A software-aided workflow for precinct-scale residential redevelopment

Environmental Impact Assessment Review 60 (2016) 1–15

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Environmental Impact Assessment Review journal homepage: www.elsevier.com/locate/eiar

A software-aided workflow for precinct-scale residential redevelopment Stephen Glackin a, Roman Trubka b, Maria Rita Dionisio c,⁎ a b c

Swinburne University of Technology, Melbourne, Victoria, Australia Curtin University, Perth, Western Australia, Australia University of Canterbury, New Zealand

a r t i c l e

i n f o

Article history: Received 5 October 2015 Accepted 11 April 2016 Available online xxxx Keywords: Urban redevelopment Residential precinct Urban sustainability Geospatial tools Planning support systems

a b s t r a c t Growing urban populations, combined with environmental challenges, have placed significant pressure on urban planning to supply housing while addressing policy issues such as sustainability, affordability, and liveability. The interrelated nature of these issues, combined with the requirement of evidence-based planning, has made decision-making so complex that urban planners need to combine expertise on energy, water, carbon emissions, transport and economic development along with other bodies of knowledge necessary to make well-informed decisions. This paper presents two geospatial software systems that can assist in the mediation of complexity, by allowing users to assess a variety of planning metrics without expert knowledge in those disciplines. Using Envision and Envision Scenario Planner (ESP), both products of the Greening the Greyfields research project funded by the Cooperative Research Centre for Spatial Information (CRCSI) in Australia, we demonstrate a workflow for identifying potential redevelopment precincts and designing and assessing possible redevelopment scenarios to optimise planning outcomes. © 2016 Elsevier Inc. All rights reserved.

1. Introduction Greening the Greyfields (GtG) is a research project that was launched in 2011 as a partnership between Curtin University, Swinburne University, the CRCSI and a number of state and local government authorities in Australia to develop tools and strategies to address suboptimal infill patterns in existing suburbs and curtail the effects of urban sprawl. In 2014 the project was extended to include the University of Canterbury in New Zealand and the City of Christchurch to assist it in recovering from the devastating effects of the earthquakes that occurred there in 2010 and 2011. This paper presents the software-aided workflow of the GtG project, demonstrated by two software applications that were developed as research outputs, Envision and Envision Scenario Planner (ESP). The systems were developed to assist urban planners, decision makers, and other end users to plan for precinct-scale redevelopment in Greyfield1 residential areas as a means to revitalising neighbourhoods and optimising infill housing. For that, this paper comprises five parts: (1) the research background, contextualising the general objectives and components of the project; (2) the Envision system, describing each of its four geospatial tools for redevelopment site identification; (3) the ESP system, describing its functionalities for designing

⁎ Corresponding author. E-mail addresses: [email protected] (S. Glackin), [email protected] (R. Trubka), [email protected] (M.R. Dionisio). 1 Mid-suburban residential areas are characterised by physical, environmental and socio-economic deterioration (Newton, 2010, Newton et al., 2012).

http://dx.doi.org/10.1016/j.eiar.2016.04.002 0195-9255/© 2016 Elsevier Inc. All rights reserved.

redevelopment scenarios; (4) the combined workflow of Envision and ESP, illustrated by two use cases with distinct redevelopment strategies; and (5) discussion on the implementation of GtG and its software systems' adoption by local government. 1.1. Background Greening the Greyfields (GtG) was initiated as a research project to address the significant potential for urban regeneration in established middle suburbs of urban areas, and thus redirect housing growth inward and away from greenfield areas (Newton, 2010; Newton et al., 2012). As first discussed by Newton (Newton, 2010), the ‘Greyfields’ research attempts to provide geospatial tools and mechanisms whereby ad-hoc urban infill can be more strategically managed and lead to more sustainable outcomes for urban growth. The complexity of urban infill is a consequence of multiple private ownership, the difficulty of coordinating landowners to work co-operatively and the lack of an established Greyfield residential redevelopment financial model. This is particularly the case when attempting to plan for scenarios that require significant amounts of land. The attractiveness of Greyfield redevelopment is also undermined by the comparative ease of greenfield and brownfield redevelopment that has been the convention for housing growth (Newton et al., 2012). The aims of the project were fourfold (Fig. 1). Firstly it focuses the benefits of urban agglomeration and the avoidable costs provided by infill (Trubka, 2011). This work examined the economic and environmental benefits of Greyfield intensification; illustrating the employment productivity benefits of more consolidated urban development

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Fig. 1. Greening the Greyfields project aims and outputs.

and the costs avoided by leveraging existing infrastructure capacity for new housing. The second aim was to develop software tools to enable stakeholders (primarily local governments) to determine where potential urban regeneration precincts could exist, and where market conditions show significant transformation and indicate a likelihood of redevelopment. In the scope of this work, precincts are defined as isolated areas of between 5 and 500 land parcels that contain significant numbers of contiguous redevelopable lots that can potentially be amalgamated. The first system developed, Envision, utilises property-level valuations data, a range of urban planning datasets and census demographic data, allowing users to specify a set of criteria for potential future regeneration, and enable the identification of lots that are highly redevelopable (Newton et al., 2012; Glackin, 2013). This is the first tool we demonstrate and is described in Section 2. The third aim of the project was to develop a system for designing and visualising precinct redevelopment scenarios in 3D and assessing their performance. This tool, Envision Scenario Planner (ESP), was to demonstrate outcomes of various redevelopment scenarios; from a businessas-usual (BAU) lot subdivision to an advanced precinct-wide urban regeneration. The sustainability focus of the project established requirements for specific reporting categories, such as embodied and operating carbon, energy demand, water demand, storm-water, capital and operating costs and transport, as the key performance indicators of a precinct's

performance. Due to the variety of potential users, the software system had to be highly visual and user friendly (Pettit et al., 2014). Aiming at improving stakeholder engagement, the proposed software tools were required to integrate an economic and environmental assessment (Rega and Baldizzone, 2015) and visualisation of redevelopment scenarios. It also had to be intuitive for non-expert users, such as decision-makers, community members, or other parties involved in neighbourhood regeneration lacking expert domain knowledge in the use of GIS technologies, or in performance assessment. ESP is the second software application discussed and demonstrated in Section 3 of this paper. The final aim corresponds to the project implementation, targeting the identification of statutory obstacles to precinct redevelopment in the Greyfields to propose legal mechanisms to facilitate urban regeneration. This stage also looks at the development of community engagement processes in the participating LGAs, enabling landowners and other parties involved in redevelopment to achieve better housing outcomes on amalgamated lots. Additionally, the project also aimed to facilitate the negotiation processes between all the parties and local governments, by creating showcases of better design outcomes and the financial benefits of integrated residential regeneration precincts, as demonstrated by Newton et al. (2012). The final stage of the project is underway, with significant interest being generated in Western Australia, Victoria, and New Zealand. The

Fig. 2. Envision MCE-1 user interface with proximity to train station, main road and district shopping centre as the selected decision criteria.

