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Evaluating exposure to land degradation in association with repetitive armed conflicts in North Lebanon using multi-temporal satellite data

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Abstract

Repetitive armed conflicts may be directly and indirectly responsible for severe biophysical modification to the environment. This, in turn, makes land more susceptible to degradation. Mapping and monitoring land degradation are essential for designing and implementing post-conflict recovery plans and informed policy decisions. The aim of this work was to evaluate the effect of repetitive armed conflicts on land degradation along the coastal zone of North Lebanon using multi-temporal satellite data. The specific objectives were to (1) identify a list of indicators for use in conjunction with satellite remote sensing, (2) monitor land cover change throughout repetitive events of armed conflicts and (3) model the effect of repetitive armed conflicts on land degradation. The methodology of work comprised the use of multi-temporal Landsat images and literature review data in GEographic Object-Based Image Analysis (GEOBIA) approach. The work resulted in the development of (1) a list of indicators to be employed, (2) land cover change detection maps with the use of multi-temporal Landsat images and, consequently, a fire risk associated with changes in vegetation cover throughout repetitive armed conflict events, and (3) an integrated approach for modelling the effect of repetitive armed conflicts on land degradation with the use of a composite land degradation index (CLDI). The final synthetic map showed four classes of exposure to land degradation associated with repetitive armed conflicts. Data collected from field visits showed that the final classification results highly reflected (average of 90 %) the effect of repetitive armed conflicts on the different classes of exposure to land degradation.

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References

  • AFDC/UNDP/SAAR (2007). War impact on forest resources and olive groves in South Lebanon (final report). In G. Mitri (Ed.), (pp. 80). Beirut: AFDC.

  • Amissah-Arthur, A., Mougenot, B., & Loireau, M. (2000). Assessing farmland dynamics and land degradation on Sahelian landscapes using remotely sensed and socioeconomic data. International Journal of Geographical Information Science, 14, 583–599.

    Article  Google Scholar 

  • Bai, Z., Dent, D., Olsson, L., & Schaepman, M. (2008). Global assessment of land degradation and improvement: identification by remote sensing. Rome/Wageningen: FAO/ISRIC.

    Google Scholar 

  • Barrow, C. (1994). Land degradation: development and breakdown of terrestrial environments. Cambridge: Cambridge University Press.

    Google Scholar 

  • Benayas, J., Martins, A., Nicolau, J., & Schuls, J. (2007). Abandonment of agricultural land: an overview of drivers and consequences. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2(057).

  • Biswas, A. K. (2002). Scientific assessment of the long-term environmental consequences of war. In J. E. Austin, & C. E. Bruch (Eds.), The environmental consequences of war: legal, economic, and scientific perspectives. Cambridge University Press.

  • Blaikie, P., & Brookfield, H. (1987). Land degradation and society. London: Methuen.

    Google Scholar 

  • Blaschke, T. (2010). Object based image analysis for remote sensing. International Journal of Photogrammetry and Remote Sensing, 65, 2–16.

    Article  Google Scholar 

  • CAS (2004). Living conditions nation survey. In Central Administration for Statistics. Lebanon (Ed.), (pp. 59). Beirut.

  • Chuvieco, E. (Ed.). (2009). Earth observation of wildland fires in Mediterranean ecosystems. Dordrecth: Springer.

    Google Scholar 

  • Civanlar, R., & Trussell, J. (1986). Constructing membership functions using statistical data. Fuzzy Sets and Systems, 18, 1–13.

    Article  Google Scholar 

  • Dumanski, J., & Pieri, C. (1996). Application of the pressure-state-response framework for the land quality indicators (LQI) programme. In Land quality indicators and their use in sustainable agriculture and rural development: proceedings of a workshop, 25-26 January. FAO: Rome.

  • ECODIT-IAURIF (1997). Regional Environmental Assessment report on the coastal zone of Lebanon: final report. ECODIT/IAURIF, Council for Development and Reconstruction.

  • ELARD (2008). The provision and development of an action plan for addressing environmental damage and for incorporating environmental standards in the rebuilding and operation of the surroundings of Nahr El Bared Palestinian Camp. Beirut: UNDP.

  • FAO (1980). Natural resources and the human environment for food and agriculture. Environment Paper No. 1. Rome.

  • GEF (2007). Land degradation focal area indicators. In International Workshop GEF, FAO Headquarters, Rome, Italy, 8-9 January 2007

  • Gitas, I., Mitri, G., & Gemma, V. (2004). Object-oriented image analysis for burned area mapping using NOAA-AVHRR imagery in Creus Cape, Spain. Remote Sensing of Environment, 92(3), 409–413.

    Article  Google Scholar 

  • Gitas, I., Mitri, G., Kazakis, G., Ghosn, D., & Xanthopoulos, G. (2006). Fuel type mapping in Anopolis, Crete by employing QuickBird imagery and object-based classification. Forest Ecology and Management, 234(1), 228.

