5A_1_Land evaluation techniques comparing fuzzy ahp with ideal point methods

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5A_1_Land evaluation techniques comparing fuzzy ahp with ideal point methods

  1. 1. Geography Department <br />Land Evaluation Techniques Comparing Fuzzy AHP with Ideal Point methodsMukhtar Elaalem Dr: Alexis ComberProf Dr: Pete Fisher <br />http://www.le.ac.uk/geography/staff/pg_elaalem.html<br />
  2. 2. Overview<br />Introduction<br />Methodology<br />Results<br />Summary <br />Conclusion <br />
  3. 3. 1.Introduction<br />Land resources are gradually becoming limited <br />Increases in population pressure on these natural resources<br />Increased pressure is particularly problematic in countries with restricted water and soil resources such as developing countries<br />Increased food production needed<br />
  4. 4. 1.Introduction<br />Land evaluation systems in developing countries frequently makes little use of local knowledge . <br />There are many land evaluation techniques which are widely used in developing countries.<br />The FAO framework with the Boolean technique is the most popular one.<br /><ul><li>The use of the Boolean logic theory to land evaluation methods has criticized by many authors (Burrough, et al., 1992; Davidson et al., 1994; Baja, et al., 2006).</li></li></ul><li>1.Introduction <br />Boolean<br />boundaries between the classes are clearly defined<br />Does not always reflect reality <br />many elements not so naturally defined.<br />Alternative:<br />Analytical Hierarchy Process (AHP)<br />Ideal Point methods<br />This paper compares Fuzzy AHP and Ideal Point applied to a land suitability problem<br />
  5. 5. 2. Methodology<br /><ul><li>Factors determining land-use suitability analysis for wheat in the study area:</li></ul>Erosion Hazard; <br />Soil characteristics<br /> Topographic<br />Weighting parameters <br />A pairwise comparisons statistical analysis (table 1).<br />
  6. 6.
  7. 7. 2.Methodology/ Model structure<br />Land evaluation model using Fuzzy AHP <br />Convert the raw data (land characteristics) into standardized criterion scores scale using different fuzzy membership function models.<br /> Generation standardized criterion map layers<br /> Derivation weighted standardized fuzzy criterion map layers.<br />Derivation fuzzy rating map layers<br />Generation the final land suitability map<br />
  8. 8. 2.Methodology/ Model structure<br />Land evaluation model using an Ideal Point<br />Determine the maximum and the minimum values for each of the weighted standardized map layer for each land characteristic<br /> Using the separation measure to compute “the distance” between the positive ideal point and each alternative<br />An application the similar separation measure to determine “the distance” between the negative ideal point and each alternative<br />Create maps from compute the relative closeness to the ideal point<br />Ranking the alternatives and create the final land suitability map<br />
  9. 9. 3.Results<br /> Fuzzy AHP map an Ideal Point map<br />
  10. 10. 3.Results<br /><ul><li>Comparison of the Results:
  11. 11. The result of the two models were cross-tabulated.
  12. 12. An overall accuracy and KHAT statistic analysis applied to assess the results (table 3). </li></li></ul><li>3.Results <br />
  13. 13. 4. Summary<br />Form this paper it can summarize that :<br />Few areas highly suitable classes have been found from the use the Fuzzy AHP and Ideal Point classifications.<br />Few areas less suitable classes have been found from the use the Fuzzy AHP and Ideal Point classifications<br />Most locations moderate suitableclasses have been found from the use the Fuzzy AHP and Ideal Point classifications<br />There is little differences in the result:<br />An Ideal Point classification has some biasness towards negative and positive ideal values.<br />The high percentages of the KHAT accuracy and an overall accuracy shows that there is a good agreement between the maps.<br />
  14. 14. 5. Conclusion<br /><ul><li>From this paper, number of conclusions can be drown: </li></ul>Land characteristics affecting wheat production was very well organized and then assessed to fit into the framework of decision-making based on local knowledge<br />The use of the Fuzzy AHP and Ideal Point methods to the model of land evaluation has facilitated the incorporation of expert knowledge from different local experts and literature reviews.<br />Weighting land characteristics were made according to their relative importance with taken the crop requirement for wheat under local conditions into accounts.<br />
  15. 15. Thank you<br />

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