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Fig. 3. Example MCE-1 output from the decision criteria and weightings from Fig. 2.

software systems are currently being implemented nationally and aim to illustrate the potential outcomes that can occur through the assessment and design of residential precincts. Section 4 of this paper details the workflow of both systems, Envision and ESP, and provides two cases where the geospatial tools successfully addressed the competing needs of various local policies, and how they were used to generate discussion points for better informed precinct planning and design. 2. The Envision system Envision was designed as a web-based decision support system (DSS) that can combine datasets to support urban planning and decision-making. Envision helps to address the debate on the potential areas for strategic infill, to identify specific land parcels that have a considerable probability or potential of being redeveloped or subdivided in the near future, and to assess the economic viability of proposed redevelopment scenarios. The system is accessible through the Australian Urban Research Infrastructure Network (AURIN) (AURIN, 2010), and integrates four geospatial tools. The first two tools facilitate strategic site identification by way of multi-criteria evaluation (MCE), with the first based on individual land parcel data, and the second on aggregated statistical data from census sources (such as the Australian Bureau of Statistics (ABS), Statistics New Zealand and other state government sources). The third tool enables precinct identification, allowing users to locate properties that present particular potential for redevelopment. The fourth tool analyses the economic viability of redevelopment scenarios that may be the most appropriate for specific areas of the city, considering a number of redevelopment business models and housing typologies.

MCE is an analysis technique that allows integration of a set of variables (termed ‘decision criteria’) by normalising values from a zero to one scale, weighting them in terms of their relative importance, and combining them to form a composite index or summary score (Nyerges and Jankowski, 2010). Envision's MCE-1 utilises propertylevel data with indicators on property characteristics and proximity to strategic assets like train stations and schools (Fig. 2), while MCE-2 utilises small census (SA1) zones with indicators on tenure, age, income, car ownership, journey to work methods and more. Fig. 2 provides an example of the MCE-1 interface with proximity to train station’ (weighting of 9), ‘proximity to main road’ (weighting of 7) and ‘proximity to district centre’ (weighting of 5) selected for analysis.2 The output of this multi-criteria evaluation scenario is shown in Fig. 3. The range of decision criteria is broad, incorporating indicators derived from property, planning, infrastructure and census datasets, necessitating users to select those that are most pertinent to specific regeneration strategies (in their local governments or institutional bodies) and weight them accordingly. Envision's MCE tools allow simultaneous analysis of ecological, geographical, infrastructural, and economic factors, and produces maps that illustrate the result of multiple interests. This is a powerful functionally to help LGAs in facilitating consensus in groups with potentially divergent perspectives, such as codesign sessions, charrette processes, workshops in local governments with officers from different departments, or discussions between state and local governments. In effect, the MCE tools allow the production of clear ‘artefacts’, which is an essential output of co-design iterations (Sanders and Stappers, 2014; Bratteteig and Wagner, 2012), while addressing the interdisciplinary tensions between the different scopes of policy making. Additionally, as the user interface for each analysis area is metadata driven, shortfalls in data can be overcome when new datasets become available by adding them to the system and updating the metadata. The third tool is a precinct identification tool, allowing users to query property attributes to locate land parcels that show a high likelihood of redevelopment. By selecting cut-off values for a number of indicators, users can run queries based on property level data to identify clusters of lots that might be market-ready for redevelopment, and generate maps such as the one shown in Fig. 4. Some of the indicators in the system that are most significantly related to redevelopment include: • Redevelopment Potential Index (RPI) — a ratio of Unimproved Land Value (ULV) to Capital Improved Value (CIV), where values close to

Fig. 4. Example output of the Precinct Identification tool, showing dwellings with high redevelopment potential that are not strata titled or in a flood zone.

2 The criteria and correspondent weighting can be different from case to case, and should aim to represent specific urban development strategies. The case provided is meant to only set an example.

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Fig. 5. Interface of the Viability tool that estimates the costs of a development and compares them with local sales volumes and prices.

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one indicate that little to no value remains in the structure(s) or building asset(s) occupying the land. Dwelling Age — the age of a building in years, where older dwellings might be more suitable for redevelopment and very old dwellings might have heritage value and should be retained. Development Efficiency — the ratio of number of dwellings on a lot, to the number of dwellings that could exist if the land was developed to full zoned capacity. Nearby Demolitions — the number of demolitions in the vicinity of a property in recent years, indicating whether an area is already undergoing significant change. Extra Land — the area of undeveloped land on a lot, where significant amounts of land might indicate capacity for additional development.

The final tool is a cost calculator that allows users to evaluate the viability of various development scenarios. It is based on the intersection of various industry standard calculations and property sales data. The image below (Fig. 5) illustrates the costing of a project with six townhouses and twelve walk-up apartments, including the sales prices and volumes in the area of the development for comparison. By comparing the costs of a hypothetical development with local sales prices by dwelling type, users can scale and assess whether it would be financially viable to develop certain types of dwellings in the area. After identifying areas that are potentially ready for redevelopment and dwelling typologies that would be profitable to develop, users can flag properties for redevelopment, delineate a precinct area, and download a zip file

containing lot boundary and building footprint data for subsequent scenario preparation in ESP. 3. The Envision Scenario Planner (ESP) system ESP is a web-based system for precinct design, visualisation and assessment, for which specifications were determined by conducting workshops with stakeholders, industry experts and potential end users in Western Australia and Victoria (Pettit et al., 2014; Trubka et al., 2015). Basic requirements for the system included the positioning and visualisation of three-dimensional models of representative dwelling typologies and an assessment framework and logic for generating feedback on a series of sustainability indicators. The workshops indicated that visualisation should be relatively simple to avoid the public mistakenly believing that detailed designs for a redevelopment site have already been established prior to planning and approval stages, while reporting outputs should include assessments of carbon, water, energy, cost and transport. As the intended end user base for the system consisted of government officers and community members, the tool also had to be reasonably simple to use and not require expert knowledge in the use of GIS systems and the assessment of sustainability performance. Based on the workshop-derived specifications, ESP was developed as a web-based system using a combination of open source and proprietary libraries that features a range of functions and features for a simple and easy manipulation of precinct data. Users can rezone, subdivide and amalgamate land parcels; create new lots; apply and visualise height

Fig. 6. Current development scenario (left) and precinct regeneration scenario (right).

