Skip to main content
Log in

Mapping and assessing land degradation vulnerability in Kangra district using physical and socio-economic indicators

  • Published:
Spatial Information Research Aims and scope Submit manuscript

Abstract

Land degradation is a major problem in the fragile ecosystem of the Himalayan region. The steep slope with low forest cover and increasing human interference are the major factors of land degradation. Therefore, identification of severe degradation prone areas is necessary for implementing conservation strategies to retard the present rate of degradation processes. The aim of this study is to assess the vulnerable land degradation areas based on Space Application Centre (SAC/ISRO) guidelines and MEDALUS model. Indicators used to calculate the degradation vulnerability are geology, slope, aspect, soil type, rainfall, temperature, land use/land cover, population density, non-worker population and illiteracy. The results reveal that the areas with higher rainfall, less forest cover and large population are highly vulnerable to degradation in spite of moderate slope. The degradation vulnerability index values have been classified into five land degradation categories. The Pong dam is a large water body where the land degradation is nil. The low, moderate, high and very high land degradation categories account for 19.01, 22.79, 31.49 and 17.37% area of the district, respectively.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. United Nation Environment Programme. (1992). World atlas of desertification (pp. 69). London: Edward Arnold. ISBN NO: 0340555122.

  2. Svensson, L. (2005). Socio-economic indicators for causes and consequences of land degradation. Land degradation assessment in drylands (LADA). Technical paper, FAO, Rome. http://www.fao.org/nr/lada/index.php?option=com_docman&task=search_result&Itemid=165&lang=en. Accessed 11 October 2015.

  3. Kosmas, C., Kirkby, M., & Geeson, N. (1999). The Medalus project Mediterranean desertification and land use- Manual on key indicators of desertification and mapping environmentally sensitive areas to desertification. European environment and climate research program—Theme: Land resources and the threat of desertification and soil erosion in Europe (pp. 88), (Project ENV4 CT 95 0119). https://www.kcl.ac.uk/projects/desertlinks/downloads/publicdownloads/ESA%20Manual.pdf. Accessed 18 October 2015.

  4. Singh, H., Sharma, M. C. (2005). Desertification status mapping of Chharapchhu watershed Lahaul and Spiti district, Himachal Pradesh using IRS satellite data. Unpublished scientific report prepared by Jawaharlal Nehru University and Space Application Centre (JNU-SAC) sponsored by Ministry of Environment and Forest, New Delhi.

  5. DeLong, C., Cruse, R., & Wiener, J. (2015). The soil degradation paradox: Compromising our resources when we need them the most. Sustainability, 7(1), 866–879.

    Article  Google Scholar 

  6. Blaikie, P., & BrookWeld, H. C. (Eds.). (1987). Land degradation and society (p. 296). London: Methuen.

    Google Scholar 

  7. Dow, K. (1992). Exploring differences in our common future(s): The meaning of vulnerability to global environmental change. Geoforum, 23(3), 417–436.

    Article  Google Scholar 

  8. Cutter, S. L. (1996). Vulnerability to environmental Hazards. Progress in Human Geography, 20(4), 529–539.

    Article  Google Scholar 

  9. Cutter, S. L. (2001). American hazardscapes: The regionalization of hazards and disaster. Washington, D.C.: Joseph Henry Press.

    Google Scholar 

  10. Duraiappah, A. K. (1998). Poverty and environmental degradation: A review and analysis of the nexus. World Development, 26(12), 2169–2179.

    Article  Google Scholar 

  11. Jolly, C. L. (1994). Four theories of population change and the environment. Population and Environment, 16(1), 61–90.

    Article  Google Scholar 

  12. Boserup, E. (1975). The impact of population growth on agricultural output. The Quarterly Journal of Economics, 89(2), 257–270.

    Article  Google Scholar 

  13. Jain, S. K., Kumar, S., & Varghese, J. (2001). Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resources Management, 15(1), 41–54.

