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Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate

Romeijn, Harmen, Faggian, Robert, Diogo, Vasco and Sposito, Victor 2016, Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate, ISPRS international journal of geo-information, vol. 5, no. 6, pp. 1-16, doi: 10.3390/ijgi5060099.

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Title Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate
Author(s) Romeijn, Harmen
Faggian, RobertORCID iD for Faggian, Robert orcid.org/0000-0001-8750-3062
Diogo, Vasco
Sposito, VictorORCID iD for Sposito, Victor orcid.org/0000-0001-8833-2816
Journal name ISPRS international journal of geo-information
Volume number 5
Issue number 6
Start page 1
End page 16
Total pages 16
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2016
ISSN 2220-9964
Keyword(s) physical sciences
technology
geography, physical
remote sensing
physical geography
land suitability
analytical hierarchy process
fuzzy Analysis
fuzzy AHP
agriculture
climate
Summary Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods; Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained.
Language eng
DOI 10.3390/ijgi5060099
Field of Research 070102 Agricultural Land Planning
070104 Agricultural Spatial Analysis and Modelling
Socio Economic Objective 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30086966

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.