SPATIAL MODEL FOR DETERMINING RISK AREA OF DEFORESTATION
Keywords:
Deforestation, spatial model, geographic information system, Tung Salaengluang, ThailandAbstract
facing the world, with serious long-term economic and social consequences. In most cases, deforestation is a process that involves competition amongst different land users for scarce resources. To understand the causes of the deforestation, a spatial relation between deforestation areas and landscape attributes was characterized. The study focused on integrating a Geographic Information System (GIS) and a spatial model based on a Composite Mapping Analysis (CMA) technique to express the vulnerability value of risk factors for determining deforestation risk areas in the future. Forest areas have mainly been changed into agricultural land. Nine variables relating to biophysical environment and human activity were used to develop the spatial model for predicting the areas at risk of deforestation. Forest type and distance from agricultural land were the most important variables for deforestation. The human activity factor had much more influence the risk of deforestation than the biophysical environment. Deforestation risk was classified into five classes; very high, high, moderate, low, and very low. The existing forest area in year 2002 was mostly classified as being in the high risk class. The accuracy of the deforestation risk model has been evaluated using the area which coincided with the deforestation risk class and the actual deforested area in the period 2000/2002. This study expands the basic function of GIS technology to map the deforestation risk zone at different severity levels, which could give effective information for developing deforestation prevention in study area.
References
Aondee, P. (2003). Application of GIS for forest resource management associated with community participation in Tung Salaengluang National Park [M.Sc. thesis]. Faculty of Agriculture Natural Resources and Environment, Naresuan University, Phitsanulok, Thailand, p. 167.
Barrow, C.J. (1991). Land degradationdevelopment and breakdown of terrestrial environments. Cambridge University Press, Cambridge, p. 295.
Boonyanuphap, J., Gunarwan Suratmo, F., Nengah, I.S.J., and Amhar, F. (2001). GIS-based method in developing wildfire risk model (case study in SASAMBA, east KALIMANTAN, Indonesia). Tropical Forest Management Journal, 7(2):33-45.
Bryan, B.A. (2000). Modeling the propagation of land clearance using cellular automata and the implications for nature conservation. Proceedings of the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs; September 2-8, 2000; Banff, Alberta, Canada, p. 10.
Cropper, M., Griffiths, C., and Mani, M. (1996). Roads, population pressures and deforestation in Thailand, 1976-1989. Policy Research Working Papers, World Bank 1997.
DeCola, L. (1989). Fractal analysis of a classified Landsat scene. Photogrammatic Engeneering and Remote Sensing, 55(5): 601-610.
Dyhr-Nielsen, M. (1986). Hydrological effect of deforestation in the Chao Phraya basin in Thailand. Proceedings of the International Symposium on Tropical Forest Hydrology and Application; June 11-44, 1986; Chiang Mai, Thailand, p. 12.
Geoghegan, J., Klepeis, P., Ogneva-Himme l - berger, Y., Chowdhury, R.R., Turner II, B.L., and Vance, C. (2000). Spatial modeling of tropical deforestation in the southern Yucatan peninsular region: comparing aggregate and disaggregate
approaches. Proceedings of the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/ EM4): Problems, Prospects and Research Needs; September 2-8, 2000, Banff, Alberta, Canada, p. 13.
Grunberg, W. (2000). Modeling deforestation risk in the Maya Biosphere Reserve, Guatemala, [M.Sc. thesis]. Faculty of the School of Renewable Natural Resources, The University of Arizona, p. 55.
Hepner, F.G. (1999). Geographic Information systems development. The Southwest Center for Environmental Research and Policy (SCERP), Department of Geography, University of Utah, Final Report. Available from: www.scerp.org/ scerp/projects/HW93_21.html. Accessed August 15, 2004.
Islam, K.R., Ahmed, M.R., Bhuiyan, M.K., and Badruddin, A. (2001). Deforestation effects on vegetative regeneration and soil quality in tropical semi-evergreen degraded and protected forests of Bangladesh. Land Degradation & Development, 12:45-56.
Joseph, P.M., and Stephen, J.W. (2000). The application of a cellular automaton model for predicting deforestation: patterns and processes of LULCC in the Ecuadorian, Amazon. Proceedings of the 4th International Conference on Integrating GIS and Environmental
Modeling (GIS/EM4): Problems, Prospects and Research Needs; September 2-8, 2000, Banff, Alberta, Canada, p. 9.
Kaimowitz, D., and Andersen, A. (1997). What can tropical deforestation models tell us? In: CIFOR๛s Research on deforestation, Center for national forestry research. Available from: www.cifor. cgiar.org/docs/_ref/findoutabout/ deforestation/df_ research.htm. Accessed September 20, 2004.
Kemp, K.K. (1996). Easing environmental models into GIS. Proceedings of the 3rd International Conference/Workshop on Integrating GIS and Environmental Modeling CD-ROM; January 21-25, 1996; National Center for Geographic Information and Analysis, Department of Geography, University of California, Santa Barbara. California, USA. Available from: www.ncgia.ucsb.edu/conf/SANTA_ FE_CD-ROM/sf_papers/kemp_karen/ kemp.html. Accessed June 12, 2004.
Mas, J.F., Sosa-Prez, A., Palacio, J.L., and Puig, H. (2000). Modelling deforestation in the region of the Lagoon of T้rminos, South East Mexico. Proceedings of the ASPRS (American Society of Photogrammetry and Remote Sensing) Annual Convention; May 22-26, 2000; Washington D.C., Washington, p. 15.
Mertens, B., and Lambin, E.F. (1997). Spatial modeling of deforestation in southern Cameroon spatial disaggregation of diverse deforestation processes. Applied Geography, 17(2):143-162.
Rahman, M.M., Csaplovics, E., and Pretzsch, J.E. (2000). Assessment of tropical deforestation in social dimension: a study in Chittagong, Bangladesh using remote sensing and geographic information system. Proceedings of the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4): Problems, Prospects and Research Needs; September 2-8, 2000; Banff, Alberta, Canada, p. 15.
Roper, J., and Roberts, R.W. (2003). Deforestation: tropical forests in decline. CIDA Forestry Advisers Network (CFAN) Forestry Issues paper. Available from:www.cifor.cgiar.org/docs/_ref/ findoutabout/deforestation/df_research. htm. Accessed August 16, 2004.
Singh, K.D. (1993). The 1990 tropical f o r e s t r e s o u r c e s a s s e s s m e n t . Unasylva - An International Journal of Forestry and Forest Industries, 44(3). Available from: www.fao.org/docrep/ v0290E/v0290e00. htm#Contents. Accessed August 15, 2004.
