DOI:10.1068/b31073 A review of rural land-use planning models <s> Discussion <s> Conflicting opinions from environmental advocates and economic interests on the best strategy for management of public lands often leaves land managers in a difficult position. Since ecosystem sustainability is in the long-term interest of each group, the establishment of nature reserves could simultaneously address both views. To promote sustainability, fragmentation of existing natural habitats should be avoided, since it is commonly recognized as being disruptive to the species adapted to these habitats. Therefore, when designing an efficient nature reserve, the compactness and contiguity of the land reserved is an essential consideration. A new formulation of the reserve selection problem is presented that explicitly addresses these issues; specifically, the model minimizes a weighted combination of compactness and contiguity measures subject to constraints on the minimal representation of each habitat class. Motivated by the ongoing reserve efforts in the large and diverse Klamath-Siskiyou region of southwestern Oregon and northwestern California, common heuristic search techniques are implemented and results compared on various simulated test problems. From these findings a new heuristic is developed that reduces solution time and increases solution quality. When applied to the Klamath-Siskiyou region, results are promising. <s> BIB001 </s> DOI:10.1068/b31073 A review of rural land-use planning models <s> Discussion <s> This paper presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on human-environment interactions. <s> BIB002
In this paper two phases in a land-use planning process have been identified; land evaluation and land-use allocation. The characteristics of the methods used at each stage have been analyzed, allowing the strengths and weaknesses of each to be examined. In land evaluation, the simplicity of the pre-FAO methods has meant that they are easily and broadly applied in real planning situations. Their weak points are the lack of consideration of socioeconomic factors and their applicability to a single global use. In addition, the land capability classification does not provide a quantified result and the parametric indices, despite offering a numerical result, are only apparently quantitative (Van Diepen et al, 1991) . The FAO framework has become the main point of reference for land evaluation. It is a flexible system which includes social and economic issues and permits the application of different techniques in order to match land use and units. For this reason, it demands complete development to be applied to a concrete situation and also the integration of other techniques, if quantitative results are desired. Amongst the post-FAO methods, LESA is one of those used, mainly in the United States, and there are even GIS modules which facilitate its application. Furthermore, it considers socioeconomic criteria and provides a numerical result. Its main drawback is that it is restricted to general agriculture use. The AEZ improves on the FAO framework in that it offers a more quantitative result, but is limited by not including the socioeconomic evaluation and by focusing on agricultural crops. The crop-simulation models provide precise and quantified results but their weakness lies in the difficulty of adopting existing models to the information available and to the geographic range of each land-use plan. The main drawback of those studies reviewed that are based on fuzzy set theory is that the evaluation is limited to soil factors, whereas the benefit is that they result in continuous suitability maps. The expert systems and neural networks can be designed to facilitate any type of output (discrete or continuous suitability classes) for any land use and on the basis of available information. However, there is still little experience of the application of these systems for land evaluation in comparison with the other methods mentioned. Multicriteria evaluation was one of the first techniques used for land-use allocation. These techniques are useful for structuring the problem, above all when the number of factors is high. Furthermore, they permit the sensitivity analysis of various parameters and, in some cases, allow multiple stakeholders to be considered. The complexity of certain mathematical operations count amongst their disadvantages  along with the limitation of the results, which are reduced to a ranking of a low number of spatial units evaluated. The integration of these techniques in GIS, which are within the scope of any GIS user, permit an increase in the number of spatial units evaluated. Another explicit and efficient technique for land-use allocation is mathematical programming, which also offers the possibility to carry out sensitivity analysis. However, mathematical programming models assume a linear relationship between the variables which may not be real, and the algorithm is specific for each particular situation in that it must be revised every time the application conditions vary. These models indicate how much land to assign to each use but not where to assign it, except in integerprogramming models, which find the optimum global spatial land-use allocation but fail when the number of units increase because they require much computing time. Spatial simulation models based on heuristic algorithms are used for the resolution of largescale problems, but do not provide optimal solutions but, rather, near optimal solutions. Amongst these algorithms, simulated annealing is that which finds the best solutions  BIB001 but it is slower than, for example, genetic algorithms. Other advantages of genetic algorithms are their capacity to yield multiple solutions and their applicability in parallel hardware. CA and ABM are used to simulate and understand land-use evolution rather than to find an optimum solution. CA have proven useful in modeling the ecological aspects of land-use change BIB002 , and ABM represent the impact of human decisionmaking on land use. Once developed, the majority of the spatial simulation models are easily adaptable to different contexts and can be used by nonexperts. In contrast, the expert systems are designed for a specific area and specific conditions, meaning that their application in a different situation requires a complex process of development and adaptation. Computer programs have been developed to make land-use planning processes easier. Within the context of land evaluation the most frequently used software has been ALES. Land-use allocation can be based on very diverse methodologies, for which different computer programs have been developed (LADSS, AEZWIN, GOAL-QUASI, etc). These programs are usually intended to solve or facilitate a specific phase in the planning process, although there are planning support systems (PSS) such as WhatIf  and Community Viz (www.communityviz.com) which include a greater number of phases. The description of these and other PSS, such as SLEUTH, INDEX, SMARTPLACES, etc, can be found in  and USEPA (2002) . These systems can use one or several of the aforementioned land-use planning techniques as their operational methods. However, the majority of them, despite considering nonurban uses, are designed for urban planning.