An Integrated Uncertainty and Sensitivity Analysis for Spatial Multicriteria Models (Short Paper)

This paper introduces an integrated Uncertainty and Sensitivity Analysis (US-A) approach for Spatial Multicriteria Models (SMM). The US-A approach evaluates uncertainty and sensitivity by considering both criteria values and weights, providing spatially distributed measures. A geodiversity assessment case study demonstrates the application of US-A, identifying influential inputs driving uncertainty in specific areas. The results highlight the importance of considering both criteria values and weights in analyzing model uncertainty. The paper contributes to the literature on spatially-explicit uncertainty and sensitivity analysis by providing a method for analyzing both categories of SMM inputs: evaluation criteria values and weights, and by presenting a novel form of visualizing their sensitivity measures with bivariate maps

Parameter-free aggregation of value functions from multiple experts and uncertainty assessment in multi-criteria evaluation

This paper makes a threefold contribution to spatial multi-criteria evaluation (MCE): firstly by presenting a new method concerning value functions, secondly by comparing different approaches to assess the uncertainty of a MCE outcome, and thirdly by presenting a case-study on land-use change. Even though MCE is a well-known methodology in GIScience, there is a lack of practicable approaches to incorporate the potentially diverse views of multiple experts in defining and standardizing the values used to implement input criteria. We propose a new method that allows generating and aggregating non-monotonic value functions, integrating the views of multiple experts. The new approach only requires the experts to provide up to four values, making it easy to be included in questionnaires. We applied the proposed method in a case study that uses MCE to assess the potential of future loss of vineyards in a wine-growing area in Switzerland, involving 13 experts from research, consultancy, government, and practice. To assess the uncertainty of the outcome three different approaches were used: firstly, a complete Monte Carlo simulation with the bootstrapped inputs, secondly a one-factor-at-a-time variation, and thirdly bootstrapping of the 13 inputs with subsequent analytical error propagation. The complete Monte Carlo simulation has shown the most detailed distribution of the uncertainty. However, all three methods indicate a general trend of areas with lower likelihood of future cultivation to show a higher degree of relative uncertainty

Enhancing geographical information systems capabilities with multi-criteria evaluation functions

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Stochastic multicriteria acceptability analysis as a forest management priority mapping approach based on airborne laser scanning and field inventory data

The mapping of ecosystem service (ES) provisioning often lacks decision-makers' preferences on the ESs pro-vided. Analyzing the related uncertainties can be computationally demanding for a landscape tessellated to a large number of spatial units such as pixels. We propose stochastic multicriteria acceptability analyses to incorporate (unknown or only partially known) decision-makers' preferences into the spatial forest management prioritization in a Scandinavian boreal forest landscape. The potential of the landscape for the management alternatives was quantified by airborne laser scanning based proxies. A nearest-neighbor imputation method was applied to provide each pixel with stochastic acceptabilities on the alternatives based on decision-makers' preferences sampled from a probability distribution. We showed that this workflow could be used to derive two types of maps for forest use prioritization: one showing the alternative that a decision-maker with given pref-erences should choose and another showing areas where the suitability of the forest structure suggested different alternative than the preferences. We discuss the potential of the latter approach for mapping management hotspots. The stochastic approach allows estimating the strength of the decision with respect to the uncertainty in both the proxy values and preferences. The nearest neighbor imputation of stochastic acceptabilities is a computationally feasible way to improve decisions based on ES proxy maps by accounting for uncertainties, although the need for such detailed information at the pixel level should be separately assessed.Peer reviewe

Parameter-free aggregation of value functions from multiple experts and uncertainty assessment in multi-criteria evaluation

This paper makes a threefold contribution to spatial multi-criteria evaluation (MCE): firstly by presenting a new method concerning value functions, secondly by comparing different approaches to assess the uncertainty of a MCE outcome, and thirdly by presenting a case-study on land-use change. Even though MCE is a well-known methodology in GIScience, there is a lack of practicable approaches to incorporate the potentially diverse views of multiple experts in defining and standardizing the values used to implement input criteria. We propose a new method that allows generating and aggregating non-monotonic value functions, integrating the views of multiple experts. The new approach only requires the experts to provide up to four values, making it easy to be included in questionnaires. We applied the proposed method in a case study that uses MCE to assess the potential of future loss of vineyards in a wine-growing area in Switzerland, involving 13 experts from research, consultancy, government, and practice. To assess the uncertainty of the outcome three different approaches were used: firstly, a complete Monte Carlo simulation with the bootstrapped inputs, secondly a one-factor-at-a-time variation, and thirdly bootstrapping of the 13 inputs with subsequent analytical error propagation. The complete Monte Carlo simulation has shown the most detailed distribution of the uncertainty. However, all three methods indicate a general trend of areas with lower likelihood of future cultivation to show a higher degree of relative uncertainty

Key challenges and meta-choices in designing and applying multi-criteria spatial decision support systems

There is an increasing use of multi-criteria spatial decision support systems in recent years for dealing with problems that have a spatial distribution of consequences. This growth might be explained by the widespread recognition that there are multiple and conflicting objectives to be considered in spatial planning (e.g. minimizing pollution to air, water and soil, increasing the acceptance of the projects, reducing implementation costs), by new requirements to consider societal values in the evaluation and to increase participation in decision processes, as well as by the crucial role that the spatial dimension plays in such problems. However, we argue in this paper that there are key challenges confronted by DSS designers who are developing such systems and by DSS practitioners who are employing them to support decision making. These challenges impose important meta-choices to designers and practitioners, which may lead to different contents of the evaluation model and to distinctive outcomes of the analysis. In this paper, we present and discuss these key challenges and the associated meta-choices. The contribution that we aim to provide to both researchers and practitioners can be summarized as follows: (i) an increased awareness about choices to be made in the design and implementation of these decision support systems; (ii) a better understanding about the available alternatives for each choice, based on recent developments in the literature; and (iii) a clearer appraisal about the inherent trade-offs between advantages and disadvantages of each alternative

