugmann H, Carter TR, Gracia CA, de la Vega-Leinert AC, Erhard M, Ewert F, Glendining M, House JI, Kankaanpää S, Klein RJ, Lavorel S, Lindner M, Metzger MJ, Meyer J, Mitchell TD, Reginster I, Rounsevell M, Sabaté S, Sitch S, Smith B, Smith J, Smith P, Sykes MT, Thonicke K, Thuiller W, Tuck G, Zaehle S, Zierl B. Ecosystem Service Supply and Human Vulnerability to Global Change in Europe. Science 2005; 310(5752), 1333-1337. DOI: 10.1126/science.1115233.
  11. Boori MS, Kuznetsov AV, Choudhary K, Kupriyanoy A. Satellite image analysis to evaluate the urban growth and land use changes in the city of Samara from 1975 to 2015. Computer Optics 2015; 39(5): 818-822. DOI: 10.18287/0134-2452-2015-39-5-818-822.
  12. Altieri L, Cocchi D, Giovanna P, Scott M, Ventrucci M. urban sprawl scatterplots for urban morphological zones data. Ecol Indic 2014; 36: 315-323. DOI: 10.1016/j.eco­lind.2013.07.011.
  13. Boori MS, Netzband M, Vozenílek V, Choudhary K. Urban growth in last three decades in Kuala Lumpur, Malaysia. IEEE: Urban Remote Sensing Event (JURSE) 2015 Joint, 2015; 2015e: 01-04. DOI: 10.1109/JUR­SE.2015.7120536.
  14.  Lu Q, Weng D. Urban classification using full spectral information of Landsat ETM+ imagery in Marion County, Indiana. Photogrammetric Engineering & Remote Sensing 2005; 71(11): 1275-1284. DOI: 10.14358/PERS.71.11.1275.
  15. Boori MS, Choudhary K, Kupriyanoy A, Kovelskiy V. Urbanization data of Samara City, Russia. Data Brief 2016; 6: 885-889. DOI: 10.1016/j.dib.2016.01.056.
  16. Thinh NX, Arlt G, Heber B, Hennersdorf J, Lehmann I. Pin-pointing sustainable urban land use structures with the aid of GIS and cluster analysis. 15th International Symposium Informatics for Environmental Protection, Zürich 2001: 559-567.
  17. Lillesand TM, Kiefer RW. Remote sensing and image interpretation. 4th ed. New York: John Wiley and Sons; 1999. ISBN: 978-0-471-25515-4.
  18. Lim B, Spanger-Siegfried E, eds, Burton I, Malone E, Huq S. Adaptation Policy Frameworks for Climate Change: Developing Strategies, Policies, and Measures. Cambridge, UK: Cambridge University Press; 2005.
  19. Yoo GY, Kim IA. Development and Application of a Climate Change Vulnerability Index. Seoul: Korea Environment Institute; 2008.
  20. Asare-Marfo D, Birol E, Gonzalez C, Moursi M, Perez S, Schwarz J, Zeller M. Prioritizing countries for biofortification interventions using country-level data. Harvestplus working paper 11. Washington, DC: International Food Policy Research Institute (IFPRI); 2013.
  21. Zhang K, Simard M, Ross M, Rivera-Monroy V, Houle P, Ruiz P, Twilley R, Whelan K. Airborne laser scanning quantification of disturbances from hurricanes and lightning strikes to mangrove forests in Everglades National Park, USA. Sensors 2008; 8(4): 2262-2292. DOI: 10.3390/s8042262.
  22. Calderon-Aguilera L, Rivera-Monroy V, Porter-Bolland L, Martínez-Yrízar A, Ladah L, Martínez-Ramos M, Alcocer J, Santiago-Pérez A, Hernandez-Arana H, Reyes-Gómez V, Pérez-Salicrup D, Díaz-Nuñez V, Sosa-Ramírez J, Herrera-Silveira J, Búrquez A. An assessment of natural and human disturbance effects on Mexican ecosystems: current trends and research gaps. Biodivers Conserv 2012; 21(3): 589-617. DOI: 10.1007/s10531-011-0218-6.
  23. Li X-H, Liu J-L, Gibson V, Zhu Y-G. Urban sustainability and human health in China, East Asia and Southeast Asia. Current Opinion in Environmental Sustainability 2012; 4(4), 436-442. DOI: 10.1016/j.cosust.2012.09.007.
  24. Xinliang X, Min X. Quantifying spatiotemporal patterns of urban expansion in China using remote sensing data. Cities 2013; 35, 104-113. DOI: 10.1016/j.cities.2013.05.002.
  25. Birkmann J. Risk and vulnerability indicators at different scales: applicability, usefulness and policy implications. Environ Hazards 2007; 7(1), 20-31. DOI: 10.1016/j.envhaz.2007.04.002.

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