Journal of Mountain Science

, Volume 11, Issue 5, pp 1192–1207 | Cite as

Deforestation trends and spatial modelling of its drivers in the dry temperate forests of northern Pakistan — A case study of Chitral

  • Khuram Shehzad
  • Faisal M. QamerEmail author
  • M. S. R. Murthy
  • Sawaid Abbas
  • Laxmi D. Bhatta


Deforestation is a major environmental challenge in the mountain areas of Pakistan. The study assessed trends in the forest cover in Chitral tehsil over the last two decades using supervised land cover classification of Landsat TM satellite images from 1992, 2000, and 2009, with a maximum likelihood algorithm. In 2009, the forest cover was 10.3% of the land area of Chitral (60,000 ha). The deforestation rate increased from 0.14% per annum in 1992–2000 to 0.54% per annum in 2000–2009, with 3,759 ha forest lost over the 17 years. The spatial drivers of deforestation were investigated using a cellular automaton modelling technique to project future forest conditions. Accessibility (elevation, slope), population density, distance to settlements, and distance to administrative boundary were strongly associated with neighbourhood deforestation. A model projection showed a further loss of 23% of existing forest in Chitral tehsil by 2030, and degradation of 8%, if deforestation continues at the present rate. Arandu Union Council, with 2212 households, will lose 85% of its forest. Local communities have limited income resources and high poverty and are heavily dependent on non-timber forest products for their livelihoods. Continued deforestation will further worsen their livelihood conditions, thus improved conservation efforts are essential.