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Fig. 7. Prospective areas of strategic focus for an ‘age in place’ scenario using property-level MCE analysis (MCE-1) in Maroondah (Victoria, Australia).

limits on lots; import and visualise existing building footprints; and populate precincts with building and landscaping objects stored in a typology library by using drag-and-drop or auto-allocate functionalities. Additionally, ESP allows three visualisation modes: 2D footprint, 3D extruded footprint, and 3D mesh. Due to the object-oriented logic of the ESP system, every object that can be inserted in a precinct can either inherit its properties from a particular building class, or have its attributes completely unique. ESP integrates a library of architectural and landscape objects, in which there are three groups of residential typologies available: ‘business-as-usual’ (BAU), ‘Efficient’, and ‘Advanced’ typologies. The integration of a group of BAU typologies in the ESP 3D library aimed to represent the types of housing being currently developed in Australia and New Zealand, in order to establish a benchmark for comparison with innovative housing scenarios. Thus, the models were based on the floor plans found in a federally-funded report on typical housing types in Australian cities (Department of Industry, 2013). The group of BAU typologies includes detached housing, attached housing, and multi-unit dwelling structures such as walk-ups and high-rises. The typologies in the ‘Efficient’ group are the same as those in the BAU group, with the distinction that these typologies present better construction standards. The third group of residential typologies integrates ‘Advanced” architectural design, mostly multi-dwelling buildings that are

characterised by improved construction standards and aim at better community outcomes. Every residential typology (corresponding to a 3D model, building footprint and floor plan) was assessed using Accurate Sustainability (Hearne Software, currently Energy Inspection) for embodied carbon, space heating and cooling thermal energy requirements and internal water demand. For each climate zone, every typology was assessed eight times at 45 degree rotations from 0 to 315 degrees to capture the effects of orientation and ventilation on building thermal performance. This modelling approach makes for highly accurate assessments of scenarios in ESP. These outputs can also be adjusted in ESP, as the system allows users to modify numerous modelling parameters at the object, typology and precinct levels, including the efficiency of various household systems and the presence of various technologies such as solar panels, rainwater capture and greywater recycling systems. Additionally, ESP integrates its own modelling of the embodied carbon, capital and operating costs and water demand of external land; stormwater runoff; transport (vehicle kilometres travelled, greenhouse gases and mode split); and district-scale energy production. Other classifications of precinct typologies, such as commercial, institutional and mixed use buildings; open space; and pathways (i.e. freeways, highways, local roads, footpaths and bicycle paths) were also included in the system.

Fig. 8. Results of the MCE-2 ‘ageing in place’ scenario, overlaid on top of the MCE-1 results (Fig. 7) in Maroondah (Victoria, Australia).

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Fig. 9. Potential redevelopment precincts (displayed in blue) in Maroondah, Victoria, Australia. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 6 illustrates a typical Australian suburban precinct (left) consisting of detached housing regenerated to include a range of housing options with the addition of significant public open space, a local shopping centre, and a new school (right). In both scenarios, the visualisation mode is set to display extruded footprints, and the panel on the right of each image shows part of the residential report, which aggregates the performance assessment of every residential object when all objects are de-selected. Selecting individual objects, or subsets of objects, will update the report accordingly. Scenarios developed in ESP can then be downloaded to a separate augmented reality (AR) application via a public project API as an immersive way of presenting redevelopment options in meetings and community events. The two systems, Envision and ESP, constitute a technological and data-driven approach for identifying the most suitable redevelopment locations, and planning for precinct regeneration. Next steps of the research project will involve the identification and evaluation of statutory and local planning frameworks to enable Greyfield precinct regeneration, as well as testing the tools in community engagement events. Together, the Envision and ESP systems provide an evidence base with visualisations that may enable better communication with communities and stakeholders in the processes of redevelopment, and enable better informed decisions. In the following section, we illustrate how Envision and ESP have been used in two distinct contexts in facilitating scenario modelling for precinct redevelopment. 4. The Envision and ESP workflow This section focuses the demonstration of Envision and ESP workflow in two cases, with distinct redevelopment paradigms. Maroondah City Council (Victoria, Australia) has been an enthusiastic

partner in the development of GtG, and has shown particular interest to implement the proposed software-aided workflow for precinctscale redevelopment focusing on ageing in place. While Christchurch City Council (New Zealand) aims to support new showcases of urban density integrating housing affordability, urban amenities, and quality of open space to attract new families into the city centre and provide confidence to developers in a context of recovery and reconstruction after the 2010 and 2011 earthquakes. The strategic, demographic and sustainability objectives of local governments, combined with conventions of lot-by-lot subdivision, typical pressures of planning for diverse populations and politically sensitive climates, make the job of aligning residential strategies particularly challenging, especially while addressing all stakeholders and stakeholder concerns. It is in this context that ENVISION and ESP were conceptualised to demonstrate the software-aided workflow for residential planning and redevelopment. In general, the workflow includes: • Step 1: Conduct property-level MCE analysis in Envision utilising the MCE-1 tool. This entails selecting decision criteria, applying suitable weightings to each criterion, and then running and displaying the results. Consideration can be given to attributes such as proximity to schools, centres, parks, transit as well as zoning, slope of land, environmental sensitivity, etc. • Step 2: Conduct census zone-level MCE analysis in Envision utilising the MCE-2 tool. This entails selecting decision criteria, applying suitable weightings to each criterion, and then running and displaying the results. Consideration can be given to attributes such as socioeconomic status, income, education, housing types, vehicle ownership, journey to work modes, etc.

Fig. 10. Three potential redevelopment precincts in Maroondah (Victoria, Australia).

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Fig. 11. A typical two-for-one redevelopment scenario exemplifying ‘BAU redevelopment’ in Maroondah (Victoria, Australia). (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.)

• Step 3: Investigate properties with significant redevelopment potential in Envision utilising the Precinct Identification tool. This entails identifying and negotiating property attributes and cut-off values, considering property attributes such as the remaining structural improvement value, structure age, extra land, development efficiency, nearby demolitions, etc. • Step 4: Select a precinct for redevelopment scenario modelling. This entails prioritising a location that scores high in MCE-1 and MCE-2, and contains a significant clustering of properties identified using the Precinct Identification tool. • Step 5: Determine the financial viability of the project in Envision using the Viability tool. This entails choosing a housing typology mix along with dwelling sizes, quantities and qualities of build and then running an analysis. • Step 6: Determine the design goals and aspirations of the redevelopment to guide scenario preparation in ESP. • Step 7: Design and compare performance of scenario options for the identified precinct using ESP. • Step 8: Conduct community engagement sessions for the design, consultation, and selection of a preferred redevelopment scenario.

