Spatial modeling and validation of forest cover change in Kanakapura region using GEOMOD

Article

Abstract

Deforestation is recognized as one of the most significant components in LULCC and global changes scenario. It is imperative to assess its trend and the rate at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. Present study was taken up in Kanakapura and surrounding areas located on the fringes of Western Ghats biodiversity hot-spots. Temporal satellite data from Landsat was classified into forest cover maps. Drivers of forest cover changes such as roads and settlements were used in order to create predicted map of the region using GEOMOD tool in Idrisi Andes. The predicted map was then validated using actual land cover map of same year prepared from Landsat data. The validated map was found to be 84.26 % accurate. The validation was also tested using ROC approach which was found to be 0.614. The model was then further extended to predict forest cover losses for year 2015. The results highlight ongoing deforestation in the areas adjoining Western Ghats. It also presents an application of the tool and the validation methods which can be used in predictive modeling related studies.

Keywords

Deforestation Predictive modeling GEOMOD Validation Kanakapura 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agarwal C, Green MG, Grove JM, Evans TP and Schweik CM (2002) A Review and Assessment of Land-Use Change Models. Dynamics of Space, Time, and Human Choice CIPEC Collaborative Report Series No. 1Google Scholar
  2. Armenteras D, Gast F and Villareal H (2003) Andean forest fragmentation and the representativeness of protected natural areas in the eastern Andes, Colombia. Biological Conservation 13(2):245–256CrossRefGoogle Scholar
  3. Baker WL (1989) A review of models in landscape change. Landscape Ecology 2(2):11–133CrossRefGoogle Scholar
  4. Behera MD, Kushwaha SPS and Roy PS (2002) High plant endemism in an Indian hotspot — eastern Himalaya. Biodiversity and Conservation 11(4):669–682CrossRefGoogle Scholar
  5. Binutha R (2007) Patterns of fuel-wood use for subsistence in the Dry forested landscapes of Kankapura Region. Project Report at ATREE, BangaloreGoogle Scholar
  6. Fearnside MP (2001) Saving tropical forests as a global warming countermeasure: an issue that divides the environmental movement. Ecological Economics 39:167–184CrossRefGoogle Scholar
  7. Giriraj A, Irfan-Ullah M, Murthy MSR and Beierkuhnlein C (2008) Modeling Spatial and Temporal Forest Cover Change Patterns (1973–2020): A Case Study from South Western Ghats (India) Sensors 8:6132–6153CrossRefGoogle Scholar
  8. Gupta S, Singh S, Agarwal S and Roy PS (2006). Degradation of Tropical evergreen forests in Makokchung Nagaland, India — a geospatial approach. International Journ Ecology and Environemntal Sciences. 32(4): 345–356.Google Scholar
  9. Hall CAS, Tian H, Qi Y, Pontius G and Cornell J (1995) Modelling spatial and temporal patterns of tropical land use change. Journal of Biogeography 22(4/5):753–757CrossRefGoogle Scholar
  10. Jha CS, Dutt CBS, and Bawa KS (2000) Deforestation and land use changes in Western Ghats, India. Current Science 79(2):231Google Scholar
  11. Lambin EF (1994) Modelling Deforestation Processes: A review. European Commission, LuxemburgGoogle Scholar
  12. Lambin EF, Turner BL, Helmut J, Geist SB, Agbola SB, Arild A, Bruce JW, Coomes OT, Dirzo R, Fischer G, Folke C, George PS, Homewood K, Imbernon J, Leemans R, Li X, Moran EF, Mortimore M, Ramakrishnan PS, Richards JF, Skanes H, Steffen W, Stone GD, Svedin U, Veldkamp T, Vogel A and Xu CJ (2001) The causes of land-use and landcover change: moving beyond the myths. Global Environmental Change 11:261–269CrossRefGoogle Scholar
