1887
Volume 2013, Issue 1
  • EISSN: 2223-506X

Abstract

The objective of this study is to evaluate sand encroached degradation in arid-land, with a predominantly agricultural ecosystem, using geospatial technologies. The study primarily involves the assessment of land degradation severity, severity change dynamics and temporal land-use change patterns, such as growth or shrinkage. Land use/land cover (LULC) change dynamics were analyzed for eight featured classes, derived using a K-means supervised classification method. Overall accuracy and kappa statistics obtained were 91.68% and 0.904 for the year 2001, while 90.85% and 0.896 for year the 2006. The analysis revealed that change dynamic patterns were highest for sand-affected areas and built-up classes, showing positive trend and an overall change of 8.92% and 5.34%, respectively. Degradation severity change dynamics and change patterns clearly showed an increasing trend in highly severe degradation areas (dynamic change 5.55 km2/change pattern 0.093%), followed by severe degradation (dynamic change 31.22 km2/change pattern 0.52%). However, the maximum change was observed in moderately severe zones.

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2014-07-01
2020-10-25
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References

  1. Koch M. Geological controls of land degradation as detected by remote sensing: A case study in Los Monegros, north-east Spain. Int J Remote Sensing. 2000; 21:3:457473.
    [Google Scholar]
  2. Das DC. Problem of soil erosion and land degradation in India. Proceedings of the National Seminar on Soil Conservation and Watershed Management. Indian Association of Soil and Water Conservationists, New Delhi, India. 1985.
  3. Gobin A, Govers G, Jones R, Kirkby M, Kosmas C. Assessment and reporting on soil erosion. European Environment Agency, Technical Report. 2003; 94::103.
    [Google Scholar]
  4. Al-Awadhi JM, Al-Helal A, Al-Enezi A. Sand drift potential in the desert of Kuwait. J Arid Environ. 2005; 63:2:425438.
    [Google Scholar]
  5. Yao ZY, Wang T, Han ZW, Zhang WM, Zhao AG. Migration of sand dunes on the northern Alxa Plateau, Inner Mongolia, China. Journal of Arid Environments. 2007; 70:1:8093.
    [Google Scholar]
  6. Helldén U. Desertification monitoring: is the desert encroaching? Desertif Control Bull. 1988; 17::812.
    [Google Scholar]
  7. Dregne HE. Desertification of Arid Lands. Springer-Verlag 1986; 434.
    [Google Scholar]
  8. Tsoar H, Karnieli A. What determines the spectral reflectance of the Negev-Sinai sand dunes. Int J Remote Sensing. 1996; 17:3:513525.
    [Google Scholar]
  9. Ho P, Azadi H. Rangeland degradation in North China: perceptions of pastoralists. Environ Res. 2010; 110:3:302307.
    [Google Scholar]
  10. Azadi H, Ho P, Hasfiati L. Agricultural land conversion drivers: a comparison between less developed, developing and developed countries. Land Degrad Dev. 2011; 22:6:596604.
    [Google Scholar]
  11. Ram B, Kolarkar AS. Remote sensing application in monitoring land-use changes in arid Rajasthan. Int J Remote Sensing. 1993; 14:17:31913200.
    [Google Scholar]
  12. Ram B, Chauhan JS. Application of remote sensing and GIS to assess land use changes in Jhunjhunun district of arid Rajasthan. J Indian Soc Remote Sensing. 2009; 37:4:671680.
    [Google Scholar]
  13. Subramaniam AR, Prasada Rao GSLHV. Climatic study of water balance, aridity and droughts in Rajasthan State. Ann Arid Zone. 1980; 19:4:371377.
    [Google Scholar]
  14. Ram B. Recent changes in land-use in an arid-environment. A case study of Siwana region. Rajasthan, Jodhpur University, Jodhpur, India. Doctoral thesis, 1988.
  15. Kumar M, Goossens E, Goossens R. Assessment of sand dune change detection in Rajasthan (Thar) Desert, India. Int J Remote Sensing. 1993; 14:9:16891703.
    [Google Scholar]
  16. Pant GB, Hingane LS. Climatic changes in and around the Rajasthan desert during the 20th century. J Climatol. 1988; 8:4:391401.
    [Google Scholar]
  17. Fredriksen P. Satellite based assessment and monitoring of land degradation in semi-arid tropical Africa – aspects of the soil/vegetation complex. EARseL Advan Remote Sensing. 1993; 2:3-XI:102110.
    [Google Scholar]
  18. Raina P, Joshi DC, Kolarkar AS. Land degradation mapping by remote sensing in the arid region of India. Soil Use Manage. 1991; 7:1:4751.
    [Google Scholar]