Remote sensing Drivers of deforestation Cellular automata 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Adams JB, Sabol DE, Kapos V, et al. (1995) Classification of multispectral images based on fractions of endmembers: Application to land-cover change in the Brazilian Amazon. Remote Sensing of Environment 52(2): 137–154. DOI: 10.1016/0034-4257(94)00098-8CrossRefGoogle Scholar
  2. Agarwal C, Green GM, Grove JM, et al. (2002) A review and assessment of land use change models. Dynamics of Space, Time, and Human Choice. CIPEC Collaborative Report Series No.1Google Scholar
  3. Agterberg FP, Bonham-Carter GF (1990) Deriving weights of evidence from geoscience contour maps for the prediction of discrete events. Paper presented at the 22nd APCOM Symposium, Berlin, Germany 2: 381–395.Google Scholar
  4. Ali J, Benjaminsen TA, Hammad AA, et al. (2005) The road to deforestation: An assessment of forest loss and its causes in Basho Valley, Northern Pakistan. Global Environmental Change 15(4): 370–380. DOI: 10.1016/j.gloenvcha.2005.06.004CrossRefGoogle Scholar
  5. Almeida CMD, Monteiro AMV, Câmara G, et al. (2005) GIS and remote sensing as tools for the simulation of urban landuse change. International Journal of Remote Sensing 26(4): 759–774.CrossRefGoogle Scholar
  6. Beg AR, Bakhsh I (1974) Vegetation of scree slopes in Chitral Gol. The Pakistan Journal of Forestry 24(2): 393–402. DOI: 0.1080/01431160512331316865Google Scholar
  7. Benedethi ACP (2010) Dynamic modeling to simulate changes in forest cover of the Sierras Southeast and Southern Campaign of the Rio Grande South. Tese (Doutorado em Engenharia Florestal) — Universidade Federal de Santa Maria, Santa Maria. pp 166–178.Google Scholar
  8. Bonham-Carter GF (1994) Geographic information systems for geoscientists: modelling with GIS (Vol. 13). Elsevier, Netherlands. pp 33–47Google Scholar
  9. Bürgi M, Hersperger AM, Schneeberger N (2004) Driving forces of landscape change-current and new directions. Landscape ecology 19(8): 857–868. DOI: 10.1007/s10980-004-0245-8CrossRefGoogle Scholar
  10. Champion HG, Seth SK, Khattak GM (1966) Forest Types of Pakistan. The Pakistan Forest Institute, Peshawar, Pakistan.Google Scholar
  11. Chadha SK (1988) Himalayas, Ecology and Environment, Mittal Publication, New Dehli, India.Google Scholar
  12. Chavez PS (1996) Image-based atmospheric corrections-revisited and improved. Photogrammetric Engineering and Remote Sensing 62(9): 1025–1035.Google Scholar
  13. Chomitz KM, Thomas TS (2003) Determinants of land use in Amazonia: a fine-scale spatial analysis. American Journal of Agricultural Economics 85(4): 1016–1028. DOI:10.1111/1467-8276.00504.CrossRefGoogle Scholar
  14. Cowling SA, Betts RA, Cox PM, et al. (2004) Contrasting simulated past and future responses of the Amazonian forest to atmospheric change. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 359(1443): 539–547. DOI: 10.1098/rstb.2003.1427.CrossRefGoogle Scholar
  15. FAO (2010) Food and Agriculture Organization. Global forest resources assessment. Rome, Italy. pp: 225. Available online: (Accessed on 31 July 2014)Google Scholar
  16. Farfán M, Mas JF, Osorio L (2012) Interpolating socioeconomic data for the analysis of deforestation: a comparison of methods. Journal of Geographic Information System 4: 358–365. DOI: 10.4236/jgis.2012.44041CrossRefGoogle Scholar
  17. Fearnside PM, Leal N, Fernandes FM (1993) Rainforest burning and the global carbon budget: Biomass, combustion efficiency, and charcoal formation in the Brazilian Amazon. Journal of Geophysical Research: Atmospheres 98(D9): 16733–16743. DOI: 10.1029/93JD01140.CrossRefGoogle Scholar
  18. Ferrari R (2008) Dynamics of Land Use and Cover Modeling the Quarta Colônia Dissertação (Mestrado em Geomática)-Universidade Federal de Santa Maria, Santa Maria, Brazil. p 130.Google Scholar
  19. Gautam AP, Shivakoti GP, Webb EL (2004) Forest cove change, physiography, local economy, and institutions in a mountain watershed in Nepal. Environmental Management 33: 48–61.CrossRefGoogle Scholar
  20. Geist HJ, Lambin EF (2001) What drives tropical deforestation? LUCC Report Series No. 4, CIACO, Louvain-la-Neuve, Belgium. p 116. Available online: (Accessed on 31 July 2014).Google Scholar
  21. Geist HJ, Lambin EF (2002) Proximate causes and underlying driving forces of tropical deforestation: Tropical forests are disappearing as the result of many pressures, both local and regional, acting in various combinations in different geographical locations. BioScience 52(2): 143–150. DOI: 10.1641/0006-3568(2002)052CrossRefGoogle Scholar
