Land Suitability Evaluation Using Fuzzy Continuous Classification (A Case Study: Ziaran Region) | Zendy

Ali Keshavarzi | Zendy; Fereydoon Sarmadian | Zendy; Ahmad Heidari | Zendy; Mahmoud Omid | Zendy

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Land Suitability Evaluation Using Fuzzy Continuous Classification (A Case Study: Ziaran Region)

Author(s) -

Ali Keshavarzi,

Fereydoon Sarmadian,

Ahmad Heidari,

Mahmoud Omid

Publication year - 2010

Publication title -

modern applied science

Language(s) - English

Resource type - Journals

eISSN - 1913-1852

pISSN - 1913-1844

DOI - 10.5539/mas.v4n7p72

Subject(s) - fuzzy logic , analytic hierarchy process , computer science , land use , fuzzy set , set (abstract data type) , statistics , data mining , environmental science , mathematics , operations research , artificial intelligence , civil engineering , engineering , programming language

Because conventional Boolean retrieval of soil survey data and logical models for assessing land suitability treat both spatial units and attribute value ranges as exactly specifiable quantities, they ignore the continuous nature of soil and landscape variation and uncertainties in measurement which can result in the misclassification of sites that just fail to match strictly defined requirements. The objective of this research is to apply fuzzy set theory for land suitability evaluation in Ziaran region in Qazvin province, Iran. The study area was divided into 15 land units and 9 land characteristics considered to be relevant to irrigated wheat. The weight contributions of individual characteristics to observed yield were determined using the analytic hierarchy process (AHP). The use of the fuzzy technique is helpful for land suitability evaluation and classification of continuous variation, especially in applications in which subtle differences in land characteristics are of a major interest.

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