    Article  Google Scholar 

  • Gitas, I., Mitri, G., Veraverbeke, S., & Polychronaki, A. (2012). Advances in remote sensing of post-fire monitoring: a review. In T. Fatoyinbo (Ed.), Remote sensing of biomass: principles and applications (pp. 143–176). NTECH publisher.

  • Gorse, J. E., & Steeds, D. (1987). Desertification in the Sahelian and Sudanian zones of West Africa. World Bank Technical Paper No 61. Washington, DC: International Bank for Reconstruction and Development/ World Bank: World Bank.

  • Haboudane, D., Bonn, F., Royer, A., Sommer, S., & Mehl, W. (2002). Land degradation and erosion risk mapping by fusion of spectrally-based information and digital geomorphometric attributes. International Journal of Remote Sensing, 23, 3795–3820.

    Article  Google Scholar 

  • Hall, F., Botkin, D., Strebel, D., Woods, K., & Goetz, S. (1991). Large-scale patterns of forest succession as determined by remote sensing. Ecology, 72, 628–640.

    Article  Google Scholar 

  • Hernandez-Leal, P., Arbelo, M., & Gonzalez-Calvo, A. (2006). Fire risk assessment using satellite data. Advances in Space Research, 37, 741–746.

    Article  Google Scholar 

  • Hill, J., Sommer, S., Mehl, W., & Megier, J. (1995). Use of earth observation satellite data for land degradation mapping and monitoring in Mediterranean ecosystems: towards a satellite observatory. Environmental Monitoring and Assessment, 37, 143–158.

    Article  CAS  Google Scholar 

  • IMAC. (2009). Assessment report: integrated management of East Mediterranean Coastlines. Tripoli: Institute of the Environment, University of Balamand.

    Google Scholar 

  • Johnson, D., & Lewis, L. (1995). Land degradation: creation and destruction. Oxford: Blackwell Publishers.

    Google Scholar 

  • Key, C., & Benson, N. (2006). Landscape assessment (LA)—sampling and analysis methods. General Technical Report RMRS-GTR-164-CD. Ogden, UT: USDA Forest Service, Rocky Mountain Research Station.

  • LADA. (2000). Report of the International Workshop on Dryland Degradation Assessment (LADA) Initiative. Rome: FAO.

    Google Scholar 

  • Lambin, E., Geist, H., Reynolds, J., & Stafford-Smith, M. (Eds.). (2005). Integrated approaches to desertification (International seminar on nuclear war and planetary emergencies, 34th session). Italy: Erice.

    Google Scholar 

  • Lavelle, P. (1987). Biological processes and productivity of soils in the humid tropics. In E. Robert (Ed.), The geophysiology of Amazonia: vegetation and climate interactions (pp. 175–222). New York: Wiley.

    Google Scholar 

  • Lu, D., Batistella, M., Mausel, P., & Moran, E. (2007). Mapping and monitoring land degradation risks on the Western Brazilian Amazon using multitemporal landsat TM/ETM images. Land Degradation and Development, 18, 41–54.

    Article  Google Scholar 

  • Machlis, G., & Hanson, T. (2008). Warfare ecology. BioScience, 729–736.

  • Maitima, J., Reid, R., Gachimbi, L., Majule, A., Layaruu, H., Pomery, D., et al. (2004). A methodological guide on how to identify trends and linkages between changes in land use, biodiversity and land degradation. LUCID working paper series (Vol. 43). Nairobi: International Livestock Research Institute.

  • Mitri, G., & El Hajj, R. (2008). State of Lebanon’s forests 2007. Beirut: AFDC/WWF/UNDP/IUCN.

    Google Scholar 

  • Mitri, G., & Gitas, I. (2004). A performance evaluation of a burned area object-based classification model when applied to topographically and non-topographically corrected TM imagery. International Journal of Remote Sensing, 25(14), 2863–2870.

    Article  Google Scholar 

  • Mitri, G., & Gitas, I. (2006). Fire type mapping using object-based classification of IKONOS imagery. International Journal of Wildland Fire, 15(4), 457–462.

    Article  Google Scholar 

  • Mitri, G., & Gitas, I. (2008). Mapping the severity of fire using object-based classification of Ikonos imagery. International Journal of Wildland Fire, 17(3), 431–442.

    Article  Google Scholar 

  • Mitri, G., & Gitas, I. (2010). Mapping post-fire vegetation regeneration using EO-1 Hyperion. IEEE Transactions on Geoscience and Remote Sensing, 48(3), 1613–1618.

    Article  Google Scholar 

  • Mitri, G., Nader, M., Van der Molen, I., & Lovett, J. (2011). The use of satellite imagery for the assessment of fire risk associated with repetitive armed conflicts in North Lebanon. In P. Duce, & D. Spano (Eds.), International conference on fire behaviour and risk modelling, Alghero, Italy, 4-6 October 2011 (pp. 159).

  • MoA/FAO (2000). Results of national agricultural census. Beirut, Lebanon: FAO/Ministry of Agriculture.

