Strengthening Participation using Interactive Planning Support Systems: A Systematic Review

Flacke, Johannes; Shrestha, Rehana; Aguilar, Rosa

doi:10.20944/preprints201911.0187.v1

Cited by 4 publications

(4 citation statements)

References 43 publications

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“…There have been several reviews focussed on the development and progress of PSS (15,16,18,(21)(22)(23)(24) and the sectors or elds of application (e.g., land use planning, water management, climate change adaptation) that PSS have been developed for and used in within the domain of spatial planning (25).…”

Section: Introductionmentioning

confidence: 99%

Exploring the Potential for Planning Support Systems to Bridge the Research-translation Gap Between Public Health and Urban Planning

Hooper

Boulangé

Arciniegas

et al. 2021

Preprint

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Background: There is consensus that planning professionals need clearer guidance on the features that are likely to produce optimal community-wide health benefits. However, much of this evidence resides in academic literature and not in tools accessible to the diverse group of professionals shaping our cities. This paper explores the role of planning support systems (PSS) to facilitate the translation and application of health evidence into urban planning and design practices to create healthy, liveable communities.Methods: A review of PSS software and studies featuring a planning support system with a built environment and health impact assessment for designing and creating healthy urban areas was undertaken. Customising existing software, a health impact PSS (the Urban Health Check) was then developed and applied to a real-world planning application with an industry partner allowing for: (i) automated calculation of built environment variables; (ii) “sketch planning” functionality; and (iii) a health impact indicator that estimates the probability of walking for transport. A participatory evaluation framework evaluated the "utility", "usability", and "usefulness" of the Urban Health Check.Results: Eleven PSS software applications were identified, of which three were identified as having the capability to undertake health impact analyses. Three studies met the inclusion criteria of presenting a planning support system customised to support health impact assessment with health impacts modelled or estimated due to changes to the built environment. Evaluation results indicated the Urban Health Check PSS helped in four key areas: visualisation of how the neighbourhood would change in response to a proposed plan; understanding how a plan could benefit the community; Communicate and improve understanding health of planning and design decisions that positively impact health outcomes; engagement – allowing community members to provide direct feedback and see the immediate implications of amendments to a proposed plan. Conclusions: The use of health-impact PSS have the potential to be transformative for the translation and application of health evidence into planning policy and practice, providing those responsible for the policy and practice of designing and creating our communities with access to quantifiable, evidence-based information about how their decisions might impact community health.

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Section: Introductionmentioning

confidence: 99%

Exploring the Potential for Planning Support Systems to Bridge the Research-translation Gap Between Public Health and Urban Planning

Hooper

Boulangé

Arciniegas

et al. 2021

Preprint

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“…An interactive PSS is hardware solutions in the form of digital table combined with geospatial mapping tools specifically dedicated to support group processes (Pelzer et al, 2014). Typically, an application of interactive PSS consists of interactive PSS tools and interactive PSS processes (Flacke et al, 2019). Interactive PSS tool usually consists of large-scale horizontal, touch enabled screen such as MapTable, which allows stakeholders to stand around the table, and a suite of geospatial tool or GIS software for map-based interaction (Figure 1).…”

Section: Interactive Planning Support Systemmentioning

confidence: 99%

Leveraging Citizen Science to Advance Interactive Spatial Decision Support Technology: A Swot Analysis

Shrestha¹,

Flacke

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Over three decades, the Spatial Decision Support System (SDSS) concept has evolved significantly exploiting information technology to assist decision maker in a variety of fields of research, development, and practice. With the communicative turn in planning, which emphasizes public participation in all levels of planning and decision making, these technologies have further matured to support participatory planning by means of supporting diverse stakeholders in the decision making process. However, for multiple reasons, SDSS are still in the domain of expert, largely failing to incorporate general citizens in its use and applications. On the same note, citizen science as a method of inquiry is gaining much attention in recent years to engage general citizens in the scientific research, thereby also empowering them to participate in the decisions of the issues affecting them. As such, it seems likely that citizen science shows great promise for advancing SDSS for achieving broad citizen engagement in planning and decision-making. This paper discusses the strengths, weaknesses, opportunities, threats (SWOT) of integrating citizen science with SDSS by analyzing existing literature on SDSS and citizen science. In particular, we explore the integration of aspects of citizen science in Interactive Planning Support System (PSS), as one form of SDSS to support wider citizen engagement.

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“…In a systematic review of interactive PSSs, Flacke et al (2020) found that while stakeholders are involved in the use of the PSSs, in many cases they have minimal input on design of the software systems being used. This distance from the inner workings of the software potentially contributes to them 'far from being used in everyday planning practice'.…”

Section: Introductionmentioning

confidence: 99%

“…In a systematic review of interactive PSSs, Flacke et al. (2020) found that while stakeholders are involved in the use of the PSSs, in many cases they have minimal input on design of the software systems being used.…”

Section: Introductionmentioning

confidence: 99%

Towards the collaborative development of machine learning techniques in planning support systems – a Sydney example

Lock

Bain

Pettit

2020

Environment and Planning B: Urban Analytics and City Science

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The rise of the term ‘big data’ has contributed to recent advances in computational analysis techniques, such as machine learning and more broadly, artificial intelligence, which can extract patterns from large, multi-dimensional datasets. In the field of urban planning, it is pertinent to understand both how such techniques can advance our understanding of cities, and how they can be embedded within transparent and effective digital planning tools, known as planning support systems. This research specifically focuses on two related contributions. First, it investigates the role of planning support systems in supporting a participatory data analytics approach through an iterative process of developing and evaluating a planning support system environment. Second, it investigates how specifically machine learning planning support systems can be co-designed by built environment practitioners and stakeholders in this environment to solve a real planning issue in Sydney, Australia. This paper presents the results of applied research undertaken through the design and implementation of four workshops, involving 57 participants who were involved in a co-design process. The research follows a mixed-methods approach, studying a wide array of measures related to participatory analytics, task load, perceived added value, recordings and observations. The results highlight recommendations regarding the design and evaluation of planning support system environments for co-design and their coupling with machine learning techniques. It was found that consistency and transparency are highly valued and central to the design of a planning support system in this context. General attitudes towards machine learning and artificial intelligence as techniques for planners and developers were positive, as they were seen as both potentially transformative but also as simply another technique to assist with workflows. Some conceptual challenges were encountered driven by practitioners' simultaneous need for concrete scenarios for accurate predictions, paired with a desire for predictions to drive the development of these scenarios. Insights from this work can inform future planning support system evaluation and co-design studies, in particular those aiming to support democracy enhancement, greater inclusion and more efficient resource allocation through a participatory analytics approach.

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Strengthening Participation using Interactive Planning Support Systems: A Systematic Review

Cited by 4 publications

References 43 publications

Exploring the Potential for Planning Support Systems to Bridge the Research-translation Gap Between Public Health and Urban Planning

Exploring the Potential for Planning Support Systems to Bridge the Research-translation Gap Between Public Health and Urban Planning

Leveraging Citizen Science to Advance Interactive Spatial Decision Support Technology: A Swot Analysis

Towards the collaborative development of machine learning techniques in planning support systems – a Sydney example

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