Skip to main content

Assessing land transformation and associated degradation of the west part of Ganga River Basin using forest cover land use mapping and residual trend analysis

Abstract

The west part of Ganga River Basin (WGRB) has experienced continuous land transformation since the Indus Valley Civilisation shifted from the Indus basin to the Ganga basin. Particularly in the last few decades the land transformation has increased many-folds due to the changing climate and rapid increase in population. In this paper, we assessed land transformation and associated degradation in the WGRB based on the forest cover land use (FCLU) mapping and residual trend analysis (RTA). The FCLU maps for 1975 and 2010 were generated using 216 Landsat satellite images and validated using 1509 ground points. We mapped 29 forest and 18 non-forest types and estimated a total loss of 5571 km2 forest cover and expansion in settlement areas (5396 km2). Other major changes mapped include a decrease in wetlands and water bodies, while an increase in agriculture and barren lands with an overall mapping accuracy of 85.3% (kappa, 0.82) and 88.43% (kappa, 0.84) for 1975 and 2010, respectively. We also performed the RTA analysis using GIMMS-NDVI3g to identify areas of significant negative vegetative photosynthetic change as an indicator for land degradation. All the RTA models showed monotonic nature of the residual trends and resulted as moderately positive but highly significant (P<0.001). Land degradation in the form of barren land accompanied by a decline in vegetation quality and coverage was found prominent in the basin with a possibility of an accelerated rate of land degradation in future due to the rapid loss of permanent forest cover.

This is a preview of subscription content, access via your institution.

References

  • Ali M, Joshi P K, Pande S, et al. 2000. Legumes in the Indo-Gangetic Plain of India. In: Johansen C, Duxbury J M, Virmani S M, et al. Legumes in rice and wheat cropping systems of the Indo-Gangetic Plain -constraints and opportunities. International Crops Research Institute for the Semi-Arid Tropics. New York: Cornell University Press, 35–70.

    Google Scholar 

  • Bai Z G, Dent D L, Olsson L, et al. 2008. Proxy global assessment of land degradation. Soil Use and Management, 24(3): 223–234.

    Article  Google Scholar 

  • Bajocco S, de Angelis A, Perini A, et al. 2012. The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study. Environmental Management, 49(5): 980–989.

    Article  Google Scholar 

  • Behera M D, Chitale V S, Shaw A, et al. 2012. Wetland monitoring, serving as an index of land use change-a study in Samaspur Wetlands, Uttar Pradesh, India. Journal of the Indian Society of Remote Sensing, 40(2): 287–297.

    Article  Google Scholar 

  • Behera M D, Patidar N, Chitale V S, et al. 2014. Increase in agricultural patch contiguity over the past three decades in Ganga River Basin, India. Current Science, 107(3): 502–511.

    Google Scholar 

  • Census India. 2011. The Office of the Registrar General & Census Commissioner, India Online access. [2016-11-22]. www.censusindia.gov.in.

    Google Scholar 

  • Dardel C, Kergoat L, Hiernaux P, et al. 2014. Rain-Use-Efficiency: What it tells us about the conflicting Sahel greening and Sahelian paradox. Remote Sensing, 6: 3446–3474.

    Article  Google Scholar 

  • Dregne H E. 1977. Desertification of arid lands. Economic Geography, 53(4): 322–331.

    Article  Google Scholar 

  • Dubey S K, Pranuthi G, Tripathi S K. 2012. Relationship between NDVI and rainfall relationship over India. International Journal of Water Resources and Environmental Sciences, 1(4): 102–108.

    Google Scholar 

  • Eckert S, Hüsler F, Liniger H, et al. 2015. Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia. Journal of Arid Environments, 113: 16–28.

    Article  Google Scholar 

  • EODC. 2015. ESA Climate Change Initiative Phase II Soil Moisture: Soil Moisture ECV Product User Guide (Ver. 10), D330. [2016-08-07]. www.esa-sst-cci.org/PUG/documents.