  19. Gao J, Liu Y. Mapping of land degradation from space: a comparative study of Landsat ETM+ and ASTER data. International Journal of Remote Sensing. 2008; 29:14:40294043.
    [Google Scholar]
  20. Ramsey MS. Global Desert Monitoring With ASTER; Research Projects. : Image Visualization and Ifrared Spectroscopy (IVIS) Laboratory, University of Pittsburg 2003.
    [Google Scholar]
  21. Sharma L, Pandey PC, Nathawat MS. Assessment of land consumption rate with urban dynamics change using geospatial techniques. J Land Use Sci. 2012; 7:2:135148.
    [Google Scholar]
  22. Srivastava PK, Gupta M, Mukherjee S. Mapping spatial distribution of pollutants in groundwater of a tropical area of India using remote sensing and GIS. Appl Geomat. 2012; 4:1:2132.
    [Google Scholar]
  23. Srivastava PK, Han D, Gupta M, Mukherjee S. Integrated framework for monitoring groundwater pollution using a geographical information system and multivariate analysis. Hydrol Sci J. 2012; 57:7:14531472.
    [Google Scholar]
  24. Srivastava PK, Han D, Rico-Ramirez MA, Bray M, Islam T. Selection of classification techniques for land use/land cover change investigation. Advan Space Res. 2012; 50:9:12501265.
    [Google Scholar]
  25. Yang X, Lo CP. Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area. Int J Remote Sensing. 2002; 23:9:17751798.
    [Google Scholar]
  26. Srivastava PK, Mukherjee S, Gupta M. Impact of urbanization on land use/land cover change using remote sensing and GIS: a case study. Int J Ecol Econ Stat. 2010; 18:S10:106117.
    [Google Scholar]
  27. Gupta M, Srivastava PK. Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India. Water Int. 2010; 35:2:233245.
    [Google Scholar]
  28. Srivastava PK, Mukherjee S, Gupta M, Singh SK. Characterizing monsoonal variation on water quality index of river Mahi in India using geographical information system. Water Qual Expo Health. 2011; 2:3-4:193203.
    [Google Scholar]
  29. Elhadi EM, Zomrawi N, Guangdao H. Landscape Change and Sandy Desertification Monitoring and Assessment. American Journal of Environmental Sciences. 2009; 5:5:633638.
    [Google Scholar]
  30. Chavez PS, MacKinnon DJ. Automatic change detection of vegetation changes in the Southwestern United States using remotely sensed images. Photogramm Eng Remote Sensing. 1994; 60:5:571583.
    [Google Scholar]
  31. Pilon PG, Howarth PJ, Bullock RA, Adeniyi PO. An enhanced classification approach to change detection in semi-arid environment. Photogramm Eng Remote Sensing. 1988; 45:12:17091716.
    [Google Scholar]
  32. Karnieli A. Development and implementation of spectral crust index over dune sands. Int J Remote Sensing. 1997; 18:6:12071220.
    [Google Scholar]
  33. Dong Z, Wang X, Chen G. Monitoring sand dune advance in the Taklimakan Desert. Geomorphology. 2000; 35:3-4:219231.
    [Google Scholar]
  34. Story M, Congalton R. Accuracy assessment: a user's perspective. Photogramm Eng Remote Sensing. 1986; 52:3:397399.
    [Google Scholar]
  35. Congalton RG. A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data. Photogramm Eng Remote Sensing. 1988; 54:5:593600.
    [Google Scholar]
  36. Bishop Y, Fienberg S, Holland P. Discrete Multivariate Analysis-Theory and Practice. Cambridge, MA: MIT Press 1975: p. 575.
    [Google Scholar]
  37. Frantzova A. Remote Sensing, GIS and Disaster Management. Third International Conference on Cartography and GIS. Nessebar, Bulgaria, 2010.
  38. Jackson RD, Huete AR. Interpreting vegetation indices. Preventive Veterinary Medicine. 1991; 11:3-4:185200.
    [Google Scholar]
  39. Townshend JRG, Justice CO. Analysis of the dynamics of African vegetation using the normalized difference vegetation index. Int J Remote Sensing. 1986; 7:11:14351445.
    [Google Scholar]
  40. Thakur JK, Srivastava PK, Singh SK, Vekerdy Z. Ecological monitoring of wetlands in semi-arid region of Konya closed Basin, Turkey. Reg Environ Change. 2012; 12:1:133144.
    [Google Scholar]
  41. Xiao J, Shen Y, Tateishi R, Bayaer W. Development of topsoil grain size index for monitoring desertification in arid land using remote sensing. Int J Remote Sensing. 2006; 27:12:24112422.
    [Google Scholar]
  42. Fadhil AH. Land degradation detection using Geo-information technology for some sites in Iraq. J Al-Nahrain Univ. 2009; 12:3:94108.
    [Google Scholar]
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