Spatial optimization for land use allocation: accounting for sustainability concerns

Land-use allocation has long been an important area of research in regional science. Land-use patterns are fundamental to the functions of the biosphere, creating interactions that have substantial impacts on the environment. The spatial arrangement of land uses therefore has implications for activity and travel within a region. Balancing development, economic growth, social interaction, and the protection of the natural environment is at the heart of long-term sustainability. Since land-use patterns are spatially explicit in nature, planning and management necessarily must integrate geographical information system and spatial optimization in meaningful ways if efficiency goals and objectives are to be achieved. This article reviews spatial optimization approaches that have been relied upon to support land-use planning. Characteristics of sustainable land use, particularly compactness, contiguity, and compatibility, are discussed and how spatial optimization techniques have addressed these characteristics are detailed. In particular, objectives and constraints in spatial optimization approaches are examined

A Participatory and Spatial Multicriteria Decision Approach to Prioritize the Allocation of Ecosystem Services to Management Units

Forest management planning can be challenging when allocating multiple ecosystem services (ESs) to management units (MUs), given the potentially conflicting management priorities of actors. We developed a methodology to spatially allocate ESs to MUs, according to the objectives of four interest groups—civil society, forest owners, market agents, and public administration. We applied a Group Multicriteria Spatial Decision Support System approach, combining (a) Multicriteria Decision Analysis to weight the decision models; (b) a focus group and a multicriteria Pareto frontier method to negotiate a consensual solution for seven ESs; and (c) the Ecosystem Management Decision Support (EMDS) system to prioritize the allocation of ESs to MUs. We report findings from an application to a joint collaborative management area (ZIF of Vale do Sousa) in northwestern Portugal. The forest owners selected wood production as the first ES allocation priority, with lower priorities for other ESs. In opposition, the civil society assigned the highest allocation priorities to biodiversity, cork, and carbon stock, with the lowest priority being assigned to wood production. The civil society had the highest mean rank of allocation priority scores. We found significant differences in priority scores between the civil society and the other three groups, highlighting the civil society and market agents as the most discordant groups. We spatially evaluated potential for conflicts among group ESs allocation priorities. The findings suggest that this approach can be helpful to decision makers, increasing the effectiveness of forest management plan implementationinfo:eu-repo/semantics/publishedVersio

Behavioral challenges in policy analysis with conflicting objectives

Public policy problems are rife with conflicting objectives: efficiency versus fairness, technical criteria versus political goals, costs versus multiple benefits. Multi-Criteria Decision Analysis provides robust methodologies to support policy makers in making tough choices and in designing better policy options when considering these conflicting objectives. However, important behavioral challenges exist in developing these models: the use of expert judgments, whenever evidence is not available; the elicitation of preferences and priorities from policy makers and communities; and the effective management of group decision processes. The extensive developments in behavioral decision research, social psychology, facilitated decision modeling, and incomplete preference models shed light on how decision analysts should address these issues, so we can provide better decision support and develop high quality decision models. In this tutorial I discuss the main findings of these extensive, but rather fragmented, literatures providing a coherent and practical framework for managing behavioral issues, minimizing behavioral biases, and optimizing the quality of human judgments in policy analysis models with conflicting objectives. I illustrate these guidelines with policy analysis interventions that we have conducted over the last decade for several organizations, such as the World Health Organization (WHO), the Food and Agriculture Organization of the United Nations (FAO), the UK Department of Environment Food and Rural Affairs (DEFRA), the Malaria Consortium/USAID, the UK National Audit Office, among others

Methods for Weighting Decisions to Assist Modelers and Decision Analysts: A Review of Ratio Assignment and Approximate Techniques

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions

Addressing forest and natural resources management planning with multicriteria approaches and group decision-making techniques

Doutoramento em Engenharia Florestal e dos Recursos Naturais / Instituto Superior de Agronomia. Universidade de LisboaSustainable forest management planning is challenged by the expectation for natural resources to provide a broad range of ecosystem services (ES). This can become more complex in joint management areas because the decision can involve several to many actors with different interests and objectives. The goal of this research is to facilitate forest management planning that best reflects the diversity of actors’ interests and that is better suited to face the challenges of the 21st century by (1) identifying the relevant actors and factors that impact forest management decisions (actor analysis); (2) assessing actors’ preferences for forest management models (FMMs) and ES (two-stage questionnaires); (3) developing a combined multicriteria decision analysis and group decision-making approach to quantify the criteria weights and rank seven FMMs (cognitive map, multicriteria questionnaire, and Delphi survey); (4) applying a Group Multicriteria Spatial Decision Support System approach to negotiate consensual solutions for seven ES, according to the objectives of four interest groups, and spatially prioritize the allocation of ES to forest management units. We report results from an application in Vale do Sousa, in northwestern Portugal. There was a consensus among the actors for a forest resilient to wildfires and a multifunctional forest that offers a diversity of ES but can be profitable. In two-stage questionnaires, actors ranked the FMM of pure eucalypt higher. However, in the multicriteria questionnaire, the FMM with the highest performance was the pedunculate oak and eucalypt was the least preferable. We found significant differences in priority scores between civil society and the other three groups, highlighting civil society and market agents as the most discordant groups. These findings contribute to a better understanding of forest management decisions. They can support joint management areas managers and other decision-makers in enhancing landscape-level, collaborative, and sustainable forest management planning, thus facilitating its implementation.N/

Strategic Decision Facilitation: Supporting Critical Assumptions of the Human in Empirical Modeling of Pairwise Value Comparisons

Modeling human decision-making is difficult. Decision-makers are typically primed with unique biases that widen the confidence interval of judgment. Therefore, it is important that the human process in the system being modeled is designed to alleviate damaging biases and assumptions in an effort to increase process consistency between decision-makers. In this experiment, it is hypothesized that coupling specific decision-facilitation methods with a specific scale range will affect the consistency between decision-makers. This article presents a multiphase experiment that examines a varying presentation mode as well as scale range to determine how value is determined in subsequent pairwise comparisons of alternatives against specific requirements. When considering subject value ratings of the expected rank order of alternative subgroups (indicating strong criteria independence), results show that subjects used consistent comparison ratios regardless of the scale range. Furthermore, when comparing the subgroups of expected rank order responses to the subgroups of biased responses, although ratios were different, the same general trend of comparison existed within subgroups. Providing evidence that careful selection of the presentation mode can facilitate more consistent value comparisons between compatible decision-makers allows for the identification of and adjustment of disparities due to bias and potential lack of incremental scaling detail. Furthermore, by creating decision processes that render more consistent cognitive behavior between decision-makers, tighter confidence intervals can be obtained, and critical assumptions can be validated

Setting rents in residential real estate: a methodological proposal using multiple criteria decision analysis

The real estate sector has been negatively affected by the recent economic recession, which has forced structural changes that impact property value and price. Recent pressures have also motivated reduced liquidity and access to credit, causing a drop in property sales and, thus, boosting the rental housing market. It is worth noting, however, that the rental housing segment is not with-out difficulties and complexity, namely in terms of legislation and rental value revaluation. In light of this reasoning, this study aims to develop a multiple criteria decision support system for calculation of residential rents. By integrating cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH), we also aim to introduce simplicity and transparency in the decision making framework. The practical implications, advantages and shortfalls of our proposal are also analyzed