  22. Geri F, Amici V, Rocchini D (2011) Spatially-based accuracy assessment of forestation prediction in a complex Mediterranean landscape. Applied Geography 31(3): 881–890. DOI: 10.1016/j.apgeog.2011.01.019CrossRefGoogle Scholar
  23. Gong P, Pu R, Biging GS, et al. (2003) Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing 41(6): 1355–1362. DOI: 10.1109/TGRS.2003.812910.CrossRefGoogle Scholar
  24. Goodacre AK, Bonham-Carter GF, Agterberg FP et al. (1993) A statistical analysis of the spatial association of seismicity with drainage patterns and magnetic anomalies in western Quebec. Tectonophysics 217(3): 285–305. DOI: 10.1016/0040-1951(93)90011-8.CrossRefGoogle Scholar
  25. GoP (2004) National Forest and Rangeland Resource Assessment, Government of Pakistan, Pakistan Forest Institute, Peshawar, Pakistan. pp 56–70Google Scholar
  26. GoP (2010) Annual Agriculture Census Report 2010. Government of Pakistan, Lahore, Pakistan. pp 258. Available online: (Accessed on 31 July 2014)Google Scholar
  27. GoP (2002) Government of Pakistan, Pakistan Water Sector Strategy, Ministry of Water and Power. Office of the Chief Engineering Advisor 1, October 2002. p 210. Available online: (Accessed on 31 July 2014)Google Scholar
  28. GoP (1992) Government of Pakistan, Forestry Sector Master Plan. National Perspective Ried, Collins and Associates, Canada and Silviconsult Ltd. Sweden. Ministry of Food and Agriculture, Islamabad, Pakistan, pp 95.Google Scholar
  29. Henders S, Ostwald M (2012) Forest carbon leakage quantification methods and their suitability for assessing leakage in REDD. Forests 3(1): 33–58. DOI: 10.3390/f3010033CrossRefGoogle Scholar
  30. Hosonuma N, Herold M, De Sy V, et al. (2012) An assessment of deforestation and forest degradation drivers in developing countries. Environmental Research Letters 7(4): 7–9. DOI: 10.1088/1748-9326/7/4/044009CrossRefGoogle Scholar
  31. Joshi PK, Gairoal S (2004) Land cover dynamics in Garhwal Himalayas-a case study of Balkhila sub-watershed. Journal of the Indian Society of Remote Sensing 32(2): 199–208. DOI: 10.1007/BF03030876.CrossRefGoogle Scholar
  32. Joshi PK, Singh S, Agarwal S, et al. (2001) Forest cover assessment in western Himalayas, Himachal Pradesh using IRS 1 C/1 D WiFS data. Current Science 80(8): 941–947. DOI: 10.1007/BF03030776Google Scholar
  33. Kamusoko C, Oono K, Nakazawa A, et al. (2011) Spatial simulation modelling of future forest cover change scenarios in Luangprabang province, Lao PDR. Forests 2(3): 707–729. DOI: 10.3390/f2030707CrossRefGoogle Scholar
  34. Kardoulas NG, Bird AC, Lawan AI (1996) Geometric correction of SPOT and Landsat imagery: a comparison of map-and GPS-derived control points. Photogrammetric Engineering and Remote Sensing 62(10): 1173–1177. DOI: 10.1080/01431160701592452Google Scholar
  35. Kennedy RE (2009) Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment 113(7): 1382–1396. DOI: 10.1016/j.rse.2008.07.018CrossRefGoogle Scholar
  36. Keuchel J, Naumann S, Heiler M, et al. (2003) Automatic land cover analysis for Tenerife by supervised classification using remotely sensed data. Remote Sensing of Environment 86(4): 530–541. DOI: 10.1016/S0034-4257(03)00130-5CrossRefGoogle Scholar
  37. Khan AA (1975) Report on the wildlife of Chitral. NWFP Forest Department, Peshawar, Pakistan.Google Scholar
  38. Khan AM (1994) Culture and natural resources of Kalash valley Bomburet. M.Sc, University of Peshawar, Pakistan.Google Scholar
  39. Sheikh MI, Khan M (1983) Forestry and range management in Chitral District. Pakistan Journal of Forestry 33(3): 105–110Google Scholar
  40. Knudsen A, Madsen ST (1999) Deforestation and Entrepreneurship in the North-West Frontier Province, Pakistan. State, Society and the Environment in South Asia, Curzon, London. pp 200–235.Google Scholar
  41. Kutrib M, Vollmar R, Worsch TH (1997) Introduction to the special issue on cellular automata. Parallel Computing 3(11): 44–66. DOI: 10.1016/S0167-8191(97)00079-3Google Scholar
  42. Lodhi MA, Echavarria FR, Keithley C (1998) Using remote sensing data to monitor land cover changes near Afghan refugee camps in northern Pakistan. Geocarto International 13(1): 33–39. DOI: 10.1080/10106049809354626CrossRefGoogle Scholar
  43. Maeda EE, Almeida CM, Carvalho Ximenes A, et al. (2011) Dynamic modeling of forest conversion: Simulation of past and future scenarios of rural activities expansion in the fringes of the Xingu National Park, Brazilian Amazon. International Journal of Applied Earth Observation and Geoinformation 13(3): 435–446. DOI: 10.1016/j.jag.2010.09.008CrossRefGoogle Scholar
