대한원격탐사학회지 (Korean Journal of Remote Sensing)

  • 제27권3호
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  • Pages.315-328
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  • 2011
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  • 1225-6161(pISSN)
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  • 2287-9307(eISSN)
대한원격탐사학회 (Korean Society of Remote Sensing)
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Assessing the Extent and Rate of Deforestation in the Mountainous Tropical Forest

  • Pujiono, Eko (Department of Environmental Science and Ecological Engineering, Korea University) ;
  • Lee, Woo-Kyun (Department of Environmental Science and Ecological Engineering, Korea University) ;
  • Kwak, Doo-Ahn (Environmental GIS/RS Center, Korea University) ;
  • Lee, Jong-Yeol (Department of Environmental Science and Ecological Engineering, Korea University)
  • 투고 : 2011.05.07
  • 심사 : 2011.05.26
  • 발행 : 2011.06.30
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초록

Landsat data incorporated with additional bands-normalized difference vegetation index (NDVI) and band ratios were used to assess the extent and rate of deforestation in the Gunung Mutis Nature Reserve (GMNR), a mountainous tropical forest in Eastern of Indonesia. Hybrid classification was chosen as the classification approach. In this approach, the unsupervised classification-iterative self-organizing data analysis (ISODATA) was used to create signature files and training data set. A statistical separability measurement-transformed divergence (TD) was used to identify the combination of bands that showed the highest distinction between the land cover classes in training data set. Supervised classification-maximum likelihood classification (MLC) was performed using selected bands and the training data set. Post-classification smoothing and accuracy assessment were applied to classified image. Post-classification comparison was used to assess the extent of deforestation, of which the rate of deforestation was calculated by the formula suggested by Food Agriculture Organization (FAO). The results of two periods of deforestation assessment showed that the extent of deforestation during 1989-1999 was 720.72 ha, 0.80% of annual rate of deforestation, and its extent of deforestation during 1999-2009 was 1,059.12 ha, 1.31% of annual rate of deforestation. Such results are important for the GMNR authority to establish strategies, plans and actions for combating deforestation.

