Spatial Decision Support Tool Research Articles

Enhancing water balance assessment in urban areas through high-resolution land cover mapping: Case study of Debrecen, Hungary

Land cover (LC) mapping in urban areas is one of the core applications in remote sensing (RS), and it plays an important role in modern urban planning and management. In order to support up-to-date simplified water balance calculation, LC modelling needs to be developed for precise and high-resolution operations to monitor rapidly expanding urban areas. This study provides a spatial decision support tool for urban water balance calculations considering hydrological parameters at pixel scale. The study is aimed to create a high-resolution LC map for more precise water balance calculations to identify and link the most important parameters, such as crop coefficient, for estimating crop evapotranspiration, runoff coefficients, and infiltration rate. Meteorological data from 2016 to 2019 were involved in evapotranspiration estimation. The study site is Debrecen, a city in northeast Hungary with a population of about 200,000. By integrating Landsat 8 imagery, Google Earth (GE), and Corine Land Cover (CLC), a LC map of 30 m resolution was created with 81.2 % overall accuracy (OA) and a coefficient of kappa greater than 0.78. For the classification of Landsat 8, seven classes were assigned (forests, sealed surfaces, areas with crop cover, grassland, semi-sealed surfaces, bare ground and surface water bodies). Classification results were validated by 101 ground truth samples using other satellite images and aerial photographs. Water balance parameters (i.e. surface runoff, infiltration and evapotranspiration) were then defined and calculated at a pixel scale and for larger areas. The technique developed in this study can also be utilized in other urban areas.

Informing climate adaptation strategies using ecological simulation models and spatial decision support tools

IntroductionForest landscapes offer resources and ecosystem services that are vital to the social, economic, and cultural well-being of human communities, but managing for these provisions can require socially and ecologically relevant trade-offs. We designed a spatial decision support model to reveal trade-offs and synergies between ecosystem services in a large eastern Cascade Mountain landscape in Washington State, USA.MethodsWe used process-based forest landscape (LANDIS-II) and hydrology (DHSVM) models to compare outcomes associated with 100 years of simulated forest and wildfire dynamics for two management scenarios, Wildfire only and Wildfire + Treatments. We then examined the strength and spatial distribution of potential treatment effects and trends in a set of resources and ecosystem services over the simulation period.ResultsWe found that wildfire area burned increased over time, but some impacts could be mitigated by adaptation treatments. Treatment benefits were not limited to treated areas. Interestingly, we observed neighborhood benefits where fire spread and severity were reduced not only in treated patches but in adjacent patches and landscapes as well, creating potential synergies among some resource benefits and services. Ordinations provided further evidence for two main kinds of outcomes. Positive ecological effects of treatments were greatest in upper elevation moist and cold forests, while positive benefits to human communities were aligned with drier, low- and mid-elevation forests closer to the wildland urban interface.DiscussionOur results contribute to improved understanding of synergies and tradeoffs linked to adaptation and restoration efforts in fire-prone forests and can be used to inform management aimed at rebuilding resilient, climate-adapted landscapes.

Engaging stakeholders in marine spatial planning for collaborative scoring of conflicts and synergies within a spatial tool environment

Collaborative spatial decision support tools can contribute with setups for including stakeholders into marine spatial planning (MSP) processes with the purpose of increasing trust in planning outcomes, facilitate knowledge co-creation and shared planning goals, and provide transparent, scientific, inclusive, and technical foundations for planning. A new collaborative spatial decision support setup based on the combination of functionalities from two spatial decision support tools called SEANERGY and Baltic Explorer was designed for and tested in a workshop in 2020 targeted local authorities, NGOs, and citizens in Denmark with an interest in MSP. While the setup needs further testing among a wider span of stakeholders to support a pluralistic approach, the findings illustrate promising potentials from ranking conflicts and synergies in collaborative settings to make marine activity interests spatially visible in MSP and gain an overview of opportunities for sea use multi-functionality in context-based, interactive, goal-oriented stakeholder processes. The use of a visual platform such as Baltic Explorer to systematically explore locations of marine uses was positively evaluated to facilitate the workshop conflict-synergy discussions. Challenges relate to how to deal with disagreements on conflict-synergy scores and the subjectivity of opinions, but the demonstrated flexible, quick, transparent way to test the sensitivity of spatial patterns to differences in input conflict-synergy scores is found to provide a promising setup for including stakeholder opinions through collaborative settings, a setup adjustable to supplementary large-scale, individual, more representative surveys as well.

