Application of remote sensing technology for land use/land cover change analysis

  • Rajeev Kumar Jaiswal
  • Rajesh Saxena
  • Saumitra Mukherjee


Land use/land cover changes over a period of 30 years were studied using remote sensing technology in a part of Gohparu block, Shahdol district of Madhya Pradesh. Land use/ land cover maps were prepared by visual interpretation of two period remotely sensed data. Post-classification comparison technique was adopted for this purpose. The loss of vegetation cover was estimated to be 22 percent and 14 percent of the land was found to have been tranformed into wasteland between 1967 and 1996. Overall rate of change was found to be 1.8 percent per year during this period.


Remote Sensing Land Cover Change Forest Department Geographic Information System Degraded Forest 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Anon (1992). Macro-level urban information system — A GIS case study for BMR. SAC/ISRO, BMRDA. Project Report No. SAC/RSA/NRIS-URIS/PR-18/March, 1992.Google Scholar
  2. Burns G S and Joyce A T (1982). Evaluation of land cover change detection techniques using Landsat MSS data. Proc. of Remote Sensing with Special Emphasis on Output to Geographic Information Systems in the 1980s., PECORA VII, South Dakota, U.S.A., 1982, pp. 252–257.Google Scholar
  3. Dhinwa P S, Pathak S K, Sastry S V C, Rao M Majumdar K L, Chotani M L, Singh J P and Sinha R L P (1992). Land use change analysis of Bharatpur District using GIS. Photonirvachak: J. Indian Soc. Remote Sensing, 20 (4): 237–250.Google Scholar
  4. Dubey K C (1982). Bharat ki Jangarna 1981, Dist. Shahdol., Madhya Pradesh.Google Scholar
  5. Estes J E, Stow D and Jenson J R (1982) Monitoring land useand land cover changes. Remote Sensing for Resources Management, Soil Conservation Soc. America, pp 100–110.Google Scholar
  6. Jensen, J R (1986). Introductory Digital Image Processing. Prentice Hall, New Jersey. 379 p.Google Scholar
  7. Likens W and Maw K (1982). Hierarchical modelling for image classification. Proc. of Remote Sensing with Special Emphasis on output to Geographic Information Systems in the 1980s., PECORA VII, South Dakota, U.S.A. 1982, pp. 290–300.Google Scholar
  8. Luong P T (1993). The detection of land use/land cover changes using remote sensing and GIS in Vietnam. Asian-Pacific Remote Sensing J., 5 (2): 63–66.Google Scholar
  9. Rubec C D and Thie J (1978). Land use monitoring with Landsat digital data in southwestern Manitoba. Proc. 5th Canadian Symp. on Remote Sensing of Environment, Victoria, British Columbia, 1978, pp 136–149.Google Scholar
  10. Sharma K D, Singh S, Singh N and Bohra D N (1989). Satellite remote sensing for detecting the temporal changes in the grazing lands. Photonirvachak: J. Indian Soc. Remote Sensing, 17 (4): 55–59.CrossRefGoogle Scholar
  11. Singh A (1989). Digital change detection techniques using remotely sensed data. Int. J. Remote Sensing, 10 (6): 989–1003.CrossRefGoogle Scholar
  12. Turner II, B L (1995). Linking the Natural and Social Sciences. The Land use/Cover Change Core Project of IGBP. IGBP Newsletter, No. 22.Google Scholar
  13. Weismiller R A and Momin S J (1977). Change detection in coastal zone environments. Photogramm. Engg. & Remote Sensing, 43 (12): 1533–1539.Google Scholar
  14. Wickware G M and Howarth P J (1981). Change detection in the Peace-Athabasca Delta using digital Landsat data. Remote Sensing Env., 11 (1): 9–25.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Rajeev Kumar Jaiswal
    • 1
  • Rajesh Saxena
    • 2
  • Saumitra Mukherjee
    • 3
  1. 1.Dept. of Space, Antariksh BhavanNNRMS, ISRO HeadquartersBangalore
  2. 2.Remote Sensing Application CentreM.P. Council of Science & TechnologyBhopal
  3. 3.School of Environmental SciencesJawaharlal Nehru UniversityNew Delhi

Personalised recommendations