  13. Lele N and Joshi PK (2009) Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999. Environment Monitoring and Assessment 156(1):159–170CrossRefGoogle Scholar
  14. Menon S and Bawa KS (1998) Deforestation in the tropics: reconciling disparities in estimates for India. Ambio 27(7):576–577Google Scholar
  15. Pandit MK, Sodhi NS, Lian PK, Bhaskar A and Brook BW (2007) Unreported yet massive deforestation driving loss of endemic biodiversity in Indian Himalaya. Biodiversity Conservation 16:153–163CrossRefGoogle Scholar
  16. Peterson TA, Ortega MA, Bartley J, Sanchez V, Soberon J, Buddemeier RH and Stockwell DRB (2001) Future projections for Mexican faunas under global climate change scenarios. Nature 416:626–629CrossRefGoogle Scholar
  17. Petit CC and Lambin EF (2002) Long-term land-cover changes in Belgian Ardennes (1775–1929): Model based reconstruction vs. historical maps. Global Change Biology 8:616–630CrossRefGoogle Scholar
  18. Pontius RG Jr (2000) Quantifying error versus location error in comparison of categorical maps. Photogrammetric Engineering and Remote Sensing 66(8): 1011–1016Google Scholar
  19. Pontius RG Jr and Schneider LC (2001) Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA. Agriculture, Ecosystems and Environment. 85(1–3):239–248CrossRefGoogle Scholar
  20. Pontius RG Jr (2002) Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions Photogrammetric Engineering and Remote Sensing 68(10): 1041–1049Google Scholar
  21. Pontius RG Jr and Malanson J (2005) Comparison of the structure and accuracy of two land change models. International Journal of Geographical Information Science 19(2): 243–265CrossRefGoogle Scholar
  22. Pontius RG Jr and Pacheco P (2004) Calibration and validation of a model of forest disturbance in the Western Ghats, India 1920–1990. Geo Journal 61:325–334Google Scholar
  23. Pontius RG Jr and Spencer J (2005) Uncertainty in extrapolations of predictive land change models. Environ. Plan. B 32:211–230CrossRefGoogle Scholar
  24. Pontius RG Jr and Batchu K (2003) Using the relative operating characteristic to quantify certainty in prediction of location of land cover change in India. Trans GIS 7: 467–484CrossRefGoogle Scholar
  25. Pontius RG Jr and Schneider L (2001) Land-use change model validation by a ROC method for the Ipswich watershed, Massachusetts, USA. Agric Ecosystem Environ 85: 239–248CrossRefGoogle Scholar
  26. Pontius RG Jr, Agrawal A and Huffaker D (2003) Estimating the uncertainty of land-cover extrapolations while constructing a raster map from tabular data. J Geogr Syst 5:253–273CrossRefGoogle Scholar
  27. Rudel TK (2007) Changing agents of deforestation: from state-initiated to enterprise driven process, 1970–2000. Land Use Policy. 24(1):35–41CrossRefGoogle Scholar
  28. Silva E and Clarke K (2002) Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems 26:525–552CrossRefGoogle Scholar
  29. Singh TP, S Singh S and Roy PS (2002) Assessing Jhum induced forest loss in Dibang Valley, Arunachal Himalayas — A remote sensing approach. J Indian Soc Remote Sens 31(1): 3–9CrossRefGoogle Scholar
  30. Velázquez A, Elvira D, Isabel R, Jean-François M, Gerardo B, Gustavo R and José-Luis P (2003) Land use-cover change processes in highly biodiverse areas: the case of Oaxaca, Mexico. Global Environmental Change 13(3):175–184CrossRefGoogle Scholar

Copyright information

© Indian Society of Remote Sensing 2010

Authors and Affiliations

  1. 1.Ashoka Trust for Research in Ecology and the Environment (ATREE)Royal Enclave, Srirampura, Jakkur PostBangaloreIndia
  2. 2.Geomatics Solutions Development GroupCentre for Development of Advance Computing (C-DAC)Aundh, PuneIndia

Personalised recommendations