Characterizing user needs for Beescape: A spatial decision support tool focused on pollinator health

Interactive maps can serve as powerful environmental decision-support tools. However, designing an interactive map that meets the needs of diverse constituencies is a challenge. In this article, we evaluate and characterize user needs for an interactive map and spatial decision-support tool called Beescape. Beescape is designed to visualize resources and environmental risks to bees and other pollinators (such as availability of nutritional resources from flowering plants and exposure to pesticides) in order to help users make informed decisions about managing bee populations and associated landscapes. We conducted a needs assessment workshop with twenty stakeholders from four user groups including beekeepers, growers, conservationists, and pollinator scientists to elicit their knowledge to guide future Beescape development. The results of the workshop identify current analytical gaps with the existing Beescape prototype, including the need for predictive and historical tools, more actionable data layers, finer-grain spatial data, and better explanations on what data represent and how they were created. Our findings on user's analytical, informational, and interface needs can be utilized to guide the future development of spatial decision support tools like Beescape, and our methodological approach may apply to other environmental informatics tools where it is important to design for multiple constituent user groups.

A comparison of tree planting prioritization frameworks: i-Tree Landscape versus spatial decision support tool

Different models as well as planting prioritization and optimization schemes based upon diverse ecological, social, and economic goals and preferences have been used to develop more efficient and effective tree planting schemes. We compare tree planting prioritization scenarios identified from i-Tree Landscape’s priority planting index to optimal scenarios identified from a spatially explicit multi-objective decision support framework at the census block group level in the Bronx, NY. We explore four scenarios with varying objectives considering populations below the poverty line, avoided runoff, and PM2.5 air pollutant removal monetary benefits. Results show that when prioritizing single objectives (e.g., PM2.5 air pollutant removal) using the same per area of tree canopy benefits from the spatially distributed modeling of ecosystem services, the two approaches recommend similar block groups for additional tree cover. Scenarios considering multiple objectives, however, result in different optimal solutions, with the decision support framework generally recommending more block groups for increased tree cover than i-Tree Landscape’s methodology. When the per area of tree canopy benefits from i-Tree Landscape are used as input in the i-Tree Landscape prioritization scenarios and the spatially distributed benefits used in the decision support framework scenarios, different optimal solutions are identified between the two approaches across all four scenarios, with i-Tree Landscape recommending fewer block groups for increased tree cover. Such a comparison will help inform the development of flexible multi-objective decision support tools to guide future greening initiatives towards prioritizing planting locations that maximize multiple objectives, as well as areas to preserve urban forests.

A Spatial Decision Support Approach for Flood Vulnerability Analysis in Urban Areas: A Case Study of Tehran

Preparedness against floods in a hazard management perspective plays a major role in the pre-event phase. Hence, assessing urban vulnerability and resilience towards floods for different risk scenarios is a prerequisite for urban planners and decision makers. Therefore, the main objective of this study is to propose the design and implementation of a spatial decision support tool for mapping flood vulnerability in the metropolis of Tehran under different risk scenarios. Several factors reflecting topographical and hydrological characteristics, demographics, vegetation, land use, and urban features were considered, and their weights were determined using expert opinions and the fuzzy analytic hierarchy process (FAHP) method. Thereafter, a vulnerability map for different risk scenarios was prepared using the ordered weighted averaging (OWA) method. Based on our findings from the vulnerability analysis of the case study, it was concluded that in the optimistic scenario (ORness = 1), more than 36% of Tehran’s metropolis area was marked with very high vulnerability, and in the pessimistic scenario (ORness = 0), it was less than 1%was marked with very high vulnerability. The sensitivity analysis of our results confirmed that the validity of the model’s outcomes in different scenarios, i.e., high reliability of the model’s outcomes. The methodical approach, choice of data, and the presented results and discussions can be exploited by a wide range of stakeholders, e.g., urban planners, decision makers, and hydrologists, to better plan and build resilience against floods.