  44. Nüsser M (2000) Change and persistence: Contemporary landscape transformation in the nanga parbat region, northern Pakistan. Mountain Research and Development 20: 348–355. DOI: 10.1659/0276-4741(2000)020[0348:CAPCLT]2.0.CO;2CrossRefGoogle Scholar
  45. Pandit MK, Sodhi NS, Koh LP et al. (2007) Unreported yet massive deforestation driving loss of endemic biodiversity in Indian Himalaya. Biodiversity and Conservation 16(1): 153–163. DOI: 10.1007/s10531-006-9038-5CrossRefGoogle Scholar
  46. Pontius RG (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): 1041–1050.Google Scholar
  47. Qamer FM, Abbas S, Saleem R, et al. (2012) Forest cover change assessment in conflict-affected areas of northwest pakistan: The case of swat and shangla districts. Journal of Mountain Science 9: 297–306. DOI: 10.1007/s11629-009-2319-1CrossRefGoogle Scholar
  48. Qasim M, Hubacek K, Termansen M, et al. (2011) Spatial and temporal dynamics of land use pattern in district swat, Hindu Kush Himalayan region of Pakistan. Applied Geography 31: 820–828. DOI: 10.1016/j.apgeog.2010.08.008CrossRefGoogle Scholar
  49. Rademaekers K, Eichler L, Berg J, et al. (2010) Study on the evolution of some deforestation drivers and their potential impacts on the costs of an avoiding deforestation scheme; ECORYS and IIASA: Rotterdam, Netherlands.Google Scholar
  50. Rogan JFJ, Roberts DA (2002) A comparison of methods for monitoring multitemporal vegetation change using thematic mapper imagery. Remote Sensing of Environment 80: 143–156. DOI: 10.1016/S0034-4257(01)00296-6CrossRefGoogle Scholar
  51. Rozenstein O, Karnieli A (2011) Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Applied Geography 31:533–544. DOI: 10.1016/j.apgeog.2010.11.006CrossRefGoogle Scholar
  52. Schickhoff U (1995) Himalayan forest-cover changes in historical perspective: A case study in the Kaghan valley, Northern Pakistan. Mountain Research and Development 3–18. DOI: 10.2307/3673697Google Scholar
  53. Soares-Filho BS, Coutinho CG, Lopes PC (2013) Dinamica-a stochastic cellular automata model designed to simulate the landscape dynamics in an amazonian colonization frontier. Ecological modelling 154: 217–235. DOI: 10.1016/S0304-3800(02)00059-5CrossRefGoogle Scholar
  54. Soares-Filho BS, Nepstad DC, Curran LM, et al. (2006) Modelling conservation in the amazon basin. Nature 440: 520–523. DOI: 10.1038/nature04389CrossRefGoogle Scholar
  55. Shroder JF (1998) Slope failure and denudation in the western Himalaya. Geomorphology 26(1): 81–105. DOI: 10.1016/S0169-555X(98)00052-XCrossRefGoogle Scholar
  56. Swaminathan MS (1988) The promise of agroforestry for ecological and nutrition security. The potential of agroforestry. World Agroforestry Center, Nairobi, Kenya.Google Scholar
  57. Tejwani K (1990) Bio-Physical and socio-economic causes of land degradation and strategy to foster watershed rehabilitation in the Himalayas. in Sah N, Bhatt S, and Pande R (eds.). Himalaya: Environment, Resources and Development, pp. 378–385. Shree Almora Book Depot, Almora, India.Google Scholar
  58. Tekle K (2000) Land-cover changes between 1958 and 1986 in Kalu district, Southern Wello, Ethiopia. Mountain Research and Development 20: 42–51. DOI: 10.1659/0276-4741(2000)020[0042:LCCBAI]2.0.CO;2CrossRefGoogle Scholar
  59. Tole L (1998) Sources of deforestation in tropical developing countries. Environmental Management 22: 19–33. DOI: 10.1016/j.worlddev.2005.09.005CrossRefGoogle Scholar
  60. Verburg PH, De Koning GHJ, Kok K, et al. (1999) A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological Modelling 116: 45–61. DOI: 10.1016/S0304-3800(98)00156-2CrossRefGoogle Scholar
  61. Walker RT (1987) Land use transition and deforestation in developing countries. Geographical Analysis 19: 18–30. DOI: 10.1111/j.1538-4632.1987.tb00111.xCrossRefGoogle Scholar
  62. Wolfram S (1983) Cellular automata. Los Alamos Science 9: 2–27. Available online: (Accessed on 31 July 2014).Google Scholar
  63. Yemshanov D, Perera AH (2002) A spatially explicit stochastic model to simulate boreal forest cover transitions: general structure and properties. Ecological Modelling 150: 189–209. DOI: 10.1016/S0304-3800(01)00480-XCrossRefGoogle Scholar

Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Khuram Shehzad
    • 1
  • Faisal M. Qamer
    • 1
    Email author
  • M. S. R. Murthy
    • 1
  • Sawaid Abbas
    • 2
  • Laxmi D. Bhatta
    • 1
  1. 1.International Centre for Integrated Mountain Development (ICIMOD)KathmanduNepal
  2. 2.The Hong Kong Polytechnic UniversityHung Hom, Kowloon, Hong KongChina

Personalised recommendations