Using spatial multi-criteria analysis as an appraisal tool for bus rapid transit trunk and feeder routes: a case study in the City of Tshwane, South Africa

Private car use around the world has grown increasingly over the last decades. One effect of this is traffic congestion, which results in various detrimental environmental, economic and social impacts. Public transport has been identified as an effective solution to congestion. In South Africa, investment into public transport has led to the implementation of full and partial Bus Rapid Transit (BRT) systems. The policy and implementation measures of these BRT systems have been modelled, to varying degrees, according to Colombia’s TransMilenio BRT. However, BRT systems in South Africa have not been as successful as TransMilenio. Failures of South African BRTs can be traced back to many reasons, one of which is an inadequate conduction of an ex ante appraisal. This dissertation intended to close a literature gap on the use of ex ante appraisal in South African transport projects. At the time of composing this thesis (February 2017), South Africa did not have a standard appraisal tool for the selection of appropriate transport projects and road-based public transport routes. This resulted in systems that were not designed in context and, hence, underperformed for the context in which they were implemented. The contextually insensitive design of BRTs and the effects thereof constituted the conceptual departure point for this research. Accordingly, this dissertation aimed to explore Spatial MultiCriteria Analysis (SMCA) as a viable appraisal tool for BRT routes. The City of Tshwane formed the study area of the investigation. SMCA is a decision-support tool that combines multi-criteria analysis (MCA) and geographic information systems for evaluating decision problems whose criteria and alternatives have spatially explicit dimensions. This method was chosen over traditional appraisal tools such as MCA and cost-benefit analysis as it is more suited to routing problems. Suitable evaluation criteria were identified from five themes that were chosen from international and local trends: equity, transport efficiency and economic, social and environmental impact. Ultimately, composite suitability maps were generated according to the aforementioned themes, and optimal trunk and feeder routes were extracted by means of a vector-based network analysis. Four trunk and four feeder routes were quantitatively and qualitatively analysed. The quantitative analysis of the route involved determining the average impedance, route length and travel time of a route. The qualitative analysis involved determining if the optimal routes had changed to current or planned city routes. On average, trunk routes obtained a higher average impedance than feeder routes. All optimal routes differed to some degree from planned city routes. Following the determination of optimal routes, an uncertainty analysis showed that trunk routes were more sensitive than feeder routes. The sensitivity analysis also showed that the transport efficiency theme criteria were the most sensitive criteria, causing the highest mean average impedance change of all criteria. Transport efficiency criteria are thus the most important criteria in finding optimal routes. The method of research adopted in this study can be reproduced in any contemporary South African city with plans for BRT. Furthermore, the method of research can be improved upon by investigating standard evaluation criteria to be included in an SMCA routing problem to ensure a uniform appraisal standard

Using spatial multi-criteria analysis as an appraisal tool for bus rapid transit trunk and feeder routes: a case study in the City of Tshwane, South Africa

Private car use around the world has grown increasingly over the last decades. One effect of this is traffic congestion, which results in various detrimental environmental, economic and social impacts. Public transport has been identified as an effective solution to congestion. In South Africa, investment into public transport has led to the implementation of full and partial Bus Rapid Transit (BRT) systems. The policy and implementation measures of these BRT systems have been modelled, to varying degrees, according to Colombia’s TransMilenio BRT. However, BRT systems in South Africa have not been as successful as TransMilenio. Failures of South African BRTs can be traced back to many reasons, one of which is an inadequate conduction of an ex ante appraisal. This dissertation intended to close a literature gap on the use of ex ante appraisal in South African transport projects. At the time of composing this thesis (February 2017), South Africa did not have a standard appraisal tool for the selection of appropriate transport projects and road-based public transport routes. This resulted in systems that were not designed in context and, hence, underperformed for the context in which they were implemented. The contextually insensitive design of BRTs and the effects thereof constituted the conceptual departure point for this research. Accordingly, this dissertation aimed to explore Spatial MultiCriteria Analysis (SMCA) as a viable appraisal tool for BRT routes. The City of Tshwane formed the study area of the investigation. SMCA is a decision-support tool that combines multi-criteria analysis (MCA) and geographic information systems for evaluating decision problems whose criteria and alternatives have spatially explicit dimensions. This method was chosen over traditional appraisal tools such as MCA and cost-benefit analysis as it is more suited to routing problems. Suitable evaluation criteria were identified from five themes that were chosen from international and local trends: equity, transport efficiency and economic, social and environmental impact. Ultimately, composite suitability maps were generated according to the aforementioned themes, and optimal trunk and feeder routes were extracted by means of a vector-based network analysis. Four trunk and four feeder routes were quantitatively and qualitatively analysed. The quantitative analysis of the route involved determining the average impedance, route length and travel time of a route. The qualitative analysis involved determining if the optimal routes had changed to current or planned city routes. On average, trunk routes obtained a higher average impedance than feeder routes. All optimal routes differed to some degree from planned city routes. Following the determination of optimal routes, an uncertainty analysis showed that trunk routes were more sensitive than feeder routes. The sensitivity analysis also showed that the transport efficiency theme criteria were the most sensitive criteria, causing the highest mean average impedance change of all criteria. Transport efficiency criteria are thus the most important criteria in finding optimal routes. The method of research adopted in this study can be reproduced in any contemporary South African city with plans for BRT. Furthermore, the method of research can be improved upon by investigating standard evaluation criteria to be included in an SMCA routing problem to ensure a uniform appraisal standard