An Analysis of Agricultural Systems Modelling Approaches and Examples to Support Future Policy Development under Disruptive Changes in New Zealand

Agricultural systems have entered a period of significant disruption due to impacts from change drivers, increasingly stringent environmental regulations and the need to reduce unwanted discharges, and emerging technologies and biotechnologies. Governments and industries are developing strategies to respond to the risks and opportunities associated with these disruptors. Modelling is a useful tool for system conceptualisation, understanding, and scenario testing. Today, New Zealand and other nations need integrated modelling tools at the national scale to help industries and stakeholders plan for future disruptive changes. In this paper, following a scoping review process, we analyse modelling approaches and available agricultural systems’ model examples per thematic applications at the regional to national scale to define the best options for the national policy development. Each modelling approach has specificities, such as stakeholder engagement capacity, complex systems reproduction, predictive or prospective scenario testing, and users should consider coupling approaches for greater added value. The efficiency of spatial decision support tools working with a system dynamics approach can help holistically in stakeholders’ participation and understanding, and for improving land planning and policy. This model combination appears to be the most appropriate for the New Zealand national context.

Developing a renewable energy planning decision-support tool: Stakeholder input guiding strategic decisions

Competing land-use demands associated with planning for renewables is resulting in growing social and political challenges. Spatial decision-support tools are being developed and applied to tackle some of these challenges by facilitating systematic identification of suitable development sites based on technical, environmental and socio-economic criteria. Nevertheless, decision-support tools are often developed with limited input from stakeholders affecting participative and accountable planning and decision-making. This paper aims to address this shortcoming and foster greater transparency in the development of support tools for renewable energy planning, and thus in siting decisions. It present and discusses a stakeholder-driven approach to the co-creation of an online decision-support tool that attends to planning policy, technical considerations, environmental protection and social concerns influencing renewable energy planning decisions in Ireland. This bottom-up approach, easily transferable to other jurisdictions, fosters proactive expert input, awareness raising and greater comprehensibility and acceptance of siting decisions. It also enables developing an interface that responds to users’ needs. The paper contributes to advancing renewable energy planning practice through effective and meaningful stakeholder engagement that supports transparent and accountable decisions from the outset. It also highlights ongoing data and technological shortcomings affecting the integration and operationalisation of stakeholders demands and needs, which signal priority areas of action to further advance the development of renewable energy decision-support tools.

An ecosystem service perspective on urban nature, physical activity, and health

Nature underpins human well-being in critical ways, especially in health. Nature provides pollination of nutritious crops, purification of drinking water, protection from floods, and climate security, among other well-studied health benefits. A crucial, yet challenging, research frontier is clarifying how nature promotes physical activity for its many mental and physical health benefits, particularly in densely populated cities with scarce and dwindling access to nature. Here we frame this frontier by conceptually developing a spatial decision-support tool that shows where, how, and for whom urban nature promotes physical activity, to inform urban greening efforts and broader health assessments. We synthesize what is known, present a model framework, and detail the model steps and data needs that can yield generalizable spatial models and an effective tool for assessing the urban nature–physical activity relationship. Current knowledge supports an initial model that can distinguish broad trends and enrich urban planning, spatial policy, and public health decisions. New, iterative research and application will reveal the importance of different types of urban nature, the different subpopulations who will benefit from it, and nature’s potential contribution to creating more equitable, green, livable cities with active inhabitants.

