Skip to main content

Assessment of Land Degradation Vulnerability Using GIS-Based Multicriteria Decision Analysis in Zakho District, Kurdistan Region of Iraq

  • Chapter
  • First Online:
Environmental Degradation in Asia

Abstract

The combination of GIS and multicriteria decision analysis approach was applied for assessment of land degradation vulnerability in Zakho District in Kurdistan Region of Iraq. First, a literature review was conducted to select effective parameters related to land degradation vulnerability. Three main groups of parameters, including physical, chemical, and socio-economic, were defined as effective criteria. The selected parameters were land use/land cover, slope, soil erosion rate, soil salinity, soil sodicity, soil organic carbon, soil acidity, and population density. The data were acquired from several sources, and the maps of the parameters were created in ArcGIS 10.3 version. The maps were standardized and adjusted in similar units and then aggregated using a weighted overlay method to show the spatial pattern of land degradation risk in the study area. The result indicated that only 7% be susceptible in the study area, while 50 and 43% were categorized as low and moderate levels, respectively. The land degradation risk is mainly due to natural factors such as slope and soil erosion. The result of this research could be useful for national organizations and agencies for sustainable land use planning and land management.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Oldeman L (1992) The global extent of soil degradation. In: ISRIC bi-annual report 1991–1992, 19–36. International Soil Reference and Information Centre, Wageningen

    Google Scholar 

  2. Global Environment Facility-GEF (2019) Land degradation report. https://www.thegef.org/sites/default/files/publications/gef_land_degradation_bifold_2019.pdf

  3. FAO (2011) Land degradation assessment in drylands: manual for local level assessment of land degradation and sustainable land management. Part 2: Field methodology and tools. food and agriculture organization of the United Nations, Rome, Italy

    Google Scholar 

  4. Pirsaheb M, Nouri M, Karimi H, Mustafa Y, Hossini H, Naderi Z (2020) Occurrence of residual organophosphorus pesticides in soil of some Asian countries, Australia and Nigeria. In: IOP conference series: materials, science and engineering, vol 737, p 012175

    Google Scholar 

  5. Neamat S, Karimi H (2020) A systematic review of GIS-based landslide hazard mapping on determinant factors from international databases. In: 2020 international conference on advanced science and engineering (ICOASE), 2020, pp 180–183. https://doi.org/10.1109/ICOASE51841.2020.9436611

  6. Vu QM, Le QB, Frossard E, Vlek PLG (2014) Socio-economic and biophysical determinants of land degradation in Vietnam: an integrated causal analysis at the national level. Land Use Policy 36:605–617. https://doi.org/10.1016/j.landusepol.2013.10.012

  7. Senjobi B, Ogunkunle A (2011) Effect of different land use types and their implications on land degradation and productivity in Ogun State, Nigeria. Int J Agric Biotechnol Sustain Dev 3(1):7–18

    Google Scholar 

  8. Joko T, Anggoro S, Sunoko HR, Rachmawati S (2017) Pesticides usage in the soil quality degradation potential in Wanasari subdistrict, Brebes, Indonesia. Appl Environ Soil Sci. https://doi.org/10.1155/2017/5896191

  9. Hostert P, Röder A, Hill J, Udelhoven T, Tsiourlis G (2003) Retrospective studies of grazing-induced land degradation: a case study in central Crete, Greece. Int J Remote Sens 24(20):4019–4034. https://doi.org/10.1080/0143116031000103844

    Article  Google Scholar 

  10. Fadhil AM (2013) Sand dunes monitoring using remote sensing and GIS techniques for some sites in Iraq. In: P SOC PHOTO-OPT INS 8762, PIAGENG 2013: intelligent information, control, and communication technology for agricultural engineering, vol 876206, Sanya, China. https://doi.org/10.1117/12.2019735

  11. Al-Quraishi AMF, Hu GD, Chen JG (2004) Land degradation detection, mapping, and monitoring in the northwestern part of Hebei Province, China, using RS and GIS Technologies. In: 2004, Map Asia 2004, the international conference on geospatial sciences, Beijing, China

    Google Scholar 

  12. Stocking MA, Murnaghan N (2013) A handbook for the field assessment of land degradation. Routledge

    Book  Google Scholar 

  13. Mitri G, Nader M, Van der Molen I, Lovett J (2014) 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. https://doi.org/10.1007/s10661-014-3957-5