The subsections that follow apply the proposed workflow to the two distinct cases of Maroondah and Christchurch, utilising Envision and ESP. 4.1. Case I: ‘ageing in place’, Maroondah, Victoria, Australia Maroondah is a municipality 20 km to the east of Melbourne with a population of approximately 100,000 people, covering an area of 6137 ha. The municipality is serviced by a train line and contains two activity centres, Ringwood in the west and a smaller centre in the east, Croydon. The western side of the municipality consists of lots ranging in size between 300 and 700 sqm, many of which are undergoing twofor-one3 or greater subdivision. The east of the municipality and the central ‘ridgeline’ contain properties that are typically larger and tend towards low density. Current planning objectives indicate the necessity of providing housing for an additional 20,000 residents in the next 25 years, while 3 Two-for-one subdivision: the result of a subdivision process, in which an original property is divided into two parcels.

addressing the needs of specific demographics, such as an ageing population, as retirees are projected to comprise 26% of the population by 2040. Municipal-wide issues of concern are the protection of canopy trees, conserving the neighbourhood character of areas, and alleviating the flood risk of low-lying areas. There is also significant debate concerning water sensitive, carbon neutral and pedestrian policies. The first two steps aim at locating areas of strategic redevelopment focus. Considering an “ageing in place” strategy in Maroondah, the first MCE tool (property-level) was set to display areas that have low land slope (to address flood issues and protect the ridgeline) and that are in close proximity to a medical centre (to address an ageing population), local centre (to have shops within walking distance) and train station (to provide high quality transit mobility). The image in Fig. 7 illustrates the outcome of the MCE-1 analysis. The second step focuses on the demographics in the municipality, to identify the presence of the target demographic group in specific areas. In the case of an “ageing in place” scenario, the study aimed to identify areas with significant levels of ageing populations in low socioeconomic areas (considering the cost of land for affordable housing and populations with low financial resources). Fig. 8 presents the results of MCE2 overlaid upon the results of MCE-1. The results show a number of strategically suitable areas for the type of redevelopment in mind when the decision criteria and weightings were selected. This process can be repeated by local planners as a process of revising decision criteria and weightings and identifying other areas of strategic redevelopment focus. The third step in the workflow involves exploring the ‘readiness’ of properties to be redevelopment, and this requires the Precinct Identification tool. The image bellow (Fig. 9) illustrates the outcomes of a precinct identification query, where the following criteria were specified: • RPI value ≥0.8 (i.e. properties have greater than 80% of their value in the land); • Elevation variation ≤2 m; • Distance to medical centre/hospital ≤800 m; • Distance to local shops ≤800 m. When zoomed in and viewed along with the previous outputs, the analysis reveals a number of precinct-scale redevelopment possibilities, as can be seen in Fig. 10. A number of precincts were selected and presented to local planners as a starting point for precinct regeneration. After some debate, the first

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Table 1 Brief summary of ESP reports of the ‘BAU redevelopment’ scenario. Total dwellings No. of residents Urban density (n. dwellings/ha) Footprint area (sqm) GFA (sqm) Storm-water run-off Total plot ratio

82 328 27.8 10,359.9 9032.3

0.31

Total area open spaces (sqm) Dwelling mix by architectural typology Dwelling mix by no. of bedrooms Energy demand — total operating (MJ/year) Average energy demand per household — operating (MJ/year) Total embodied carbon (Kg CO2-e) Total parking spaces

option (Fig. 10, left) was identified as the most appropriate for targeted precinct-scale regeneration and scenario modelling in ESP. ESP allows users to import property data from Envision in Shapefile format, or alternatively users can create their own Shapefile for importing into the system. Users can then subdivide, amalgamate and rezone lots in order to create a structure plan that works holistically as an integrated precinct. This is suitable for accommodating multi-unit typologies that feature in one of the example scenarios. After preparing the site, users can then drag and drop typologies of precinct objects into place. Before modelling an integrated redevelopment precinct, however, it is useful to create a scenario that exemplifies the outcome of a BAU redevelopment approach. The image bellow (Fig. 11) illustrates a typical two-for-one redevelopment scenario of the previously identified precinct for comparison with an integrated precinct redevelopment scenario. Grey extruded footprints on light blue lots identify existing buildings and do not factor in the scenario as they were not flagged as being re-developable. The table below (Table 1) reports some outputs generated by ESP for the ‘BAU redevelopment’ scenario.4 As reported in Table 1, a ‘BAU redevelopment’ scenario would generate 82 dwellings, achieving a plot ratio of 0.31 and accommodating a population of 328 residential units assuming that each dwelling contains one more occupant than there are number of bedrooms. This redevelopment scenario does not provide any public open space or local amenity, nor does it include any sustainable technologies. An alternative scenario aims to illustrate a ‘regenerative redevelopment’ scenario, where lots are amalgamated, allowing a retrofitting of local infrastructure, as depicted in Fig. 12. Due to amalgamation and incorporation of multi-unit typologies, the precinct can allocate land for public space, enhancing walkability and storm-water capture, as well as preserve the existing canopy tree coverage, while increasing housing density and the range of housing options. As presented in the Table 2, it is possible to build 98 dwellings in a ‘regenerative redevelopment’ scenario, with a plot ratio of 0.8 and 382 residents. Despite the similarity with the previous scenario (Table 3) in terms of parking requirements, this scenario integrates approximately 5000 sqm of open public space in the precinct. Despite the estimated higher upfront redevelopment costs in comparison to the ‘BAU scenario’, the ‘regenerative redevelopment’ scenario shows significant improvements on: 1) Higher construction standards featured in the ‘regenerative redevelopment’ allow better environmental performance at the precinct level. Despite an increase of 19.5% of residents, the ‘regenerative redevelopment’ scenario presents lower operating costs (electricity, gas, and water) which support the economic sustainability of the precinct; 2) The environmental performance of the dwellings: The average operating energy demand in the ‘BAU redevelopment’ scenario corresponds to 56,625.6 MJ/year per household; whereas the average operating energy demand in the ‘regenerative redevelopment’ scenario corresponds to 7440.9 MJ/year per household. This represents a significant reduction of the annual energy costs for households, 4 The actual ESP system reports over 300 KPIs. For the purposes of this case study only a small subset of indicators is presented.

0.00 100% single houses 100% dwellings with 3 bedrooms plus 4,643,299.1 56,625.6 1,632,002.5 182

sustaining that the ‘regenerative redevelopment’ scenario supports environmental performance and housing affordability in the long and medium term. 3) The integration of public open space (51 sqm/resident), which is attainable through a more efficient residential plot ratio in the ‘regenerative redevelopment’ scenario, may enhance better community outcomes in promoting recreational activities and chance social encounters between residents. These social outcomes are fundamental for community development, and for the promotion of an ‘ageing in place’ strategy while ensuring the attractiveness of the precinct for a diverse population. The application of GtG workflow, featuring the use of Envision and ESP, enabled the identification of the most appropriate precinct locations for an ‘ageing in place’ redevelopment. The proposed workflow also enabled the estimation of economic viability for two distinct redevelopment scenarios; and the co-design, visualisation, and assessment of the economic and environmental outcomes of redevelopment scenarios. This process provided Maroondah City Council with valuable information for supporting evidence-based decisions for precinct redevelopment. Additionally, the systems' visualisations are relevant for the negotiation processes with developers and engagements with local communities. 4.2. Case II: ‘rebuild smarter’, Christchurch, New Zealand Christchurch is the largest city in the South Island of New Zealand, with approximately 450,000 inhabitants in the greater Christchurch area. In late 2010 and 2011, a sequence of significant earthquakes caused extensive damage to the built, natural, and social environments throughout Canterbury region and the City of Christchurch. The most damaging earthquake, in February 22nd 2011, resulted in 185 deaths and thousands of casualties. The distribution of physical damage was influenced by geomorphological factors, such as soil composition and vulnerability to liquefaction; and aggravated by socio-economic factors (CERA, 2015; Manula-Seadon and McLean, 2015; Dionisio et al., 2015). The housing stock was heavily damaged in the earthquakes (approximately 91% of all Christchurch houses suffered some degrees of damage) and about 22,000 houses will need to be rebuilt (CERA, 2015; Dionisio et al., 2015). Consequently, the housing market has been through unprecedented change with dwelling shortages over the past four years, with (1) approximately 8000 homes being zoned “red” by the Crown due to the uneconomic viability of the land, and another 4200 houses throughout the city considered uninhabitable (CDC, 2014); (2) the increase in population (demanding about 8100 new dwellings in the next 4 years); (3) temporary accommodation for displaced residents during residential repairs and rebuilds, and (4) accommodation of construction workers (MBIE, 2013). In the latest Housing Activity Management Plan (Long Term Plan 2015–2025) (CCC, 2014), the Christchurch City Council established affordability, housing quality, and promotion of community environment, as the main goals of future housing achievements in Christchurch (CDC, 2014). These goals are convergent with the Land Use Recovery Plan (LURP), and it is critical for the City Council to promote the development of demonstrative showcases of new housing typologies to enable higher