Operationalizing Urban Resilience to Floods in Island Territories—Application in Punaauia, French Polynesia

In the context of climate change and increasing urbanization, Small Island Developing States are increasingly vulnerable to natural disasters. In response to urbanization in at risk areas, the concept of territorial resilience has potential as an approach to urban flood issues. The objective of this research is to develop a spatial decision support tool based on a collaborative assessment method of territorial resilience. The proposed methodology consists of: the adaptation to the French Polynesian context, three existing resilience assessment methods applied to a case study in the Punaruu Valley’s (Punaauia, French Polynesia) and the use of geovisualization techniques: use of GIS for data processing and analysis, visualization, mapping and model processing. This methodology integrates the technical, urban and social components of the territory, while highlighting the various levers available to improve territorial resilience and facilitate its understanding through collaborative work efforts and the use of a visual tool. The results demonstrate the reproducibility of these methods for assessing resilience in French Polynesia. They underline the potential of a collaborative approach to highlight critical infrastructures and generate possible decision support to improve the territory’s ability to function despite a disruption and the ability to rebuild following this disruption.

Supporting integrative maritime spatial planning by operationalising SEANERGY – a tool to study cross-sectoral synergies and conflicts

ABSTRACT With growing pressures on marine ecosystems and on marine space, an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while separating conflicting marine human uses. The ArcMap toolbox SEANERGY is a new, cross-sectoral spatial decision support tool (DST) that enables maritime spatial planners to consider synergies and conflicts between marine uses to support assessments of co-location options. Cross-sectoral approaches are important to reach more integrative maritime spatial planning (MSP) processes. As this article demonstrates through a Baltic Sea analysis, SEANERGY presents a cross-sectoral use catalogue for MSP through enabling the tool users to answer important specific questions to spatially and/or numerically weight potential synergies/conflicts between marine uses. The article discusses to what degree such a cross-sectoral perspective can support integrative MSP processes. While MSP integrative challenges still exist, SEANERGY enables MSP processes to move towards developing shared goals and initiate discussions built on best available knowledge regarding potential use-use synergies and use-use conflicts for whole sea basins at once.

Strategic Habitat Conservation for Beach Mice: Estimating Management Scenario Efficiencies

ABSTRACTThe Perdido Key beach mouse (Peromyscus polionotus trissyllepsis), Choctawhatchee beach mouse (P. p. allophrys), and St. Andrew beach mouse (P. p. peninsularis) are 3 federally endangered subspecies that inhabit coastal dunes of Alabama and Florida, USA. Conservation opportunities for these subspecies are limited and costly. Consequently, well‐targeted efforts are required to achieve their downlisting criteria. To aid the development of targeted management scenarios that are designed to achieve downlisting criteria, we developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30‐m resolution across a portion of the Florida Panhandle. We then designed alternative management scenarios for a variety of habitat conditions for coastal dunes. Finally, we estimated how much area is needed to achieve the established downlisting criterion (i.e., habitat objective) and the amount of effort needed to achieve the habitat objective (i.e., management efficiency). The results suggest that after 7 years of post‐storm recolonization, habitat objectives were met for Perdido Key (within its Florida critical habitat) and Choctawhatchee beach mice. The St. Andrew beach mouse required 5.14 km2 of additional critical habitat to be protected and occupied. The St. Andrew beach mouse habitat objective might be achieved by first restoring protected critical habitat to good dune conditions and then protecting or restoring the unprotected critical habitat with the highest predicted probability of beach mouse presence. This scenario provided a 28% increase in management efficiency compared to a scenario that randomly protected or restored undeveloped unprotected critical habitat. In total, when coupled with established downlisting criteria, these quantitative and spatial decision support tools could provide insight into how much habitat is available, how much more is needed, and targeted conservation or restoration efforts that might efficiently achieve habitat objectives. © 2020 The Wildlife Society.

A GIS-based methodology to increase energy flexibility in building cluster through deep renovation: A neighborhood in Seville

Natural resource depletion, global warming and pollution pose substantial threats in prioritizing environmental policy, both for private organizations and for governments. Half the EU building stock is prior to energy efficiency standards, thus making it an urgent challenge for the EU to aim at decarbonized cities by 2050. Urban energy retrofitting at cluster level represents a major opportunity, as its current rate is lower than an annual 1%, 3% being the EU desirable rate.This paper presents a bottom-up methodology to assess energy flexibility of building clusters within a Geographic Information System (GIS) framework, applied on a district scale. Energy performance certificates and GIS-based data permit diagnosis and neighborhood selection. The methodology evaluates building cluster energy flexibility via energy demand reduction and PV production. The results show the building cluster hourly load profile for heating and cooling, and thermal comfort indexes. It is expected that this GIS-based methodology will become part of a wider spatial decision support tool for environmental public policies contributing to building stock transformation, from energy consumer to prosumer through deep renovation and renewable energy use. Finally, this methodology is adaptable to other climates, particularly within Spain.