    Google Scholar 

  • Evans J, Geerken R. 2004. Discrimination between climate and human-induced dryland degradation. Journal of Arid Environments, 57(4): 535–554.

    Article  Google Scholar 

  • Fensholt R, Langanke T, Rasmussen K, et al. 2012. Greenness in semi-arid areas across the globe 1981–2007 -an Earth Observing Satellite based analysis of trends and drivers. Remote Sensing of Environment, 121: 144–158.

    Article  Google Scholar 

  • Gabriels D, Cornelis W M. 2009. Human-induced land degradation. In: Land Use, Land Cover and Soil Sciences-Volume III: Land Use Planning, Encyclopaedia of life support system [2016-06-22]. http://www.eolss.net/sample-chapters/c12/E1-05-03-05.pdf.

    Google Scholar 

  • Gupta R K, Naresh R K, Hobbs P R, et al. 2003. Sustainability of post-green revolution agriculture: the rice–wheat cropping systems of the Indo-Gangetic Plains and China. In: Ladha J K, Hill J E, Duxbury J M, et al., Improving the Productivity and Sustainability of Rice–Wheat Systems: Issues and Impacts. Madison: American Society of Agronomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc., 1–25.

  • Gupta A K, Tyagi P, Sehgal V K. 2011. Drought disaster challenges and mitigation in India: strategic appraisal. Current Science, 100(12): 1795–1806.

    Google Scholar 

  • Helldén U, Tottrup C. 2008. Regional desertification: a global synthesis. Global and Planetary Change, 64(3–4): 169–176.

    Article  Google Scholar 

  • Helsel D R, Hirsch R M. 2002. Statistical methods in water resources. In: Techniques of Water Resources Investigations of the United States Geological Survey, Book 4, Hydrologic Analysis and Interpretation, Chapter A3. [2002-09-22] https://pubs.usgs.gov/twri/twri4a3/pdf/twri4a3-new.pdf.

    Google Scholar 

  • Higginbottom T P, Symeonakis E. 2014. Assessing land degradation and desertification using vegetation index data: current frameworks and future directions. Remote Sensing, 6(10): 9552–9575.

    Article  Google Scholar 

  • Hill J, Stellmes M, Udelhoven T, et al. 2008. Mediterranean desertification and land degradation: mapping related land use change syndromes based on satellite observations. Global and Planetary Change, 64(3–4): 146–157.

    Article  Google Scholar 

  • Holben B N. 1986. Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing, 7(11): 1417–1434.

    Article  Google Scholar 

  • Ibrahim Y Z, Balzter H, Kaduk J, et al. 2015. Land degradation assessment using residual trend analysis of GIMMS NDVI3g, soil moisture and rainfall in Sub-Saharan West Africa from 1982 to 2012. Remote Sensing, 7(5): 5471–5494.

    Article  Google Scholar 

  • Kumar T L, Rao K K. 2013. Studies on spatial pattern of NDVI over India and its relationship with rainfall, air temperature, soil moisture adequacy and ENSO Geofizika, 30: 1–19. [2016-07-22]. http://hrcaksrcehr/indexphp/.

    Google Scholar 

  • Lamb D. 2011. Forest and land degradation in the Asia-Pacific region. In: Regreening the Bare Hills. World Forests, Vol. 8. Springer, Dordrecht, 61.

    Book  Google Scholar 

  • Le Q B, Nkonya E, Mirzabaev A. 2016. Biomass productivity-based mapping of global land degradation hotspots. In: Nkonya E, Mirzabaev A, von Braun J. Economics of Land Degradation and Improvement–A Global Assessment for Sustainable Development. Cham: Springer, 55–84.

    Chapter  Google Scholar 

  • Leemans R, Zuidema G. 1995. Evaluating changes in land cover and their importance for global change. Trends in Ecology & Evolution, 10(2): 76–81.

