Advertisement

Modeling Earth Systems and Environment

, Volume 4, Issue 4, pp 1341–1353 | Cite as

Quantitative land evaluation based on fuzzy-multi-criteria spatial model for sustainable land-use planning

  • Mohamed A. E. AbdelRahman
  • Adel Shalaby
  • E. F. Essa
Original Article
  • 92 Downloads

Abstract

Evaluating land according to its suitability and soil mapping is an important contribution for agricultural land use planning. Therefore FAO system was used to produce suitability sub classes for horticultural and field crops. Land capability map was produced at a scale of 1:10,000 using soil information according to USDA criteria. All attributed insight analysis were ranked according to them priority and performed with analysis criteria to provide the spatial extent of soil suitability and capability. Also a new dimension was added in the spatial model to determine capability index for soil suitability to different irrigation methods. The overall accuracy of used spatial model is 89% and the validation was carried out through field work. The significance of the created model for mapping is being at a detailed survey level. The landforms were mapped using SRTM combined with sentinel satellite image of the studied area. Accordingly landforms were represented by 33 soil profiles collected in 2015. Another 32 auger profile samples were dug to identify the boundaries among landform units. The capability units were produced in association with geomorphology units. The study shows that 662.4 km2 (33%), 715.9 km2 (35.6%), 85.8 km2 (4.3%), 25.4 km2 (1.3%), 490.6 km2 (24.4%) and 30.0 km2 (1.5%) of the area were categorized in II, III, IV, and V, VI (sand dunes and quarries (and VII (Rock outcrops) land classes respectively. The produced suitability subclasses demonstrates that the land use must be planned for according to identified land capability classes (LCC) to maximize agricultural productivity and sustain the land resources for future generations.

