A rapid analytics tool to map the effect of rezoning on property values
Introduction
Growing global populations, particularly in urban areas, are creating demand for additional, and more advanced, public infrastructure. Such infrastructure is essential for realisation of the implicit goals of global urbanisation: liveability, sustainability, resilience, and economic opportunity in a competitive global context. Importantly, in many jurisdictions this growth in demand for infrastructure is outpacing any growth in government budgets. As such, infrastructure funding and financing is an inherently contentious topic.
The provision of urban infrastructure is typically, and closely, associated with intensification of surrounding land, accommodated by permissive zonings or land-use regulations. Such zoning or regulatory changes generate a windfall for private landowners whose land values increase according to their development potential. Recognising the nexus between infrastructure and carrying capacity of urban land, and seeking to defray the flow of ‘unearned’ increments to local landowners, governments have commonly adopted land-use regulations and development fees. By capturing the uplift in private land value through fees (called ‘value capture mechanisms’), governments can, at least partially, fund the public infrastructure that causes that uplift.
However, robust methodologies to estimate the uplift of land and property values stemming from infrastructure development and zoning decisions are often lacking. This is, in part, because land values are not the primary driver of such zoning decisions, while those making zoning decisions are seldom experts in land valuation. Instead planning controls on density, building form and land use are driven by notions of environmental ‘carrying capacity’ and by local character objectives. To be useful in the zoning process, land values under different zoning scenarios need to be available rapidly and for whole regions. Ideally they should be in a format, and delivered through a platform, that makes them easy to incorporate into zoning decision-making. The absence of such tools means that the nexus between zoning decisions and value uplift is not exploited efficiently.
In contemporary urban data analytics, there is an opportunity to improve this dimension of zoning decisions, and even improve planners' understanding of land values, through a new generation of planning support systems that connect planning controls and land valuations. More and better information, innovative analytical methodologies, and robust and fast cloud computing can produce land valuation estimates more rapidly, more accurately and with greater contextual specificity. This will allow uplift to be better incorporated into existing planning processes that create, compare and assess zoning scenarios. This, in turn, allows for more informed decision-making and fairer application of value capture mechanisms.
The study presented here is part of an effort to address the existing gap. A residual land valuation (RLV) model to estimate value uplift from rezoning is embedded into a planning support system called RAISE – Rapid Analytics Integrated Scenario Explorer (Pettit et al., 2020). Section 2 backgrounds this research, discussing how cities progressively grow through rezoning and densification, and the effect of such rezoning on land values. Section 2 also outlines RLV methods, and how they can inform rezoning practices if estimated in a timely and interactive manner. Section 3 presents the development of the RLV tool, describing the assumptions, data inputs, calculations and outputs connecting zonings with RLV. Section 4 describes the testing component of the empirical research, illustrated through estimation of value uplift around proposed metro (train) stations and their associated rezoning precincts in Sydney, Australia. Section 5 evaluates the proposed RLV tool, with focus on its usability by actual end-users, its computational performance, the validity of the RLV estimates, and the generalisability of the tool to different geographical contexts. The final section summarises the achievements of this study and discusses its limitations and future work.
Section snippets
Urban growth through rezoning
Australian cities, like many that grew significantly over the second half of the Twentieth Century, did so by regularly expanding their urban fringe (James et al., 2017). More recent policy has, however, turned towards ‘compact city’ form as a better means of accommodating greater residential and commercial activity. Compact city growth is based on redevelopment of existing urban areas at higher densities and with mixed uses. Initially such growth was accommodated through ‘brownfield’
Overall tool design
This study adopted a RLV method based on broad dwelling categories (apartments, semi-detached/terrace dwellings, and houses) which are appropriate for this scale of the analysis (parcel unit based at metropolitan to national level). The RLV model joined a suite of valuation models (e.g. hedonic price) already existing in the RAISE toolkit. The RLV model makes use of RAISE's existing database, data management system, computing architecture, and platform interface. However, the RLV module is
The new Sydney metro north west renewal corridor
The North West Rail Link (NWRL), in suburban Sydney, Australia, is a priority railway transport infrastructure project for the state of New South Wales (NSW). The 23 km line integrates the northwest region of Sydney with the existing CityRail network, and includes eight new stations. According to the NSW Government plan, this $8.3 billion infrastructure investment also provides the opportunity to plan for and build liveable centres around each of the proposed new stations, through the creation
Results and discussion
This section reports on the use and testing of the RAISE-RLV tool and discusses its future applicability to urban management and planning. The focus is not on the results of the use cases specifically, as these were hypothetical, but rather on five key characteristics of the online tool: its usability; its computational performance; the sensitivity of the model equation; a validation strategy for the results; and its generalisability to other geographical contexts.
Conclusions
The need to better understand the impact of rezoning on land value is greater than ever. Value uplift is a potentially vital funding source for new infrastructure that supports urban growth and the broad goals that growth supports – from economic prosperity to cultural diversity. However, barriers to the incorporation of land value uplift in rezoning processes persist. This study has demonstrated the potential of a targeted PSS to overcome those barriers. The main contributions of the proposed
Author statement
Simone Z Leao: Conceptualization, Methodology, Formal analysis, writing original and revised draft; Ryan van den Nouwelant: Conceptualization, Methodology, Formal analysis, writing original and revised draft; Vivien Shy: Data curation, Methodology (data modelling), Validation, Visualisation, writing original draft; Hoon Han: Conceptualization, Formal analysis, writing original and revised draft; Sarbeswar Praharaj: Methodology (co-design workshops), writing original draft; Christopher J Pettit:
Acknowledgements
This work has been supported by FrontierSI, a not-for-profit company that exists to deliver major benefits to governments, industry and the community in Australia and New Zealand through the application of spatial information, and Landcom, the NSW Government's land and property development organisation. The authors are grateful to the land valuers and urban planners who participated in the co-design workshops in developing the RLV tool for RAISE.
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