  • Moran, E., Brondizio, E., Tucker, J., Da Silva-Forsberg, M. C., Stephen, M., & Falesi, I. (2000). Effects of soil fertility and land use on forest succession in Amazonia. Forest Ecology and Management, 139, 93–108.

    Article  Google Scholar 

  • Mouflis, G., Gitas, I., Iliadou, S., & Mitri, G. (2008). Assessment of the visual impact of marble quarry expansion (1984–2000) on the landscape of Thasos island, NE Greece. International Journal of Landscape and Urban Planning, 86(1), 92–102.

    Article  Google Scholar 

  • Mubareka, S., & Ehrlich, D. (2010). Identifying and modeling environmental indicators for assessing population vulnerability to conflict using ground and satellite data. Ecological Indicators, 10, 493–503.

    Article  Google Scholar 

  • Muchena, F. (2008). Indicators for sustainable land management in Kenya’s context. Nairobi: GEF Land Degradation Focal Area Indicators, ETC-East Africa.

    Google Scholar 

  • Perez-Trejo, F. (1994). Desertification and land degradation in the European Mediterranean. EUR 14850 EN, (Office for Official Publications of the European Communities), Luxembourg.

  • POPIN (1995). Population and the environment: a review of issues and concepts for population programmes staff. FAO/UNFPA TSS.

  • Reuveny, R., Mihalache-O’Keef, A., & Li, Q. (2010). The effect of warfare on the environment. Journal of Peace Research, 47(6), 749–761.

    Article  Google Scholar 

  • Scherr, S., & Yadav, S. (2001). Land degradation in the developing world: issues and policy options for 2020 In P. Pinstrup-Andersen, & R. Lorch (Eds.), The unfinished agenda: perspectives on overcoming hunger, poverty and environmental degradation (pp. 133–138). Washington, DC: International Food Policy Research Institute.

  • Snel, M., & Bot, A. (2002). Some suggested indicators for land degradation assessment of drylands. In Land Degradation Assessment in Drylands—LADA, International Electronic Mail Conference, accomplished in October, 09, November, 11, 2002.

  • Sonneveld, B. (2003). Formalizing expert judgements in land degradation assessment: a case study for Ethiopia. Land Degradation & Development, 14, 347–361.

    Article  Google Scholar 

  • Stocking, M., & Murnaghan, N. (2001). Handbook for the field assessment of land degradation. London: Earhscan Publications Ltd.

    Google Scholar 

  • Symeonakis, E., & Drake, N. (2004). Monitoring desertification and land degradation over sub-Saharan Africa. International Journal of Remote Sensing, 25, 573–592.

    Article  Google Scholar 

  • TEDO (2006). Tripoli environment and development observatory. Progress Report 20 (pp. 235). Tripoli.

  • Thiam, A. (2003). The causes and spatial pattern of land degradation risk in southern Mauritania using multitemporal AVHRR-NDVI imagery and field data. Land Degradation & Development, 14, 133–142.

    Article  Google Scholar 

  • UNCCD (2008). The consequences of desertification: fact sheet 3. Accessed 27-2-2012 2012.

  • UNDP. (2006). Lebanon rapid environmental assessment for green recovery reconstruction and reform. Beirut: ELARD.

    Google Scholar 

  • UNEP-MAP/ECODIT (2005). National action plan for the reduction of pollution into the Mediterranean Sea from land based sources. (pp. 63).

  • Ustin, S., Jacquemoud, S., Palacios-Oreuta, A., Li, L., & Whiting, M. (2005). Remote sensing based assessment of biophysical indicators for land degradation and desertification. In 1st International Conference on Remote Sensing and Geoinformation Processing in the Assessment and Monitoring of Land Degradation and Desertification, Trier, Germany.

  • Wessels, K., Prince, S., Frost, P., & van Zyl, D. (2004). Assessing the effects of human induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series. Remote Sensing of Environment, 91, 47–67.

    Article  Google Scholar 

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Acknowledgments

The authors wish to express their appreciation to the Netherlands Organisation for Scientific Research and the WOTRO Science for Global Development for providing financial assistance to pursue the current work. Also, the authors are thankful to the Planet Action (SPOT initiative) for providing technical support to pursue certain tasks of the current work.

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Authors and Affiliations

  1. Institute of the Environment, University of Balamand, El-Koura, Lebanon

    George Mitri & Manal Nader

  2. Centre for Risk Management, Safety and Security, University of Twente, Enschede, The Netherlands

    Irna Van der Molen

  3. School of Geography, University of Leeds, Leeds, West Yorkshire, UK

    Jonathan Lovett

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  1. George Mitri
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  2. Manal Nader
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  3. Irna Van der Molen
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  4. Jonathan Lovett
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Correspondence to George Mitri.

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Mitri, G., Nader, M., Van der Molen, I. et al. Evaluating exposure to land degradation in association with repetitive armed conflicts in North Lebanon using multi-temporal satellite data. Environ Monit Assess 186, 7655–7672 (2014). https://doi.org/10.1007/s10661-014-3957-5

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  • DOI: https://doi.org/10.1007/s10661-014-3957-5

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