Keywords

Land capability Land forms Soil data Spatial analysis Land use planning 

References

  1. AbdelRahman MAE, Tahoun SA, Abdel Bary EA, Arafat SM (2008) “Detecting land degradation processes using geo statistical approach in port said, Egypt”. Zagazig J Agric Res 35(6)Google Scholar
  2. AbdelRahman MAE, Natarajan A, Srinivasamurty CA, Hegde R (2016) Estimating soil fertility status in physically degraded land using GIS and remote sensing techniques inChamarajanagar district, Karnataka, India. Egypt J Remote Sens Space Sci.  https://doi.org/10.1016/j.ejrs.2015.12.002 CrossRefGoogle Scholar
  3. AbdelRahman MAE, Shalaby A, Aboelsoud MH et al.(2017) GIS spatial model based for determining actual land degradation status in Kafr El-Sheikh Governorate, North Nile Delta Model. Earth Syst Environ (2018) 4:359–372.  https://doi.org/10.1007/s40808-017-0403-z CrossRefGoogle Scholar
  4. Al-Mashreki MH, Akhir JBM, Rahim SA, Kadderi MD, Tukimat L, Haider AR (2011) Land suitability evaluation for sorghum crop in the Ibb Governorate, Republic of Yemen using remote sensing and GIS techniques. Aust J Basic Appl Sci 5(3):359–368Google Scholar
  5. Amir S, Fassil K, Mitiku H (2008) Land capability classification and growing period for GuilaAbena watershed in SassieTsedaEmba District in Eastern Tigray, Ethiopia. Nature Sci 8(9):237–243Google Scholar
  6. Atalay I (2016) A new approach to the land capability classification: case study of Turkey. Procedia Environ Sci 32:264–274CrossRefGoogle Scholar
  7. Azzam MA (2016) Land suitability evaluation for cultivation of some soils in western desert of egypt, el-minya governorate using gis and remote sensing. Int J Adv Res 4(2):486–503Google Scholar
  8. Bailey R (1974) Land capability classification of the lake Tahoe basin, California-Nevada: a guide for planning. U.S department of agriculture, pp 34Google Scholar
  9. Belay T (2003) Combining land capability evaluation, geographic information systems, and indigenous technologies for soil conservation in northern Ethiopia. East Afr Soc Sci Res Rev 19(2):23–53CrossRefGoogle Scholar
  10. Bibby J, Douglas H, Thomasson A, Robertson J (1991) Land capability classification for agriculture. Macaulay Land Use Research Institute, AberdeenGoogle Scholar
  11. Bui NE (2004) Soil survey as knowledge system. Geoderma 120:17–26CrossRefGoogle Scholar
  12. Elewa AMT, El-Sayed E, El-Kashouty M, Morsi M (2013) Quantitative study of surface and groundwater systems in the Western Part of the River Nile, Menia Governorate, Upper Egypt: water quality in relation to anthropogenic activities. Greener J Phys Sci 3(6):212–228Google Scholar
  13. Elsheikh RFA (2015) GIS based land evaluation decision support system. Acad J Agric Res 3(12):369–380Google Scholar
  14. FAO, (1990).Guidelines for soil description, 3rd edn (revised). FAO, RomeGoogle Scholar
  15. Fresco LO, Using land evaluation and farming systems methods for planning sustainable land use—an example from Costa Rica., Land use planning applications. In: Proceedings FAO Expert Consultation, Rome, 10–14 December 1990, World Soil Resources—Reports, 1991, No. 68, pp. 153–157Google Scholar
  16. Hamade S (2012) Evolution socio-économique et dégradation des terres et des eaux dubassin versant de l’Oronte au Liban:Cas de la région de Hermel. Université Paris Ouest Nanterre. ParisGoogle Scholar
  17. Klingebiel AA (1991) Development of soil survey interpretations. Soil Surv Horiz 32(3):53–66CrossRefGoogle Scholar
  18. Korany E, Sakr S, Darwish M, Morsy S (2006) Hydrogeologic modeling for the assessment of continuous rise of groundwater levels in the quaternary aquifer, Nile Valley, Egypt: case study. In: Proceedings of the 8th International Conference on the Geology of the Arab World (GAW8), Cairo University, July 2006, 703–711Google Scholar
  19. Lanen Van HAJ, Van D, Reinds CA, G. J. and Koning GHJ (1992) Physical land valuation methods and GIS to explore the crop growth potential and its effects within the European communities. Agric Syst 38:307–328CrossRefGoogle Scholar
  20. Martin D, Saha SK (2009)Land evaluation by integrating remote sensing and GIS for cropping system analysis in a watershed. Curr Sci 96:4Google Scholar
  21. Moneim AAA, Fernández-Álvarez JP, El Ella EMA, Masoud AM (2016) Groundwater management at West El-Minia Desert Area, Egypt using numerical modeling. J Geosci Environ Protect 4:11.  https://doi.org/10.4236/gep.2016.47008 (Article ID: 68931)CrossRefGoogle Scholar
  22. Monserud R (1990) Methods for comparing global vegetation maps, Report WP-90-40. IIASA, LaxenburgGoogle Scholar
  23. Oz B, Friedman J (2001) Allelopathic bacteria and their impact on higher plants. Crit Rev Microbiol 27:41–55CrossRefGoogle Scholar
  24. Panhalkar S (2011) Land capability classification for integrated watershed development by applying remote sensing and GIS techniques. ARPN J Agric Biol Sci 6(4):46–55Google Scholar
  25. Panhalkar S, Mali S, Pawar C (2014) Land capability classification in Hiranyakeshi basin of Maharashtra (India): a geo-informatics approach. IJETR 2(6):18–21Google Scholar
  26. Rees D (1995) A land capability study of the Cassilis Valley, Swifts Creek. Centre for land protection research. Technical report No. 27Google Scholar
  27. Rossiter GD (1996a) A theoretical frame work for land evaluation. Goederma 72:165–190CrossRefGoogle Scholar
  28. Rossiter DG (1996b) A theoretical framework for land evaluation (with discussion). Geoderma 72:165–202 (Elsevier Scientific)CrossRefGoogle Scholar
  29. Rossiter DG, Van Wambeke AR (1997) Automated land evaluation system ALES version 4.65 user’s manual. Management 6(1):7–20Google Scholar
  30. Rushemuka PN, Laurent B, Jeremias GM (2014) Soil science and agricultural development in Rwanda: state of the art. A review. Biotechnol Agron Soc Environ 18:142–154Google Scholar
  31. Saeid K, Bagherzadeh A, Ebrahimi H (2015) parametric approach to land evaluation for irrigation methods using Gis Model At Jolgeh-Rokh Plain, Iran. Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231–6345, 2015 vol 5 (S1), pp. 3699–3703/Karimi et al (Online) An Open Access, Online International Journal Available at: http://www.cibtech.org/sp.ed/jls/2015/01/jls.htm
  32. Schaetzl RJ, Anderson S (2005) Soils: genesis and geomorphology. Cambridge Univ Press, West Nyack, p 817CrossRefGoogle Scholar
  33. Soil Conservation Service US (1992) Washington, DC: Soil Conservation Service, pp 60–73Google Scholar
  34. Sys C, Verheye W (1974) Land evaluation for irrigation of arid regions by the use of the parameteric method. Trans 10th Int Cong Soil Sci Moscow 10 149–155Google Scholar
  35. Sys I, Van Ranst E, Debaveye J (1991) Land evaluation, part II. Methods in land evaluation. Agriculture publications no. 7 General Administration for Development Cooperation. Brussels, Belgium, pp 70–76Google Scholar
  36. Taffa T (2002) Soil and water conservation for sustainable agriculture. Mega Publishing Enterprise, Addis Ababa, pp 150Google Scholar
  37. Temesgen G, Taffa T, Mekuria A (2017a) Erosion risk assessment for prioritization of conservation measures in Geleda watershed, Blue Nile basin, Ethiopia. Environ Syst Res 6(1):1–14Google Scholar
  38. Temesgen G, Taffa T, Mekuria A, Abeyou W (2017b) Evaluation and prediction of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia. Environ Syst Res 6(17):1–15Google Scholar
  39. USDA (United States Department of Agriculture) (1961) Soil conservation service, land capability classification, agriculture hand book No. 210Google Scholar
  40. USDA (United States Department of Agriculture) (1973) Soil conservation service, land capability classification, agriculture hand book No. 210Google Scholar
  41. Van Diepen CA, Van Keulen H, Wolf J, Berkhout JAA (1991) Land evaluation: from intuition to quantification. Adv Soil Sci 15:139–204CrossRefGoogle Scholar
  42. Wielemaker WG, De Bruin S, Epema GF, Veldkamp A (2001) Significance and application of the multi-hierarchical landsystem in soil mapping. Catena 43:15–34CrossRefGoogle Scholar
  43. Wilson J, Gallant J (2000) Terrain analysis: principles and applications. Wiley, New YorkGoogle Scholar
  44. Wischmeier W, Smith D (1978) Predicting rainfall erosion losses—a guide to conservation planning. U.S. Department of Agriculture, Agriculture handbook No. 537Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mohamed A. E. AbdelRahman
    • 1
  • Adel Shalaby
    • 1
  • E. F. Essa
    • 2
  1. 1.National Authority for Remote Sensing and Space SciencesCairoEgypt
  2. 2.National Research CenterDokkiEgypt

Personalised recommendations