    Article  Google Scholar 

  • Li X B, Li R H, Li G Q, et al. 2016. Human-induced vegetation degradation and response of soil nitrogen storage in typical steppes in Inner Mongolia, China. Journal of Arid Environments, 124: 80–90.

    Article  Google Scholar 

  • Matin S, Chitale V S, Behera M D, et al. 2012. Fauna data integration and species distribution modelling as two major advantages of geoinformatics-based phytobiodiversity study in today's fast changing climate. Biodiversity and Conservation, 21(5): 1229–1250.

    Article  Google Scholar 

  • Matin S, Behera M D. 2017. Alarming rise in aridity in the Ganga river basin, India, in past 3.5 decades. Current Science, 112(2): 229–230.

    Google Scholar 

  • Mbow C, Brandt M, Ouedraogo I, et al. 2015. What four decades of earth observation tell us about land degradation in the Sahel? Remote Sensing, 7: 4048–4067.

    Article  Google Scholar 

  • NBSS and LUP (National Bureau of Soil Survey and Land Use Planning). 2005. Annual Report 2005. Nagpur: NBSS and LUP, 2.

    Google Scholar 

  • Reynolds J F, Smith D M S, Lambin E F, et al. 2007. Global desertification: building a science for dryland development. Science, 316(5826): 847–851.

    Article  Google Scholar 

  • Shiva V. 1991. The Violence of the Green Revolution: Third World Agriculture, Ecology, and Politics. London: Zed Books, 21.

    Google Scholar 

  • Sklenicka P. 2016. Classification of farmland ownership fragmentation as a cause of land degradation: A review on typology, consequences, and remedies. Land Use Policy, 57: 694–701.

    Article  Google Scholar 

  • Suhag R. 2016. Overview of ground water in India. In: PRS Legislative Research ("PRS”) standing committee report on Water Resources examined 10 year report. New Delhi, India. [2017-04-02]. https://www.prsindia.org/theprsblog/status-groundwater-extraction-exceeds-recharge.

    Google Scholar 

  • Symeonakis E, Calvo-Cases A, Arnau-Rosalen E. 2007. Land use change and land degradation in southeastern Mediterranean Spain. Environmental Management, 40(1): 80–94.

    Article  Google Scholar 

  • UNCCD. 1994. Elaboration of an international convention to combat desertification in countries experiencing serious drought and/or desertification, particularly in Africa. [2016-07-19]. http://wwwunccdint/convention/menu.php.

    Google Scholar 

  • Wang J, Rich P M, Price K P. 2003. Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. International Journal of Remote Sensing, 24(11): 2345–2364.

    Article  Google Scholar 

  • Wessels K J, Prince S D, Malherbe J, et al. 2007. Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. Journal of Arid Environments, 68(2): 271–297.

    Article  Google Scholar 

  • Xu L, Myneni R B, Chapin III, et al. 2013. Temperature and vegetation seasonality diminishment over northern lands. Nature Climate Change, 3(3): 581–586.

    Article  Google Scholar 

  • Yan K, Park T, Yan G, et al. 2016. Evaluation of MODIS LAI/FPAR product collection 6. Part 1: Consistency and improvements. Remote Sensing, 8(5): 359.

    Google Scholar 

  • Zhang Y, Xiao X, Wu X, et al. 2017. A global moderate resolution dataset of gross primary production of vegetation for 2000–2016. Scientific Data, 4: 170165.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shafique Matin.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Matin, S., Ghosh, S. & Behera, M.D. Assessing land transformation and associated degradation of the west part of Ganga River Basin using forest cover land use mapping and residual trend analysis. J. Arid Land 11, 29–42 (2019). https://doi.org/10.1007/s40333-018-0106-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40333-018-0106-y

Keywords

  • land degradation
  • remote sensing
  • NDVI
  • GIMMS
  • Ganga River Basin