Wind, sun, and wildlife: do wind and solar energy development ‘short-circuit’ conservation in the western United States?

Despite the trade-offs between renewable energy development, land use, humans, and wildlife, wind and solar development continues to transform the western US into a green energy landscape. While renewable energy reduces carbon emissions and reliance on fossil fuels, many studies have emerged on the associated ecological and social impacts of this technology. Here, we review the current state of knowledge on the nexus between wildlife conservation and energy development in the western US since 2010. We revisit pertinent ecological concepts presented in earlier reviews to assess how far the field has progressed in mitigating negative effects. Specifically, we examine: (i) recent trends in the literature on how wind and solar energy development impact wildlife in the US, (ii) how siting and design of development may maximize energy benefits while minimizing negative effects on wildlife, (iii) the availability and benefits of before-after control-impact studies, and ultimately (iv) how impacts of renewable energy development on wildlife may be mitigated. We also provide case studies on the desert tortoise and greater sage-grouse, two conservation-reliant umbrella species in the western US, to highlight efforts to mitigate the effects of solar and wind energy development, respectively. We recognize that many other species are affected by renewable energy development, but desert tortoises and sage-grouse are representative of the conflicts that need to be addressed. Our review concludes that mitigation can be improved via use of spatial decision support tools, applying novel wildlife deterrence and detection systems developed for existing installed facilities, and incorporating impact studies that provide managers with conservation metrics for evaluating different future development land-use scenarios.

Water Resources Management Strategies for Irrigated Agriculture in the Indus Basin of Pakistan

Agriculture of Pakistan relies on the Indus basin, which is facing severe water scarcity conditions. Poor irrigation practices and lack of policy reforms are major threats for water and food security of the country. In this research, alternative water-saving strategies are evaluated through a high spatio-temporal water footprint (WF) assessment (1997–2016) for the Punjab and Sindh provinces, which cover an irrigated area of 17 million hectares in the Indus basin of Pakistan. The SPARE:WATER model is used as a spatial decision support tool to calculate the WF and establish alternative management plans for more sustainable water use. The average water consumption (WFarea) is estimated to 182 km3 yr−1, composed of 75% blue water (irrigation water from surface water and groundwater sources), 17% green water (precipitation) and 8% grey water (water used to remove soil salinity or dilute saline irrigation water). Sugarcane, cotton, and rice are highly water-intensive crops, which consume 57% of the annual water use. However, WFarea can be reduced by up to 35% through optimized cropping patterns of the existing crops with the current irrigation settings and even by up to 50% through the combined implementation of optimal cropping patterns and improved irrigation technologies, i.e., sprinkler and drip irrigation. We recommend that the economic impact of these water-saving strategies should be investigated in future studies to inform stakeholders and policymakers to achieve a more sustainable water policy for Pakistan.

A spatial decision support system for enhancing resilience to floods: bridging resilience modelling and geovisualization techniques

Abstract. In the context of climate change and increasing urbanization, floods are considerably affecting urban areas. The concept of urban resilience may be an interesting means of responding to urban flood issues. The objective of this research is to propose a spatial decision support tool based on geovisualization techniques and a resilience assessment method. The goal is to localize the level of resilience modelled in different territories. The methodology proposed consists of integrating three resilience indicators applied to a case study in Avignon (Provence-Alpes-Côte d'Azur region, France) and the use of geovisualization techniques: using GIS for data processing and analysis, visualization, mapping, and model processing. The methodology integrates decision-making by identifying characteristics capable of improving urban resilience and facilitating its understanding using a visual tool. The results demonstrate the usefulness of modelling resilience using geovisualization techniques to identify the potential for local resilience; integrate local stakeholders into a process of clarifying the concept through the contribution of visualization; and consider easier access to this concept based on data analysis, processing and visualization through the design of maps.