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참고문헌

  1. Abdulaziz, A. M., J. M. Hurtado, and R. Al-Douri, 2009. Application of multitemporal Landsat data to monitor land cover change in the Eastern Nile Delta region, Egypt. International Journal of Remote Sensing, 30(11): 2977-2996. https://doi.org/10.1080/01431160802558675
  2. Bahadur, K., 2009. Improving Landsat and IRS Image Classification: Evaluation of Unsupervised and Supervised Classification through Band Ratio and DEM in a Mountainous Landscape in Nepal. Remote Sensing, 1: 1257-1272. https://doi.org/10.3390/rs1041257
  3. Bauer, M. E., T. E. Burk, A. R. Ek, P. R. Coppin, S. D. Lime, T. A. Walsh, D. K. Walters, W. Befort, and D. F. Heinzen, 1994. Satellite Inventory of Minnesota Forest Resources. Photogrammetric Engineering & Remote Sensing, 60(3): 287-298.
  4. Bonfour, A. and E. F. Lambin, 1999. How valuable is remote sensed information? The case of tropical deforestation modelling. Space Policy, 15: 149-158. https://doi.org/10.1016/S0265-9646(99)00025-9
  5. Broich, M., M. Hansen, F. Stolle, P. Potapov, B. A. Margono, and B. Adusei, 2011. Remote sensed forest cover loss shows high spatial and temporal variation across Sumatera and Kalimantan, Indonesia 2000-2008. Environmental Research Letter, 6.
  6. Burgess, R., M. Hansen, B. Olken, and S. Sieber, 2010. The political economy of deforestation in the tropics. The University of Warwick, Coventry, UK.
  7. Casson, A. and K. Obidzinski, 2002. From New Order to Regional Autonomy: Shifting Dynamics of 'Ilegal' Logging in Kalimantan, Indonesia. World Development, 30(12): 2133-2151. https://doi.org/10.1016/S0305-750X(02)00125-0
  8. Congalton, R., 1991. A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data. Remote Sensing of Environment, 37: 35-46. https://doi.org/10.1016/0034-4257(91)90048-B
  9. Congalton, R., 1996. Accuracy Assessment: A Critical Component of Land Cover Mapping. Gap Analysis. Gap Analysis. American Society for Photogrammetry and Remote Sensing.
  10. Eghenter, C., 2000. Mapping Peoples 'Forests: The Role of Mapping in Planning Community- Based Management of Conservation Areas in Indonesia. Washington DC.: Biodiversity Support Program (BSP).
  11. FAO, 1995. Forest Resources Assessment 1990. Global Synthesis. FAO, Rome, Italy.
  12. FAO, 2007. Manual on Deforestation, Degradation and Fragmentation using Remote Sensing and GIS. MAR-SFM Working Paper 5/2007.Food and Agriculture Organization of the United Nations, Rome.
  13. FAO, 2010. Global Forest Resources Assessment 2010. FAO Forestry Paper No. 163, the United Nations, Food and Agriculture Organization, Rome.
  14. Fisher, L. M., 1998. Cattle, Cockatoos, Chameleons and Ninja Turtles: Seeking Sustainability in Forest Management and Conservation in Nusa Tenggara, Indonesia. International CBNRM Workshop. Washington D.C.
  15. Fisher, L., I. Moeliono, and S. Wodicka, 2003. The Nusa Tenggara Upland, Indonesia: Multiple-site lessons in conflict management. In D. Buckles (Ed.), Cultivating Peace - Conflict and Collaboration in Nature Resources Management (p. 300pp). Ottawa, Canada: International Development Research Center (IDRC).
  16. Fuller, D. O, E. M. Meijaard, L. Christy, and T. C. Jessup, 2010. Spatial Assessment of threats to biodiversity within East Kalimantan, Indonesia. Applied Geography, 30: 416-425. https://doi.org/10.1016/j.apgeog.2009.11.004
  17. FWI & CIFOR., 2006. Analisa Kondisi Tutupan Hutan di Papua dan Irian Jaya Barat Sebagai Salah Satu Langkah untuk Mendukung Pengelolaan Hutan Alam dan Pembatasan Konflik di Sektor Kehutanan. Laporan Updating Landcover Mapping Papua, Kerjasama: FWI-Bogor dan CIFOR, Bogor. (In Indonesian language)
  18. FWI., 2003. Pemetaan Land Use Land Cover (LULC) dari Penginderaan Jauh Landsat7 ETM+ untuk Wilayah Mamberamo dan Raja Ampat Provinsi Papua. Laporan Proyek, Kerjasama: FWI, Baplan-Departemen Kehutanan dan Conservation International Indonesia-Papua Program, Bogor. (In Indonesian language)
  19. Gaveau, D. L. A., M. Linkie, Suyadi, P. Levang, and N. Leader-Williams, 2009. Three decades of deforestation in southwest Sumatra: Effects of coffe prices, law enforcement and rural poverty. Biological conservation, 142: 597-605. https://doi.org/10.1016/j.biocon.2008.11.024
  20. Gaveau, D. L. A., H. Wandono, and F. Setiabudi, 2007. Three decades of deforestation in Soutwest Sumatra: Have protected area halted forest loss and logging, and promoted regrowth? Biological Conservation, 134: 495-504. https://doi.org/10.1016/j.biocon.2006.08.035
  21. GoI-FAO, 1996. National Forest Inventory of Indonesia : Final Forest Resources Statistics Report. Directorate General of Forest Inventore and Land Use Planning, Ministry of Forestry Government of Indonesia and Food and Agriculture Organization of the United Nations, Jakarta.
