Multiple criteria land use analysis

Antoine, J., Fischer, G., & Makowski, M. ORCID: (1997). Multiple criteria land use analysis. Applied Mathematics and Computation 83 (2) 195-215. 10.1016/S0096-3003(96)00190-7.

Full text not available from this repository.


Since the early 1980s, the Food and Agriculture Organization of the United Nations (FAO) and the International Institute for Applied Systems Analysis (IIASA) have been collaborating on expanding FAO's Agro-Ecological Zones (AEZ) methodology of land resources appraisal by incorporating decision support tools for optimizing the use of land resources. Initially, these tools consisted of the application of linear optimization techniques for analyzing land-use scenarios with regard to single objective functions, such as maximizing argicultural production or minimizing the cost of production under specific physical environmental and socio-economic conditions and constraints. Often, the specification of a single objective function does not adequately reflect the preferences of decision-makers, which are of a multiobjective nature in many practical problems dealing with resources. Multicriteria optimization approaches address problem definitions and solutions in a more realistic way and have recently been applied by FAO and IIASA in a land resources appraisal study in Kenya. In this study, optimization techniques coupled with multicriteria decision analysis (MCDA) techniques, using the Aspiration-Reservation Based Decision Support (ARBDS) approach, have been used to analyze various land use scenarios, considering simultaneously several objectives such as maximizing revenues from crop and livestock production, maximizing district self-reliance in agricultural production, minimizing costs of production and environmental damages from erosion. The main users of the new tool being developed, which combines AEZ and MCDA, are expected to be natural resources analysts and managers, land-use planners, ecologists, environmentalists, economists at national and regional levels, and agricultural extensionists at the local scale.

Item Type: Article
Research Programs: Modeling Land-Use and Land-Cover Changes (LUC)
Risk, Modeling, Policy (RMP)
Bibliographic Reference: Applied Mathematics and Computation; 83(2-3):195-215 [1997]
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:08
Last Modified: 27 Aug 2021 17:15

Actions (login required)

View Item View Item