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Modeling Deforestation Using a Neural Network-Markov Model

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Spatial Analysis and Modeling in Geographical Transformation Process

Part of the book series: GeoJournal Library ((GEJL,volume 100))

Abstract

Tam Dao National Park (TDNP) region is a last remaining primary forest near Hanoi, the capital of Vietnam. It is endowed with some of the highest levels of biodiversity in Vietnam. Forest conversion due to illegal logging and agricultural expansion due to growing population in its vicinity is a major problem that is hampering biodiversity conservation efforts in the TDNP region. Yet, areas vulnerable to forest conversion are unknown. In this chapter, we predicted areas vulnerable to forest changes in the TDNP region using multi-temporal remote sensing data and a multi-layer perceptron neural network (MLPNN) with a Markov chain model (MLPNN-M). The MLPNN-M model predicted increasing pressure in the remaining primary forest within the park as well as on the secondary forest in the surrounding areas. The primary forest is predicted to decrease from 18.03% in 2007 to 15.10% in 2014 and 12.66% in 2021. Our results can be used to prioritize locations for future biodiversity conservation and forest management efforts. The combined use of remote sensing and spatial modeling techniques provides an effective tool for monitoring the remaining forests in the TDNP region.

This chapter is improved from “Duong Dang Khoi and Yuji Murayama (2010), Forecasting areas vulnerable to forest conversion in the Tam Dao National Park Region, Vietnam, Remote Sensing, 2, 1249–1272”.

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References

  • Ali, J., Benjaminsen, A. T., Hammad, A. A., & Dick, B. O. (2005). The road to deforestation: An assessment of forest loss and its causes in Basho Valley, Northern Pakistan. Global Environmental Change, 15, 370–380.

    Article  Google Scholar 

  • Bawa, K. S., & Dayanandan, S. (1997). Socioeconomic factors and tropical deforestation. Nature, 386, 562–563.

    Article  Google Scholar 

  • Brown, S., & Lugo, A. E. (1990). Tropical secondary forests. Journal of Tropical Ecology, 6, 1–32.

    Article  Google Scholar 

  • Cropper, M., Puri, J., & Griffiths, C. (2001). Predicting the location of deforestation: The role of roads and protected areas in North Thailand. Land Economics, 77, 172–186.

    Article  Google Scholar 

  • De Koninck, R. (1999). Deforestation in Vietnam. Ottawa, ON: International Development Research Center. Retrieved September 15, 2008, from http://www.idrc.ca/en/ev-9318-201-1-DO_TOPIC.html.

    Google Scholar 

  • Dendoncker, N., Roundsevell, M., & Bogaert, P. (2007). Spatial analysis and modeling of land use distributions in Belgium. Computers, Environment and Urban Systems, 31, 188–205.

    Article  Google Scholar 

  • Eastman, J. R. (2009). IDRISI taiga, guide to GIS and remote processing (pp. 234–256). Worcester: Clark University.

    Google Scholar 

  • Eastman, J. R., Jin, W., Kyem, P. A. K., & Toledano, R. (1995). Raster procedures for multi-criteria/multi-objective decisions. Photogrammetric Engineering and Remote Sensing, 61, 539–547.

    Google Scholar 

  • FAO, 2006. Global forest resources assessment 2005: Progress toward sustainable forest management. FAO. Retrieved September 25, 2008, from http://www.fao.org/DOCREP/008/a0400e/a0400e/a0400e00.htm

  • Geist, H. J., & Lambin, E. F. (2002). Proximate causes and underlying driving forces of tropical deforestation. BioScience, 52, 143–150.

    Article  Google Scholar 

  • Ghazoul, J. (1994). Tam Dao nature reserve: Results of a biological survey. Hanoi: Society for Environmental Exploration, UK and Xuan Mai Forestry College.

    Google Scholar 

  • Giriraj, A., Irfan-Ullah, M., Murthy, M. S. A., & Beierkuhnlein, A. (2008). Modelling spatial and temporal forest cover change patterns (1973–2020): A case study from South Western Ghats (India). Sensors, 8, 6132–6153.

    Article  Google Scholar 

  • Haines-Young, R. (2009). Land use and biodiversity relationships. Land Use Policy, 26, 178–186.

    Article  Google Scholar 

  • ICEM (International Centre for Environmental Management). (2003). Vietnam national report on protected areas and development (pp. 19–47). Indooroopilly, QLD: ICEM.

    Google Scholar 

  • Kanellopoulos, I., & Wilkinson, G. G. (1997). Strategies and best practice for neural network image classification. International Journal of Remote Sensing, 18, 711–725.

    Article  Google Scholar 

  • Khang, N. D., Hoe, H., Duc, H. D., Thin, N. N., Tien, D. D., Lanh, V. L., et al. (2007). Tam Dao national park (pp. 9–56, in Vietnamese). Hanoi, Vietnam: Agricultural Publishing House.

    Google Scholar 

  • Kuznetsov, A. N. (2005). Rapid botanical assessment of Tam Dao national park: Detailed botanical survey final report. Tam Dao: Tam Dao National Park.

    Google Scholar 

  • Lambin, E. F. (1994). Modelling deforestation processes: A review (TREES Series B: Research Report No. 1, EUR 15744 EN). Luxembourg: European Commission.

    Google Scholar 

  • Lambin, E. F. (1997). Modelling and monitoring land-cover change processes in tropical regions. Progress in Physical Geography, 21, 375–393.

    Article  Google Scholar 

  • Lek, S., Delacoste, M., Baran, P., Dimopoulos, I., Lauga, J., & Aulanier, S. (1996). Application of neural networks to modelling non-linear relationships in ecology. Ecological Modelling, 90, 39–52.