    Article  Google Scholar 

  14. Singh, O., Sarangi, A., & Sharma, M. C. (2008). Hypsometric integral estimation methods and its relevance on erosion status of North-Western Lesser Himalayan watersheds. Water Resources Management, 22(11), 1545–1560.

    Article  Google Scholar 

  15. Rashid, M., Lone, M. A., & Romshoo, S. A. (2011). Geospatial tools for assessing land degradation in Budgam district, Kashmir Himalaya, India. Journal of Earth System Science, 120(3), 423–433.

    Article  Google Scholar 

  16. Mandal, D., & Sharda, V. N. (2011). Appraisal of soil erosion risk in the eastern Himalayan region of India for soil conservation planning. Land Degradation and Development, 24(5), 430–437.

    Google Scholar 

  17. Rawat, J. S., Joshi, R. C., & Mesia, M. (2013). Estimation of erosivity index and soil loss under different land uses in the tropical foothills of Eastern Himalaya (India). Tropical Ecology, 54(1), 47–58.

    Google Scholar 

  18. Saha, D., & Kukal, S. S. (2013). Soil structural stability and water retention characteristics under different land uses of degraded lower Himalayas of north-west India. Land Degradation and Development, 26(3), 263–271.

    Article  Google Scholar 

  19. Saini, S. S., Jangra, R., & Kaushik, S. P. (2015). Vulnerability assessment of soil erosion using geospatial techniques a pilot study of upper catchment of Markanda River. International Journal of Advancement in Remote Sensing, GIS and Geography, 2(1), 9–21.

    Google Scholar 

  20. Kayastha, S. L. (1958). Precipitation characteristics of the Himalayan Beas Basin. The Journal of Scientific Research Banaras Hindu University, 8(2), 183–189.

    Google Scholar 

  21. Singh, R. L. (1971). India: A regional geography (p. 992). Varanasi: National Geographical Society of India.

    Google Scholar 

  22. Census of India. (2006). Administrative atlas- Himachal Pradesh (census of India 2001). New Delhi: Office of the registrar general census commissioner.

    Google Scholar 

  23. Census of India. (2012). Administrative atlas- Himachal Pradesh (census of India 20011). New Delhi: Office of the registrar general census commissioner.

    Google Scholar 

  24. Census of India. (1988). Himachal Pradesh: Regional divisions of India, a cartographic analysis atlas. New Delhi: Office of the Registrar General and Census Commissioner.

    Google Scholar 

  25. Bhagat, R. M., Kalia, V., Sood, C., Mool, P. K., & Bajracharya, S. R. (2004). Inventory of glaciers and glacial lakes and the identification of potential glacial lake outburst floods (GLOFs) affected by global warming in the mountains of Himalayan region. Project report. Collaborative work of ICIMOD, CSKHPAU, APN, START, & UNEP. http://14.139.224.135/myapp/cgrt/index_files/Project_Reports_Completed/CGRT4.Misc.595-15-HP%20Himalya%20Inventory%20of%20Glaciers(GLOF)—03-06.pdf. Accessed 12 September 2015.

  26. India Meteorological Department. (2010). Climatological tables (6th ed.). New Delhi: The director general of meteorology.

    Google Scholar 

  27. District Census Handbook, Kangra. (2011). Village and town directory. Series-03, Part VIII-A http://www.censusindia.gov.in/2011census/dchb/0202_PART_B_DCHB_KANGRA.pdf. Accessed 26 February 2016.

  28. Space application centre (SAC), Ahmedabad. (2013). Desertification status mapping of India, second cycle. Unpublished workplan. A joint programme of Ministry of Environment and Forests (MoEF) and Department of Space (DOS).