    Article  Google Scholar 

  14. AbdelRahman MAE, Natarajan A, Hegde R, Prakash SS (2019) Assessment of land degradation using the comprehensive geostatistical approach and remote sensing data in GIS-model builder. Egypt J Remote Sens Space Sci 22(3):323–334. https://doi.org/10.1016/j.ejrs.2018.03.002

    Article  Google Scholar 

  15. Dubovyk O (2017) The role of remote sensing in land degradation assessments: opportunities and challenges. Eur J Remote Sens 50(1):601–613. https://doi.org/10.1080/22797254.2017.1378926

    Article  Google Scholar 

  16. Karimi H, Jafarnezhad J, Khaledi J, Ahmadi P (2018) Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran. Arab J Geosci 11(592). https://doi.org/10.1007/s12517-018-3940-5

  17. KouroshNiya A, Huang J, Karimi H, Keshtkar H, Naimi B (2019) Use of intensity analysis to characterize land use/cover change in the biggest island of Persian Gulf, Qeshm Island, Iran. Sustainability 11:4396

    Article  Google Scholar 

  18. KouroshNiya A, Huang J, Kazemzadeh-Zow A, Karimi H, Karimi B (2020) Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran. Environ Monit Assess 192:302. https://doi.org/10.1007/s10661-020-08274-6

    Article  Google Scholar 

  19. Karimi H, Jafarnezhad J, Kakhani A (2020) Landsat time-series for land use change detection using support vector machine: case study of Javanrud District, Iran. In: 2020 international conference on computer science and software engineering (CSASE). Duhok, Iraq, pp 128–131. https://doi.org/10.1109/CSASE48920.2020.9142087

  20. Mustafa YT (2020) Multi-temporal satellite data for land use/cover (LULC) change detection in Zakho, Kurdistan Region-Iraq. In: Al-Quraishi A, Negm A (eds) Environmental remote sensing and GIS in Iraq. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-030-21344-2_7

  21. Fadhil AM (2011) Drought mapping using geoinformation technology for some sites in the Iraqi Kurdistan Region. Int J Digit Earth 4(3):239–257. https://doi.org/10.1080/17538947.2010.489971

    Article  Google Scholar 

  22. Prakash S, Sharma MC, Kumar R, Dhinwa PS, Sastry KLN, Rajawat AS (2016) Mapping and assessing land degradation vulnerability in Kangra district using physical and socio-economic indicators. Spat Inf Res 24:733–744. https://doi.org/10.1007/s41324-016-0071-5

    Article  Google Scholar 

  23. Al-Quraishi AMF, Gaznayee HA, Crespi M (2021) Drought trend analysis in a semi-arid area of Iraq based on normalized difference vegetation index, normalized difference water index and standardized precipitation index. J Arid Land 13:413–430. https://doi.org/10.1007/s40333-021-0062-9

    Article  Google Scholar 

  24. Reith J, Ghazaryan G, Muthoni F, Dubovyk O (2021) Assessment of land degradation in semiarid Tanzania—using multiscale remote sensing datasets to support sustainable development goal 15.3. Remote Sens 13(9):1754. https://doi.org/10.3390/rs13091754

  25. Mzuri RT, Mustafa YT, Omar AA (2021) Land degradation assessment using AHP and GIS-based modelling in Duhok District, Kurdistan Region, Iraq. Geocarto Int. https://doi.org/10.1080/10106049.2021.1987534

    Article  Google Scholar 

  26. Imbrenda V, D’Emilio M, Lanfredi M, Simoniello T, Ragosta M, Macchiato M (2013) Integrated indicators for the estimation of vulnerability to land degradation, soil processes and current trends in quality assessment. Maria C. Hernandez Soriano, IntechOpen. https://doi.org/10.5772/52870. https://www.intechopen.com/books/soil-processes-and-current-trends-in-quality

  27. Malczewski J, Rinner C (2015) Multicriteria decision analysis in geographic information science. Springer, New York

    Book  Google Scholar 

  28. Karimi H, Soffianian A, Mirghaffari N, Soltani S (2016) Determining air pollution potential using geographic information systems and multi-criteria evaluation: a case study in Isfahan Province in Iran. Environ Process 3:229–246. https://doi.org/10.1007/s40710-016-0136-4

    Article  Google Scholar 

  29. Siefi S, Karimi H, Soffianian A, Pourmanafi S (2017) GIS-based multi criteria evaluation for thermal power plant site selection in Kahnuj county, SE Iran. Civil Eng Infrastruct J 50(1):179–189. https://doi.org/10.7508/ceij.2017.01.011