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Fig. 12. A ‘regenerative redevelopment’ scenario in Maroondah (Victoria, Australia).

levels of urban density, while promoting improved living standards. Additionally, there is also a nationwide debate on the need for better housing quality and lower energy impacts, in which the central government and the Christchurch City Council argue that Christchurch is positioned with the opportunity to “rebuild smarter”. This case illustrates the application of the workflow proposed by GtG, with the support of Envision and ESP, to identify the most suitable precincts for reconstruction, in a particularly sensitive socio-political climate as part of negotiating the reconstruction process of the city. In this context, Envision and ESP will support local government in driving the processes of communication, consultation, and engagement with stakeholders to develop showcases to enhance developer and investor confidence. And will help to integrate local know-how in co-designed precinct reconstruction, enabling better social outcomes (Hartz-Karp and Newman, 2006, Dionisio et al., 2015). As previously discussed, the first two steps of the workflow focus on the identification of strategic areas for reconstruction. Considering a “rebuild smarter” scenario in Christchurch, MCE-1 (property-level analysis) was set to display areas that are located near bus stops (promoting public transportation, as key factor to enable urban intensification, near supermarkets, main roads, local centres and strategic centres enabling proximity to a wider diversity of urban amenities. All of which can be attractive to a wider range of demographic groups), near medical centres (critical for ageing in place), near primary and secondary schools (critical for young families), and near urban parks (to enhance better living standards in the city). Fig. 13 shows the outcome of the MCE-1 analysis considering the described criteria.

The MCE-2 (census zone analysis) aims to identify areas where specific target groups may be particularly concentrated. Considering the goal “rebuild smarter”, the council aspires to support the reconstruction of residential precincts capable to attract a wide diversity of people, such as students, young families with or without children, and elderly. In addition, it is also critical to include areas where both New Zealand and foreign born citizens mingle, in order to promote cultural and ethnic diversity. The results (Fig. 14) show several areas of the city that meet the selected criteria in both MCE-1 and MCE-2. This process can be replicated by Christchurch's local government for identifying other areas considering other groups of criteria for reconstruction or redevelopment strategies. Next, the third step of the workflow involves the identification of potential land parcels for reconstruction, with the use of the Precinct Identification tool. Despite the focus of this scenario on reconstruction potential, this tool can also be used to identify priority areas for redevelopment. In this case, the parameters considered were: • RPI value ≥0.8 (i.e. properties have 80% of value in their land); • Area ≥ 200 m (to exclude land parcels with dimensions bellow 200 sqm); • Nearby Demolitions ≥5 (over 10 years within 200 m); • Distance to Local Shops ≤1000 m. The results show a number of land parcels that meet the previous parameters (Fig.15), which can support decision-making on the selection of precincts for reconstruction in Christchurch.

Table 2 Brief summary of ESP reports of the ‘regenerative redevelopment’ scenario. Total dwellings No. of residents Urban density (n. dwellings/ha) Footprint area (sqm) GFA (sqm) Storm-water run-off Total plot ratio

98 382 62.3 8434 14,693.6

0.8

Total area open spaces (sqm) Dwelling mix by architectural typology Dwelling mix by no. of bedrooms Energy demand — total operating (MJ/year) Average energy demand per household — operating (MJ/year) Total embodied carbon (Kg CO2-e) Total parking spaces

5000 sqm (approx.) 81.6% attached, 18.4% low rise apartment 89.8% dwellings with 2 bedrooms, 10.2% dwellings with 3 bedrooms plus 3,178,730.9 (729,207.2 in the residential sector) 7440.9 2,935,773.2 (2,677,242.3 in the residential sector) 181

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Table 3 Results of the ESP precinct reports, comparing the two redevelopment scenarios. BAU redevelopment scenario Planning Total GFA (sqm) Total residents Total jobs Total open spaces area (sqm) Total parking spaces Energy demand Total operating (MJ/year) Carbon Total embodied carbon (Kg CO2-e) Total operating carbon (Kg CO2-e/year) Water demand Total potable water (KL/year) Total operating (KL/year) Financial Total property cost (land, landscaping, and construction) (AUD$) Total operating (electricity, gas, and water) cost (AUD$)

9032 328 0 0.00 182

Regenerative redevelopment scenario 14,694 382 34 5000 (approx.) 181

2,818,343

2,333,314

1,632,003 4,643,299

2,935,773 3,178,731

24,375 24,375

9982 17,601

26,032,632

41,170,271

1,602,480

1,286,047

Unlike Maroondah, Christchurch City Council's project stakeholders have not selected the precincts yet, for further scenario co-design and modelling using ESP. However, Envision's tool allowed the identification of a relevant amount of land potential for redevelopment in the north-eastern area of central Christchurch. Additionally, this area of the city (Fig. 16) is critical enhance residential attractiveness in the central city (within the four avenues), as contemplated in the Central City Plan — the Blueprint —, prepared by CERA (CCDU, 2012). After importing the selected precinct into ESP, users can create multiple reconstruction scenarios with different selections of housing typologies after rezoning, subdividing, and amalgamating the imported lots. However, before beginning the exercise of co-design and precinct modelling, it is relevant to determine the outline of each reconstruction scenario to be examined in ESP. In the case of Christchurch, it is crucial to examine the economic and environmental benefits of better construction standards in showcases capable to enhance the confidence of investors and developers. Thus, the “rebuild smarter” case includes two scenarios: the ‘BAU reconstruction’ scenario, and the “innovative reconstruction” scenario. The following image (Fig. 17) corresponds to the ‘BAU reconstruction’ scenario, illustrating the most common redevelopment schema: the subdivision of parcels in two or three Battle-axe allotments,5 and small-scale amalgamation for attached housing, without complete block amalgamation. In contrast, the second scenario (Fig. 18) integrates total land amalgamation of the block into a precinct for the maximisation of the redevelopment potential, promoting higher urban density and greater public open space for better spatial sociability, and walkability. The environmental and economic outcomes of both scenarios can be compared by referring to Tables 4, 5 and 6. As presented in Table 4, a ‘BAU reconstruction’ scenario, would allow the construction of 51 dwellings (single, grouped, and attached houses), accommodating 246 inhabitants in this precinct in Christchurch. As in most BAU redevelopment initiatives, no common open spaces were included in the urban design of the precinct. The promotion of local amenities and community facilities is crucial to guarantee the attractiveness of the city centre to a wider diversity of population groups, such as students, couples, young families, and elderly. The ‘innovative reconstruction’ scenario (Fig. 18, Table 5) increases the number of dwellings to 166, for a total 622 new residents, while 5

