Accelerating grey belt housing development with GIS - Featured in Inside Housing

As land is released under the revised National Planning Policy Framework (NPPF),?Alex Zirpolo, principal GIS consultant at Lanpro, says geographic information systems (GIS) offer developers a powerful, data-driven tool to swiftly identify grey belt land for housing development.

The revised NPPF, published by the government in December, offered a long-awaited definition of the grey belt. Importantly, in relation to social and affordable housing, the NPPF clarified that green belt land that meets the criteria of grey belt may be released for housing and that a high proportion of that should be affordable.

This definition enables us to better identify which sites may be classified as grey belt. They must not “strongly contribute to any purposes” of the green belt; must have been previously developed for other uses; and all land protected on an environmental, social or historic basis (such as habitat sites, Sites of Special Scientific Interest, Local Green Space, national parks or heritage assets) is excluded.

However, an important aspect of the definition is that there is no belt of grey land surrounding towns and cities, to the extent that the green belt is belt-like in its distribution. On the contrary, sites that will be identified as grey belt will be distributed randomly throughout the green belt. They may connect to transport corridors to a greater extent than other sites within the green belt, but there is no formal structure governing their distribution.

The issue, then, is how such sites can be identified easily, for example by a developer searching for suitable sites nationwide.

GIS will play a pivotal role. GIS enables developers and planning consultants to identify such sites easily and efficiently. This involves evaluating the most suitable locations using multi-criteria evaluation, a decision-making tool that combines multiple criteria into a single map to solve complex problems.?

“In the case of identifying grey belt sites, the ability of GIS to immediately access land-use zoning, environmental quality and flooding data will provide the necessary information to begin the process of site selection”

It is commonly used in environmental management, disaster risk assessment and site-finding. It draws on a combination of data sources, including land-use zoning, environmental quality, transport accessibility, demographics, customer density, distance from competitors, current land use and flood risk.

In the case of identifying grey belt sites, the ability of GIS to immediately access land-use zoning, environmental quality and flooding data will provide the necessary information to begin the process of site selection. Weighting, scoring and ranking criteria, and analysing data layers are then used to create suitable maps and modelling.

Why is this tool particularly relevant in identifying grey belt sites? In some cases, grey belt sites will be difficult to identify and analyse in terms of development potential. GIS ensures that diverse datasets such as satellite imagery, elevation, land use, environmental/planning constraints and key topographical features are integrated and that the data is stored, weighted and managed effectively.

GIS also enables sophisticated spatial analysis, such as buffer analysis and identifying areas within a certain distance of key features such as roads or water bodies. Proximity analysis allows developers and planning consultants to determine the distance from essential facilities such as schools, hospitals and GP surgeries. Furthermore, physical modelling factors in topography and land-use type.

“With GIS, measurements can be standardised for ease of comparison, producing a single map that highlights areas of high, moderate and low suitability”

One of the complexities of using multiple data sets is a lack of consistency. However, with GIS, measurements can be standardised for ease of comparison. Weighting is allocated to reflect the relative importance of data layers, with the resulting algorithm multiplying these scores and weights to produce a single suitability map. This map can then be turned into easy-to-understand maps, highlighting areas of high, moderate and low suitability.

The result, which can be achieved within hours as opposed to weeks or even months when compared with more traditional methods, is a data-driven visual tool that depicts the most suitable sites for development.?

With the grey belt now part of policy and the government indicating a positive reception for development applications – whether through the (soon to be reformed) local authority decision-making process, appeal or intervention by the secretary of state – there will be an inevitable rush to identify and acquire suitable grey belt sites up and down the UK to enable housing delivery in this parliamentary term. Tools that enable the swift selection of such sites will provide a significant advantage in the race against time.

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