Challenges of Spatial Decision-Support Tools in Urban Planning: Lessons from New Zealand’s Cities

Abstract Urban planning decision-makers face wicked problems and are required to make complex decisions regarding the functioning of cities. Spatial decision-support tools (SDSTs) have the potentia...

Tools for Sustainable Change

This research focuses on the ability of spatial decision-support tools (SDST) to transform urban regeneration processes through collaborative planning between authorities and communities. This article presents what was learned from the implementation of two SDST within planning authorities in Aotearoa, New Zealand. The first tool, Envision, enables the identification of suitable areas for urban regeneration; the second, ESP, focuses on the environmental and socio-economic assessment of regeneration scenarios at the neighbourhood scale. We use empirical observations from the implementation of these SDST in diverse planning authorities, to analyse the influence of local specificities and appropriate collaboration models for the development and adoption of the tools for decision-making and community engagement. We provide recommendations for future development and implementation of SDST to reinforce collaborative planning and local governance within urban regeneration processes.

Participatory development of digital support tools for local-scale energy transitions: Lessons from two European case studies

Spatial planning systems at local and regional levels are often not well-adapted to the growth of small-scale and local social innovations in renewable energy. Participatory decision support tools have been developed to support the implementation of many areas of environmental policy, but are less common in energy contexts. In response to this knowledge gap, we discuss, compare and contrast the participatory development of two different types of digital support tools for the cases of Spain and the Netherlands, leading to insights into the characteristics that local-level stakeholders find particularly desirable. We adopt an integrative approach, hybridizing implementation theory and action research for, respectively, analysis of implementation characteristics of key actors, and knowledge co-construction with participant stakeholders. The tools developed represent two extremes of the spatial decision support tool spectrum, a simple touchscreen application on the one hand (COLLAGE) and a more complicated spatial model on the other (APoLUS). COLLAGE was used and well-liked by stakeholders, whereas APoLUS was not adopted by the participant group, who nevertheless contributed much essential information to its development. We identify eight key differences between the two tools which shed light on the nature of bottom-up energy transition processes: 1: Target users; 2: Target scale of action; 3: Relevance to users’ needs; 4: Interactive quality; 5: Key emphasis; 6: Level of complexity; 7: Ease of communication of tool rationale; 8: Cost. The differences between these tools also relate to a recognized dichotomy in sustainability transition research, with complex spatial support systems like APoLUS tending towards descriptive-analytical modes of sustainability science and simpler tools like COLLAGE being more clearly related to transformational modes. Approaches to supporting local-scale energy transitions that are able to span both modes are likely to become increasingly relevant as the climate crisis evolves. We also identify a research gap between support tools for implementation of established policy and support tools for transformative actions at local scales, and suggest the study of digital “transition support tools” as a promising avenue for future research.

Urban green space qualities: An integrated approach towards GIS-based assessment reflecting user perception

For city dwellers urban green space is the primary source of contact with nature. Qualitative green space is increasingly perceived as an important factor for quality of life in urban areas and a key component of sustainable urban design and planning. In this study, the relation between different features of urban green spaces and perception of green space qualities was analyzed by combining the outcome of a survey on green space perception with GIS-based spatial metrics. A survey has been conducted among residents of the Brussels Capital Region and surroundings to assess the relative importance residents assign to different qualities of urban green spaces and how they value these qualities within visited spaces. Quietness, spaciousness, cleanliness and maintenance, facilities and feeling of safety are identified as important qualities of public green spaces, while naturalness, historical and cultural value are perceived as less important qualities. A GIS-based model was developed to infer naturalness, quietness and spaciousness as perceived by users of public green spaces from green space properties. Using variables describing biological value, land-cover composition, green space area and shape, good correlations were obtained between GIS-based assessment of naturalness and spaciousness and how green space users perceive these qualities. The model proposed may be useful for simulating green space development and improvement scenarios and assess their impact on perceived quality. Thus it may serve as a spatial decision support tool for improving the quality of urban green spaces.