Battle-axe allotment constitutes a type of subdivision, in which the access to multiple dwellings is composed by a common driveway, services and landscaping (DTPC Victoria 2011). It resembles the shape of an axe, hence the name (DTPC Victoria 2011).

promoting a new urban vibrancy with local amenities and a diverse range of community facilities, such as a public library, a health centre, a primary school and civic centre. Despite the substantial increase of energy demand and total embodied carbon of the ‘innovative reconstruction scenario’, it is possible to see that such values are significantly lower per inhabitant. In addition, the ‘innovative reconstruction’ scenario integrates an opportunity to reinvigorate the local economy, which together with the promotion of community facilities, is crucial to build social resilience (Magis, 2010; Stevenson et al., 2011; Berkes and Ross, 2012; Collier et al., 2013). Despite higher upfront reconstruction costs, the ‘innovative reconstruction’ scenario is a better option in meeting the strategic goals for “rebuild smarter” in Christchurch (Table 6). It shows to be more efficient in: 1) The environmental performance of the precinct. The maximisation of reconstruction potential from 0.39 plot ratio of the “BAU reconstruction’ to 0.79 plot ratio of the ‘innovative reconstruction’, represents an increase in the number of residents by 152%, while reducing significantly the energy demand per resident. In the ‘BAU reconstruction’ scenario, the average operating energy demand per inhabitant is estimated to be about 10,536 MJ/year, whereas in the ‘innovative reconstruction’ scenario it is estimated to be only 192 MJ/year per inhabitant (considering only the residential operating energy demand of the precinct), representing a significant reduction of energy demand in the residential sector. 2) The environmental performance of the dwellings, due to improved construction standards. The average operating energy demand in the ‘BAU reconstruction scenario’ corresponds to 50,821.2 MJ/year per household, in contrast to an average of 719.8 MJ/year per household in the ‘innovative reconstruction scenario’. This represents a significant reduction of annual energy costs per household, supporting the assumption that the ‘innovative reconstruction’ scenario supports housing affordability. 3) The environmental impact of the residential built asset. The embodied carbon of the residential sector in the ‘BAU reconstruction’ scenario corresponds to 1,449,329 Kg CO2-e, against 147,398 Kg CO2e in the residential sector of the ‘innovative reconstruction’ scenario. 4) The inclusion of open common spaces (12 sqm/resident) and a more efficient plot ratio of urban density in the ‘innovative reconstruction’ scenario correspond to critical features to enhance better community outcomes, promoting chance social encounters between residents and the opportunity for outdoor community activities. The promotion of improved social outcomes in the precinct is quintessential not only to enhance the sense of community, but also to boost the attractiveness and invitingness of the city centre. In terms of community sustainability, the ‘regenerative redevelopment’ scenario in Maroondah and the ‘innovative reconstruction’ scenario in Christchurch promote good levels of urban density, which supports more open space and potentially the development of more urban amenities. Promoting open space for community activities is critical in supporting future amenities and urban sociability, all fundamental to the quality urban life, vibrancy, and safety (Jacobs, 1961; Appleyard and Lintell, 1972; Shaftoe, 2008; Carmona et al., 2010; Gehl, 2011). Moreover, the existence of high quality open space, capable of supporting sociability and conviviality within communities is critical to building community resilience (Wisner et al., 2004; Bosher, 2008; Edgington, 2010). 5. Discussion By proposing a software-aided workflow for housing redevelopment and urban regeneration, the GtG research project aims to enable better informed decision-making in the processes of urban planning. With the support of Envision, it is possible to identify potential and priority

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Fig. 13. Prospective areas of strategic focus for ‘rebuild smarter’ scenario using MCE-1 in Christchurch (New Zealand).

Fig. 14. Results of the MCE-2 ‘rebuild smarter’ scenario, overlaid on top of the MCE-1 results (Fig. 13) in Christchurch (New Zealand).

redevelopment areas, while assessing preliminary feasibility through the estimation of redevelopment costs. Additionally, the usage of ESP allows the design, modelling, and comparison of precinct redevelopment scenarios to achieve better environmental, economic and social outcomes.

In the last two decades, the development and use of similar geospatial software tools increased significantly in urban planning, especially in the context of decision-making, information processes, and community engagement (Sieber, 2000; Kyem, 2000; Sieber, 2003). However, most of these geospatial tools either require a high level of

Fig. 15. Outcome of the Precinct Identification tool in Christchurch (New Zealand).

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Fig. 16. North-eastern area of central Christchurch (New Zealand), showing several land parcels identified in Envision's precinct identification tool.

Fig. 17. ‘BAU reconstruction’ scenario of the Christchurch precinct (New Zealand).

expertise or are inaccessible to a wider range of users, compromising their usefulness and potential impact for urban planning (Dionisio et al., 2015). Conversely, Envision and ESP were developed within the proposed workflow to be applied in the practice of urban planning by non-experts, while allowing the application of the tools in public consultation and community engagement events. Thus, the most significant challenges of developing Envision and ESP were related determining specifications for tools such that they would have immediate use, while developing user friendly interfaces capable of summarising the most relevant information to different groups that local governments will consult throughout the process of precinct redevelopment (i.e. landowners, developers and investors, resident communities, and construction companies). In the case of Maroondah, the proposed workflow enabled the identification of a precinct in an area close to medical services, public transport and on land with low slope. Furthermore, the comparison between

two precinct redevelopment scenarios has addressed a number of local policies, including low carbon, walkable neighbourhood and water sensitive strategies. This example demonstrated that it is possible to simultaneously address the plurality of issues that has risen in this location, while using Envision and ESP in the process of decision-making. On the other hand, the application of the GtG workflow in Christchurch demonstrated the potential of Envision and ESP tools in facilitating the processes of precinct reconstruction, while attaining the need to attract new residents, and illustrating the social and environmental benefits of innovative precinct design with improved construction standards. The application of the GtG workflow with the support of Envision and ESP presents several possibilities for the distinct scopes of users. For local governments and planning agencies, Envision enables the identification of areas potential for urban regeneration, which is particularly critical presently given the trends of urban infill redevelopment in major cities. In addition, Envision enables an accurate assessment of

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Fig. 18. ‘Innovative reconstruction’ scenario of the Christchurch precinct (New Zealand).