    Article  Google Scholar 

  • Li, X., & Yeh, A. G. O. (2002). Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science, 16, 323–343.

    Article  Google Scholar 

  • Linkie, M., Smith, R. J., & Leader-Williams, N. (2004). Mapping and predicting deforestation patterns in the lowlands of Sumatra. Biodiversity and Conservation, 13, 1809–1818.

    Article  Google Scholar 

  • Ludeke, A. K., Maggio, R. C., & Reid, L. M. (1990). An analysis of anthropogenic deforestation using logistic regression and GIS. Journal of Environmental Management, 1, 247–259.

    Article  Google Scholar 

  • Mas, J. F., Puig, H., Palacio, J. L., & Lopez, A. S. (2004). Modelling deforestation using GIS and artificial neural networks. Environmental Modeling and Software, 19, 461–471.

    Article  Google Scholar 

  • Merten, B., & Lambin, E. F. (1997). Spatial modeling of tropical deforestation in southern Cameroon: Spatial disaggregation of diverse deforestation processes. Applied Geography, 17, 143–162.

    Article  Google Scholar 

  • Meyfroidt, P., & Lambin, F. E. (2008). The causes of the reforestation in Vietnam. Land Use Policy, 25, 182–197.

    Article  Google Scholar 

  • Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B., & Kent, J. (2000). Biodiversity hotspots for conservation priorities. Nature, 403, 853–858.

    Article  Google Scholar 

  • Pijanowski, B. C., Brown, D. G., Shellito, B. A., & Manik, G. A. (2002). Using neural networks and GIS to forescast land use changes: A land transformation model. Computers, Environment and Urban Systems, 26, 553–575.

    Article  Google Scholar 

  • Poffenberger, M., & Nguyen, H. P. (1998). Stewards of Vietnam’s upland forests. Center for southeast Asia Studies. Retrieved September 20, 2008, from http://www.mekonginfo.org/mrc_en/doclib.nsf/0/E5E0A84E9B42A19F80256690003862FB/$FILE/FULLTEXT.html

  • Pontius, R. G., Huffaker, D., & Denman, K. (2004). Useful techniques of validation for spatially explicit land change models. Ecological Modelling, 179, 445–461.

    Article  Google Scholar 

  • Sader, S. A., & Joyce, A. T. (1998). Deforestation rates and trends in Costa Rica, 1940–1983. Biotropica, 20, 11–19.

    Article  Google Scholar 

  • Sala, O. E., Chapin, F. S., III, Armesto, J. J., Berlow, E., Bloomfield, J., Dirzo, R., et al. (2000). Global biodiversity scenarios for the year 2100. Science, 287, 1770–1774.

    Article  Google Scholar 

  • Sam, D. D. (1994). Shifting cultivation in Vietnam: Social, economic and environmental values relative to alternative land use (pp. 3–15). London: International Institute for Environment and Development.

    Google Scholar 

  • TDMP (Tam Dao National Park and Buffer Zone Management Project). (2005). Rural household economics baseline survey. Tam Dao National Park. Retrieved October 15, 2009, from http://tamdaonp.com.vn/

  • Turner, W., Spector, S., Gardiner, N., Fladeland, M., Sterling, E., & Steininger, M. (2003). Remote sensing for biodiversity science and conservation. Trends in Ecology and Evolutions, 18, 306–314.

    Article  Google Scholar 

  • Vitousek, P. M. (1994). Beyond global warming: Ecology and global change. Ecology, 75, 1861–1876.

    Article  Google Scholar 

  • Walker, R. (2004). Theorizing land-cover and land-use change: The case of tropical deforestation. International Regional Science Review, 27, 247–270.

    Article  Google Scholar 

  • Wilkie, D., Shaw, E., Rotberg, F., Morelli, G., & Auzel, P. (2000). Roads, development, and conservation in the Congo Basin. Conservation Biology, 14, 1614–1622.

    Article  Google Scholar 

  • World Bank. (1992). World development report 1992: Development and the environment. Oxford University Press. Retrieved June 12, 2009, from http://econ.worldbank.org/external/default/main?pagePK=64165259&theSitePK=469372&piPK=64165421&menuPK=64166093&entityID=000178830_9810191106175

  • Wright, S. J. (2005). Tropical forests in a changing environment. Trends in Ecology and Evolutions, 20, 553–560.

    Article  Google Scholar 

  • Zhou, J., & Civco, D. (1996). Using genetic learning neural networks for spatial decision making in GIS. Photogrammetric Engineering and Remote Sensing, 62, 1287–1295.

    Google Scholar 

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Authors and Affiliations

  1. Division of Spatial Information Science, Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan

    Duong Dang Khoi & Yuji Murayama

Authors
  1. Duong Dang Khoi
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  2. Yuji Murayama
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Correspondence to Duong Dang Khoi .

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Editors and Affiliations

  1. Graduate School of Life and Environmenta, Division of Spatial Information Science, University of Tsukuba, Tennodai 1-4-1, Tsukuba, 305-8571, Ibaraki, Japan

    Yuji Murayama

  2. , Geoenvironmental Sciences, University of Tsukuba, Tennodai 1-1-1, Tsukuba, 305-8572, Ibaraki, Japan

    Rajesh Bahadur Thapa

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Khoi, D.D., Murayama, Y. (2011). Modeling Deforestation Using a Neural Network-Markov Model. In: Murayama, Y., Thapa, R. (eds) Spatial Analysis and Modeling in Geographical Transformation Process. GeoJournal Library, vol 100. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0671-2_11

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