  22. Jensen, J., 2005. Introductory Digital Image Processing: A Remote Sensing Perspective (3rd ed.). Upper Saddle River, NJ: Pearson Education, Inc.
  23. Landis, J. and G. Koch, 1977. The measurement of Observer Agreement for Categorical Data. Biometrics, 33: 159-174. https://doi.org/10.2307/2529310
  24. Leica Geosystems, 2005. Erdas Field Guide, Leica Geosystems Geospatial Imaging, LLC, Norcross, GA, USA.
  25. Lentz, C., M. Malo, and M. Bowe, 1998. Environmental Management in Gunung Mutis. International Association for the Study of Common Property, 10-14 June. Vancouver, Canada.
  26. Lillesand, T. M., R. W. Kiefer, and J. W. Chipman, 2004. Remote Sensing and Image Interpretation (5th ed.). Hoboken, NJ: John Willey & Sons, Inc.
  27. Linkie, M., R. J. Smith, and N. L. Williams, 2004. Mapping and predicting deforestation patterns in the lowlands of Sumatra. Biodiversity and Conservation, 13:1809-1818. https://doi.org/10.1023/B:BIOC.0000035867.90891.ea
  28. Macdonald, E. A., M. Collins, P. J. Johnson, L. M. Clayton, Y. Malhi, J. B. Fisher, E. J. Milner- Gulland, and D. W. Macdonald, 2011. Wildlife conservation and reduced emission from deforestation in a case study of Nantu National Park, Sulawesi. Environmental Science & Policy, article in press, doi: 10.1016/j.envsci. 2011.03.003.
  29. Mulyanto, L. and I. N. S. Jaya, 2004. Analisis Spasial Degradasi Hutan dan Deforestasi: Studi Kasus di PT. Duta Maju Timber, Sumatera Barat. Manajemen Hutan Tropika, X(1), 29-42.(In Indonesian language)
  30. Prenzel, B., 2004. Remote sensing-based quantification of land-cover and land-use change for planning. Progress in Planning, 61: 281-299. https://doi.org/10.1016/S0305-9006(03)00065-5
  31. Prenzel, B. and P. Treitz, 2004. Remote sensing change detection for a watershed in nort Sulawesi, Indonesia. Progress in Planning, 61: 349-363. https://doi.org/10.1016/S0305-9006(03)00068-0
  32. Puyravaud, J., 2003. Standardizing the calculation of the annual rate of deforestation. Forest Ecology and Management, 177: 593-596. https://doi.org/10.1016/S0378-1127(02)00335-3
  33. Rahman, M., 1997. Identification of Land Use and Land Cover using Band Ratioing Tecnique. Retrieved June 1, 2011, from http://www. murraystate.edu/qacd/cos/geo/gsc641/1997/ra hman/
  34. Redy, M. B. and B. Blah, 2009. Topographic normalization of satellite imagery for image classification in India. Progress in Physical Geography, 33(6): 815-836. https://doi.org/10.1177/0309133309351048
  35. Reese, H. M, T. M. Lillesand, D. E. Nagel, J. S. Stewart, R. A. Goldmann, T. E. Simmons, J. W. Chipman, and P. A. Tessar, 2002. Statewide landcover derived from multiseasonal Landsat TM data: A retrospective of the WISCLAND project. Remote Sesing of Environment, 82: 224-237. https://doi.org/10.1016/S0034-4257(02)00039-1
  36. Rouse, J. W., R. H. Haas, J. A. Schell, and D. W. Deering, 1974. Monitoring Vegetation Systems in Great Plains with ERTS. Proceedings, 3rd Earth ResourceTechnology Satellite (ERTS) Symposium, 1: 48-62.
  37. Saha, A. K., M. K. Arora, E. Csaplovics, and R. P. Gupta, 2005. Land Cover Classification using IRS LISS III Image and DEM in a Rugged Terrrain. Geocarto International, 20(2): 33-40. https://doi.org/10.1080/10106040508542343
  38. Shrestha, D. P. and J. A. Zink, 2001. Land use classification in mountainous areas: integration of image processing, digital elevation data and field knowledge (application to Nepal). International Journal of Applied Earth and Geoinformation, 3(1): 78-85. https://doi.org/10.1016/S0303-2434(01)85024-8
  39. Singer, B., 2009. Indonesian Forest-Related Policies: A Multisectoral Overview of Public Policies in Indonesia's Forests since 1965. PhD Thesis (Draft), Institut d'Etudes Politiques and CIRAD, France.
  40. Sunderlin, W. D., A. Angelson, B. Belcher, P. Burgers, R. Nasi, L. Santoso, S. Wunder, 2005. Livelihoods, Forests, and Conservations in Developing Countries: An Overview. World Development, 33(9): 1383-1402. https://doi.org/10.1016/j.worlddev.2004.10.004
  41. Tole, L., 2002. An estimate of forest cover extent and change in Jamaica using Landsat MSS data. International Journal of Remote Sensing, 23(1): 91-106. https://doi.org/10.1080/01431160010014837
  42. Yacouba, D., H. Guangdao, and W. Xingping, 2009. Assessment of Land Use Cover Changes using Ndvi and Dem in Puer and Simao Counties, Yunnan Province, China. World Rural Observation, 1(2): 1-11.
  43. Zhang, Z., R. R. D. Wulf, M. B. V. Coillie, L. P. C. Verbeke, E. M. De Clercq, and X. Qu, 2011. Influence of different topographic correction strategies on mountain vegetation classification accuracy in the Lancang Wathershed, China. Journal of Applied Remote Sensing, 5: 1-21.

피인용 문헌

  1. Assessment of causes and future deforestation in the mountainous tropical forest of Timor Island, Indonesia vol.16, pp.10, 2011, https://doi.org/10.1007/s11629-019-5480-1