Table 4 Brief summary of ESP reports of the ‘BAU reconstruction’ scenario. Total dwellings No. of residents Urban density (n. dwellings/ha)

51 246 18.6

Total area open spaces (sqm) Dwelling mix by architectural typology Dwelling mix by no. of bedrooms

Footprint area (sqm) GFA (sqm) Storm-water run-off

5933.6 10,585

Total plot ratio

0.39

Energy demand — total operating (MJ/year) Average energy demand per household — operating (MJ/year) Total embodied carbon (Kg CO2-e) Total parking spaces

0.00 49% single houses, 51% attached houses 96.1% dwellings with 3 bedrooms plus, 3.9% dwellings with 2 bedrooms 2,591,883.4 50,821.2 1,449,328.5 156

Table 5 Brief summary of ESP reports of the ‘innovative reconstruction’ scenario. Total dwellings No. of residents Urban density (n. dwellings/ha)

166 622 153.4

Total area open spaces (sqm) Dwelling mix by architectural typology Dwelling mix by no. of bedrooms

Footprint area (sqm) GFA (sqm) Storm-water run-off

10,397.8 18,457.2

Total plot ratio

0.79

Energy demand — total operating (MJ/year) Average energy demand per household — operating (MJ/year) Total embodied carbon (Kg CO2-e) Total parking spaces

physical and social vulnerabilities, which is critical in the scope of urban planning. Its functionalities and outcomes are both accurate for the practice of urban planning; and intuitive for stakeholders and communities. Additionally, Envision's viability tool enables the assessment of the economic feasibility of different redevelopment scenarios that can facilitate consultation processes with landowners towards land amalgamation. The identification of the best redevelopment opportunities for a given housing strategy can also be used to support business cases to attract new investment among developers, promoting innovative construction methods. For local communities, residents and local business, Envision can promote better understanding on the potential or prioritisation of redevelopment areas, underpinning cases to local governments or developers to obtain support for their neighbourhood's change, upgrade, or plan. It can also be used by local governments to communicate with local communities, raising the awareness on the specific regeneration needs of neighbourhoods. Within the proposed workflow for precinct redevelopment, ESP complements Envision by supporting the accurate assessment of

7500 (approx.) 100% walk-ups 48.2% dwellings with 1 bedroom, 25.3% dwellings with 2 bedrooms, and 26.5% 2 and 3 bedrooms plus 19,215,948.7 (119,478.7 MJ/year in residential) 719.8 9,774,157 (147,398.4 Kg CO2-e in residential) 463

environmental impacts and economic feasibility of different redevelopment scenarios, at precinct and building scale. Such functionality supports urban planners and decision-makers in the ability of managing a better optimisation of urban design choices, and more informed trade-offs. Additionally, ESP aids the decision-making on infrastructure, amenities, and community facilities that is fundamental for residential planning and for community development. Envision complements ESP to support the development of business showcases to facilitate negotiation processes between local governments and planning agencies, and other redevelopment actors. ESP also plays a fundamental role within the GtG proposed workflow, in demonstrating the benefits of innovative and efficient design methods that are critical to raising awareness and helping to develop better confidence among developers and resident communities. The application of the GtG workflow with Envision and ESP helps to reach a wide spectrum of urban planning practices. However, it is critical to emphasise that the GtG research project aims to support local governments and planning agencies (primary end users), in the

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Table 6 Results of the ESP precinct reports, comparing the two Christchurch reconstruction scenarios. BAU Innovative reconstruction reconstruction scenario scenario Planning Total GFA (sqm) Total residents Total jobs Total open space area (sqm) Total parking spaces Energy demand Energy demand — total operating (MJ/year) Carbon Total embodied carbon (Kg CO2-e) Total operating carbon (Kg CO2-e/year) Water demand Total potable (KL/year) Total operating (KL/year) Financial Total property cost (land, landscaping, and construction) (AUD$) Total operating (electricity, gas, and water) cost (AUD$)

10,585 246 0 0 156

18,457.2 622 681 7500 (approx.) 463

2,591,883.4

19,215,949

1,449,329 1,031,090.1

9,774,157 906,124

17,887 17,887

50,018 50,018

21,624,749

66,710,581

1,699,279

15,016,342

processes of communication, consultation, and engagement in redevelopment and reconstruction, and in particular resident communities, landowners, developers, construction companies, investors and funding agencies (secondary end users). The augmented relevance of deliberative democracy models in urban planning (Hartz-Karp, 2005; Hartz-Karp and Newman, 2006; Glackin, 2013) places the focus of decision-making on the processes of engagement to inform, consult, and empower communities and stakeholders. In this context, the proposed software-aided workflow focuses on the identification, co-design, and assessment of the best redevelopment options (Newton et al., 2012), and so placing local governments and planning agencies in a better informed and conscious position to achieve improved outcomes in community engagement processes. References Appleyard, D., Lintell, M., 1972. The environmental quality of City streets: the residents' viewpoint. J. Am. Inst. Plann. 38 (2), 84–101. AURIN, 2010. Final Project Plan, Australian Urban Research Infrastructure Network. Melbourne, Australia. Berkes, F., Ross, H., 2012. Community resilience: toward an integrated approach. Soc. Nat. Resour. 26 (1), 5–20. Bosher, L., 2008. Introduction: the need for built-in resilience. In: Bosher, L. (Ed.), Hazards and the Built Environment, Attaining Built-in Resilience. Routledge, New York. Bratteteig, T., Wagner, I., 2012. Spaces for participatory creativity. Codesign 8, 105–126. Carmona, M., Heath, T., Oc, T., Toesdell, S., 2010. Public Places — Urban Spaces: the Dimensions of Urban Design. Architectural Press Elsevier, Oxford and Burlington. CCC — Christchurch City Council, 2014. Housing activity management plan, long term plan 2015–2025. Chromosoma. CCDU — Christchurch Central Development Unit, 2012. Christchurch central recovery plan. Chromosoma. CDC — Canterbury Development Corporation, 2014. Infrastructure situation report. Chromosoma. CERA — Canterbury Earthquake Recovery Authority, 2015. http://cera.govt.nz. Collier, M.J., Nedovic-Budic, Z., Aerts, J., Connop, S., Foley, D., Foley, K., Newport, D., McQuaid, S., Slaev, A., Verburg, P., 2013. Transitioning to resilience and sustainability in urban communities. Cities 32, 21–28. Department of Industry, 2013. Representative dwelling models: industry consultation summary paper for survey participants. Industry Do. Australian Government, Canberra. Dionisio, M.R., Kingham, S., Banwell, K., Neville, J., 2015. The potential of geospatial tools for enhancing community engagement in the post-disaster reconstruction of Christchurch, New Zealand. Proceedings of the International Conference on Sustainable Design. Engineering and Construction, Chicago.