  29. Roxo, M. J., Mourao, J. M., Rodrigues. L., & Casimiro, P. C. (1999). The Alentejo region (Metrola municipality, Portugal). In C. Kosmas, M. Kirkby & N. Geeson (Eds.), The Medalus project Mediterranean desertification and land use- Manual on key indicators of desertification and mapping environmentally sensitive areas to desertification (pp. 80–87). Brussels: European Commission. https://www.kcl.ac.uk/projects/desertlinks/downloads/publicdownloads/ESA%20Manual.pdf. Accessed 18 October 2015.

  30. USGS. (2015). Landsat 8 (L8) data users handbook (version 1.0). https://www.greenpolicy360.net/mw/images/Landsat8DataUsersHandbook.pdf. Accessed 16 November 2016.

  31. Jia, K., Wei, X., Gu, X., Yao, Y., Xie, X., & Li, B. (2014). Land cover classification using Landsat 8 operational land imager data in Beijing, China. Geocarto International, 29(8), 941–951.

    Article  Google Scholar 

  32. Xu, H. (2007). Extraction of urban built-up land features from Landsat imagery using a thematic- oriented index combination technique. Photogrammetric Engineering and Remote Sensing, 73(12), 1381–1391.

    Article  Google Scholar 

  33. Bahreini, F., & Pahlavanravi, A. (2013). Assess and mapping the environmental sensitivity to desertification (A case study in boushehr province, southwest Iran). International Journal of Agriculture and Crop Sciences, 5(18), 2172–2183.

    Google Scholar 

  34. Oliver, M. A., & Webster, R. (2007). Kriging: A method of interpolation for geographical information systems. International Journal of Geographic Information Systems. doi:10.1080/02693799008941549.

    Google Scholar 

  35. Thornes, J. B. (1995). Mediterranean desertification and the vegetation cover. In R. Fantechi, D. Peter, P. Balabanis, & J. L. Rubio (Eds.), EUR 15415 desertification in a European context: Physical and socio-economic aspects (pp. 169–194). Brussels: Office for Official Publications of the European Communities.

    Google Scholar 

  36. Sciortino, M., Colonna, N., Ferrara, V., Grauso, S., Iannetta, M., & Svalduz, A. (2000). La lotta alla desertificazione in Italia e nel bacino Del Mediterraneo. Energia, Ambiente e Innovazione, 2, 29–40.

    Google Scholar 

  37. Thornes, J. B. (1988). Competitive vegetation- erosion model for Mediterranean countries. In R. P. C. Morgan & R. J. Rickson (Eds.), Agriculture, erosion assessment and modelling. Comm. Eur. Com. EUR 10860 EN.

  38. Zachar, D. (1982). Soil erosion: Developments in soil science 10 (p. 547). Amsterdam: Elsevier Scientific.

    Google Scholar 

  39. Fox, D. M., & Rorke, B. B. (2000). The relationship of soil loss by interrill erosion to slope gradient. Catena, 38(3), 211–222.

    Article  Google Scholar 

  40. Mandal, D., Sharda, V. N., & Tripathi, K. P. (2010). Relative efficacy of two biophysical approaches to assess soil loss tolerance for Doon Valley soils of India. Journal of Soil and Water Conservation, 65(1), 42–49.

    Article  Google Scholar 

  41. Grepperud, S. (1996). Population pressure and land degradation: The case of Ethiopia. Journal of Environmental Economics and Management, 30(1), 18–33.

    Article  Google Scholar 

  42. World Bank. (1990). World Development Report 1990: Poverty. New York: Oxford University Press. © World Bank. https://openknowledge.worldbank.org/handle/10986/5973 License: CC BY 3.0 IGO. Accessed 07 January 2016.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Satya Prakash.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Prakash, S., Sharma, M.C., Kumar, R. et al. Mapping and assessing land degradation vulnerability in Kangra district using physical and socio-economic indicators. Spat. Inf. Res. 24, 733–744 (2016). https://doi.org/10.1007/s41324-016-0071-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41324-016-0071-5

Keywords

Navigation