  30. Chehrazar F, Nahavandchi M, Balist J, Amiri M (2018) Capability Evaluation of tourism with fuzzy logic in mountain areas in GIS environment (case study: Hamedan City). J Environ Sci Stud 3(1):659–672

    Google Scholar 

  31. Karimi H, Amiri S, Huang J, Karimi A (2019) Integrating GIS and multi-criteria decision analysis for landfill site selection, case study: Javanrood County in Iran. Int J Environ Sci Technol 16:7305–7318. https://doi.org/10.1007/s13762-018-2151-7

    Article  Google Scholar 

  32. Karimi K, Soffianian A, Seifi S, Pourmanafi S, Ramin H (2020) Evaluating optimal sites for combined-cycle power plants using GIS: comparison of two aggregation methods in Iran. Int J Sustain Energy 39(2):101–112. https://doi.org/10.1080/14786451.2019.1659271

    Article  Google Scholar 

  33. Adil Z, Jabbar S, Sulaiman RH, Mustafa YT, Karimi H (2021) Land suitability analysis for identifying industrial zones in Duhok District, Kurdistan Region of Iraq. JoCEF 2(02):51–56

    Article  Google Scholar 

  34. Balist J, Nahavandchi M, Bidar GS (2021) Landfill site selection using fuzzy logic & AHP & WLC (case study: Razan city—Iran). JoCEF 2(01):01–07. https://doi.org/10.38094/jocef20129

    Article  Google Scholar 

  35. Karimi H, Hossini H, Amin AA (2022) Municipal landfill site selection and environmental impacts assessment using spatial multicriteria decision analysis: a case study. Comput Earth Environ Sci 235–244. https://doi.org/10.1016/B978-0-323-89861-4.00030-0

  36. Muhammed AH, Karimi H, Ghareeb BK, Neamat N, Mirzaei K (2020) Assessment of the quality of the environment in Duhok Province, Kurdistan Region of Iraq. JoCEF 1(1):20–24

    Article  Google Scholar 

  37. Wodaje ST (2016) Land degradation vulnerability assessment using GIS and remote sensing in Beshilo River Basin, Ethiopia. MSc Thesis, NTNU, The Netherlands

    Google Scholar 

  38. Haregeweyn N, Tsunekawa A, Poesen J, Tsubo M, Meshesha DT, Fenta AA, Nyssen J, Adgo E (2017) Comprehensive assessment of soil erosion risk for better land use planning in river basins: a case study of the Upper Blue Nile River. Sci Total Environ 574:95–108

    Article  CAS  Google Scholar 

  39. Imane H, Tahri M, Mohamed M, Mustapha H (2019) Efficiency of fuzzy analytic hierarchy process to detect soil erosion vulnerability. Geoderma 354:113853. https://doi.org/10.1016/j.geoderma.2019.07.011

    Article  Google Scholar 

  40. Sentinel-2_Team (2015) Sentinel-2 user hand book, European Space Agency

    Google Scholar 

  41. Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). U.S. Department of Agriculture-Agriculture Handbook No. 7

    Google Scholar 

  42. Sun W, Shao Q, Liu J, Zhai J (2014) Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China. CATENA 121:151–163

    Article  Google Scholar 

  43. USGS (2005)

    Google Scholar 

  44. Saeedi R, Safaei E, Lee Y, Lužnik J (2019) Oxidation of sulfides including DBT using a new vanadyl complex of a non-innocent o-aminophenol benzoxazole based ligand. Appl Organomet Chem

    Google Scholar 

  45. Osman KT (2013) Soil degradation, conservation and remediation. Springer, New York

    Google Scholar 

  46. Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98

    Google Scholar 

Download references

Acknowledgements

We thank Department of Agriculture of the University of Duhok for providing the required data and information.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hazhir Karimi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Karimi, H., Mustafa, Y.T., Hossini, H., Al-Quraishi, A.M.F. (2022). Assessment of Land Degradation Vulnerability Using GIS-Based Multicriteria Decision Analysis in Zakho District, Kurdistan Region of Iraq. In: Al-Quraishi, A.M.F., Mustafa, Y.T., Negm, A.M. (eds) Environmental Degradation in Asia. Earth and Environmental Sciences Library. Springer, Cham. https://doi.org/10.1007/978-3-031-12112-8_3

Download citation

Publish with us

Policies and ethics