Edgington, D.W., 2010. Reconstructing Kobe: the Geography of Crisis and Opportunity. University of British Columbia Press, Canada. Gehl, J., 2011. Life Between Buildings: Using Public Space. Island Press, Washington, Covelo, and London. Glackin, S., 2013. Redeveloping the greyfields with ENVISION: using participatory support systems to reduce urban sprawl in Australia. Eur. J. Geogr. 3, 6–22. Hartz-Karp, J., 2005. A Case Study in Deliberative Democracy: Dialogue With the City. Journal of Public Deliberation. Hartz-Karp, J., Newman, P., 2006. The Participative Route to Sustainability. Community Voice: Creating Sustainable SpacesUniversity of Western Australia Press, Perth, pp. 28–42. Jacobs, J., 1961. The Death and Life of Great American Cities. Random House, New York. Kyem, P.A.K., 2000. Embedding GIS applications into resource management and planning activities of local and indigenous communities: a desirable innovation or a destabilizing enterprise? J. Plan. Educ. Res. 20 (2), 175–186. Magis, K., 2010. Community resilience: an indicator of social sustainability. Soc. Nat. Resour. 23 (5), 401–416. Manula-Seadon, L., McLean, I., 2015. Response and Early Recovery Following 4 September 2010 and 22 February 2011 Canterbury Earthquakes: Societal Resilience and the Role of Governance. International Journal of Disaster Reduction. Ministry of Business, Innovation & Employment, Housing pressures in Christchurch, a summary of the evidence/2013, Wellington, New Zealand. Newton, P., 2010. Beyond greenfields and brownfields: the challenge of regenerating Australia's greyfield suburbs. Built Environ. 36 (1), 81–104. Newton, P., Newman, P., Glackin, S., Trubka, R., 2012. Greening the greyfields: unlocking the redevelopment potential of the middle suburbs in Australian cities. International Journal of Social, Education, Economics and Management Engineering 6 (11), 481–500. Nyerges, T., Jankowski, P., 2010. Regional and Urban GIS: a Decision Support Approach. Guilford Press, New York. Pettit, C., Glackin, S., Trubka, R., Ngo, T., Lade, O., Newton, P., Newman, P., 2014. A rapid prototyping approach for building a 3D volumetric precinct urban planning tool. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2 (2), 47–53. Rega, C., Baldizzone, G., 2015. Public participation in strategic environmental assessment: a practitioners' perspective. Environ. Impact Assess. Rev. 50, 105–115. Sanders, E.B.N., Stappers, P.J., 2014. Probes, toolkits and prototypes: three approaches to making in codesigning. CoDesign 10, 5–14. Shaftoe, H., 2008. Convivial Urban Spaces: Growing the Public Life of Cities. United Kingdom, Demos. Sieber, R.E., 2000. Conforming (to) the opposition: geographic information systems in the conservation movement. Int. J. Geogr. Inf. Syst. 14 (8), 776–793. Sieber, R.E., 2003. Public participation geographic information systems across borders. Can. Geogr. 47 (1), 50–61. Stevenson, J.R., Kachali, H., Whitman, Z., Seville, E., Vargo, J., Wilson, T., 2011. Preliminary Observations of the Impacts of the 22 February Christchurch Earthquake on Organisations and the Economy: a Report from the Field (22 February — 22 March 2011). New Zealand Society for Earthquake Engineering Bulletin. Trubka, R., 2011. Productivity and the Density of Economic Activity: Preliminary Estimates of Agglomeration Benefits in Australian Cities Planning Our Cities. Trubka, R., Glackin, S., Lade, O., Pettit, C., 2015. A web-based 3D visualisation and assessment system for urban precinct scenario modelling. ISPRS Journal of Photogrammetry and Remote Sensing. Wisner, B., Blaikie, P., Cannon, T., Davis, I., 2004. At Risk: Natural Hazards, People's Vulnerability, and Disasters. second ed. Routledge, London.

Stephen Glackin is a post-doctoral fellow researcher in Greening the Greyfields, in Swinburne University of Technology (Melbourne, Australia) since 2011. Stephen's fields of expertise range from sociology to computer science, covering community engagement/development, cultural studies, urban geography and a variety of other sociological areas. He is currently involved in a number of projects that incorporate geography, sociology and software engineering, all of which are related to analysing the functions of cities. He began his career as a software engineer, building computer systems for clients such as the Australian Navy, British Petroleum, and Exxon. His Masters focused subcultures and the spaces where they gather, in particular the ‘house party’. His PhD continued this research, analysing how a variety of subcultural and contemporary youth practices generated and maintained very fluid and dynamic but enduring individualised communities. His current research is mainly geographical, examining ways to reduce urban sprawl through developing software that brings a wide range of urban data together enabling planners and community members to better design their urban precincts. Other research includes examining the geographical distribution of poverty and public transport, the socio-cultural factors influencing the change in dwelling size and style, developing 3D applications for town and community planning, and aiding national data infrastructure networks with the development of their data infrastructures and e-tools.

S. Glackin et al. / Environmental Impact Assessment Review 60 (2016) 1–15 Roman Trubka is a post-doctoral fellow researcher in Greening the Greyfields project since 2011, in Curtin University, Perth, Australia. His background spans the areas of urban, transport and land economics; econometrics and economic modelling; financial modelling; urban planning; GIS and software development; and sustainability. The author enjoys bridging the gaps between different disciplines where innovation can occur. As such he developed significant experience as a conduit between technical and nontechnical disciplines, acting both as a modeller and software programmer and a project manager directing others and reporting to stakeholders. His research aims to cultivate a broad and diverse skill set and matching them with an understanding of a wide variety of urban systems-related specialisations and issues. This is because he strongly believes that cities are complex in nature and when developing tools and strategies to improve them, we must be able to cut across a wide range of specialisations and consider a multitude of factors that interact with each other.

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Maria Rita Dionisio is currently a post-doctoral fellow in Greening the Greyfields research project in the University of Canterbury, Christchurch, New Zealand. Rita graduated in architecture and urban management, in 2006, at the Faculty of Architecture, University of Lisbon, Portugal. Rita received her Master (2010) and Doctoral degree (2013) in the Department of Architecture, Graduate School of Engineering in the University of Tokyo, Japan. Her research focuses urban regeneration, urban Public Spaces and social interaction, and community resilience. Rita's research in Japan focused on different spheres of urban regeneration, such as the importance of Public Spaces to sustain efficient urban disaster prevention system, and the relations between Public Spaces and creative/cultural driven social interactions. Rita participated in several other research projects in Japan, such as “Tokyo Void” and “Strategies for community-based Reconstruction in Shibitachi village after the 2011 Tohoku Earthquake and Tsunami”. She is currently involved in several research projects on community resilience, Public Spaces, and urban regeneration in Christchurch, New Zealand.