Guidance

Land use dialogues

Published 21 December 2022

This content was previously hosted on an external microsite that was live between 21 December 2022 and 8 December 2023.

About

In 2022 and 2023, the Geospatial Commission worked with the Open Innovation Team on the Land Use Dialogues, as part of the National Land Data Programme (NLDP).

The Land Use Dialogues brought together academic and industry experts in NLDP’s regional pilots in Devon, Cambridgeshire, Newcastle and Northern Ireland. The evidence and findings formed the bases for the recommendations in the Finding Common Ground report that concluded NLDP.

The pilots explored how data analysis and modelling could support local decision-making. Academics also provided insights into existing data visualisation tools for decisions on energy security, housing and water security.

Insights from Land Use Dialogues policy theme 1: Energy security

First published 6 March 2023

Recent rises in fuel prices and the cost of living crisis, driven by geopolitical shocks such as the invasion of Ukraine, have highlighted the need for an increase in secure, affordable and sustainable energy production.

The government’s ambitions, set out in the Energy Security Strategy, will help achieve this by reducing our dependence on imported oil and gas and decarbonising our electricity system by 2035. This will require an increase in domestic energy production, which will place additional demands on land.

In collaboration with Defra and Department for Energy Security and Net Zero (DESNZ), we’ve been exploring how geospatial data and modelling tools could help support decisions on where to locate energy infrastructure and how best to balance the land required for energy security with other important land uses. 

We began with a roundtable attended by senior civil servants from Defra, BEIS, and Department for Levelling Up, Housing and Communities (DLUHC), and followed this with an online interactive workshop attended by academic experts, civil servants, and experts from public bodies.

Strength in a diverse set of approaches?

In November 2022, we brought together senior civil servants to discuss priority areas for UK energy security, land use implications of different energy scenarios, and how spatial data might support better integrated land-use decisions in relation to energy infrastructure. 

Attendees agreed that a diverse range of models, which can be tested against each other and where assumptions and parameters are clearly defined, would be more useful than a ‘master model’. It was felt that a single overarching model would be inflexible, difficult to implement, and limit the evaluation of different assumptions on policy implications. 

Further, it was agreed a model that tackles priorities in a cross-departmental way would be beneficial to ensure a good understanding of potential synergies and trade-offs. The attendees highlighted some unknowns and limitations of modelling, such as the impact of innovation on land requirements for energy infrastructure and social perceptions of energy infrastructures.

Building on existing models

During the first half of the workshop in January 2023 we considered the strengths, limitations, and compatibility of existing spatial data tools in supporting energy infrastructure decision-making. Several existing models were discussed, such as highRes and ADVENT.  To ensure the models are effective for energy infrastructure policy, academics agreed that decision-makers need to be clear about what policy question they want the model to address. This includes consideration of the order of priorities, as well as spatial scale requirements, and socio-economic and environmental factors.  

The second half of the workshop focused on how we could better use spatial data and modelling tools to support future government decision-making on energy security. It was agreed that to improve the accuracy of model outputs, soft links between models could be made to enable fast and flexible testing of different policy options. Suggestions for improving model accuracy included the use of ensemble models (combining predictions from several models) and pyramid structures of models (scenario evaluation with an optimisation level). Further, new models may only be needed to fill existing knowledge gaps, for example agricultural land quality, land ownership, and social and human factors

Using spatial data science to deliver more from the same land

First published 13 March 2023

The Geospatial Commission’s National Land Data Programme (NLDP) is partnering with the Alan Turing Institute on a pilot with Newcastle City Council to explore how complex local land use decision making can be supported by scenario modelling using data science and AI techniques.

Emma Warneford, Senior Specialist in Planning at Newcastle City Council, and Prof. Dani Arribas-Bel, Deputy Programme Director in Urban Analytics at the Alan Turing Institute, tell us more about the progress of the pilot to date.

Delivering for a growing city

Newcastle City Council (NCC) are looking to build their evidence base to optimise the use of land in the city to ensure that it meets the needs and aspirations of current and future generations. NCC are undertaking strategic spatial planning analysis to balance the delivery of various policy priorities. These include supporting inclusive economic prosperity, moving towards net zero emissions, improving environmental outcomes, and delivering accessible housing to sustainably meet the needs of local communities and a growing population.

NCC faces challenges in identifying sites for future housing development in order to meet housing supply targets, due to the land use constraints they face. Development options are limited by the river Tyne running through the city, and the tightly drawn surrounding Green Belt area.

Identifying sites for housing development therefore requires the consideration of different approaches and options including brownfield redevelopment and urban densification. Understanding where these options are viable can be challenging and considerations need to be taken into account about how these different options impact on NCC’s wider policy priorities.

To support NCC in the identification of sustainable development sites, we are developing a modelling system that leverages data science and AI to cut through inherent complications in land use planning. This will support the planning of strategic interventions by:

• Evaluating the impact of high level development options against policy priority indicators
• Using machine learning and AI to suggest interventions to achieve policy outcomes

Leveraging data science and AI

The first stage of this pilot was to gain an understanding of the priority competing aspects of land use in Newcastle that could be used as indicators in the modelling of scenarios and establish a baseline. These would help NCC assess the impacts of different options for housing developments.

Through a number of collaborative workshops, the following indicators were determined:

• Environment: Air quality
• Economy: House prices & job accessibility
• Society & Health: Accessibility to green space

Publicly accessible datasets have been identified to quantify these indicators, alongside the Urban Grammar and Synthetic Population Catalyst land use data products previously developed by the Alan Turing Institute.

The existing baseline will be modified through planning scenarios which are currently being co-produced with NCC, such as:

• Consideration of low-density or mid-density residential development
• Densification of inner city areas
• Redeveloping brownfields into dense neighbourhoods
• Combinations of the above

The modelling system will then be able to illustrate the trade-offs between competing objectives through an evaluation of the key indicators.

An Ensemble Engine will also be developed which can suggest scenarios that can lead to desired outcomes. This will allow planners to input target growth goals, such as additional housing, and a number of interventions would be suggested, using machine learning and artificial intelligence, that are capable of delivering this goal.

Insights from the Land Use Dialogues policy theme 2: Housing

First published 5 April 2023

As the population continues to rise and lifestyle choices lead to more people living alone for longer, the UK needs to increase its housing supply. The government remains committed to delivering 300,000 homes a year by the mid-2020s and many of the immediate changes focus on how we plan to deliver the homes our communities need. However, by building more homes additional pressure will be placed on land.  Balancing the UK’s housing policy agenda with other potential uses of land requires an awareness of socio-economic factors, the form and features of land itself , and readiness of land for construction.

We have been working with the Department for Levelling Up, Housing and Communities (DLUHC) to explore how geospatial data and modelling tools can support better decision making on land for housing. We started with a roundtable with senior officials from across the government. This was followed by a workshop that brought together academic experts, civil servants, and public body representatives.

Identifying viable land through geospatial modelling

In February 2023, we brought together senior decision makers to understand the policy priorities related to land for housing developments and how land use tools may better support integrated land-use decisions. 

Attendees agreed that the evidence on viable land is held mainly by Local Authorities. The National Planning Policy Framework sets out the principles to guide local authorities, but it does not specify where housing developments should be taking place. They also felt that regular and consistent updating of brownfield site data (through the Brownfield Land Registers) could further assist local authorities in identifying suitable sites for redevelopment. 

The civil servants agreed integrated modelling tools could be useful to support dialogues between local authorities, developers, and the public to allocate land for housing, while considering other socio-economic factors. For example, the attendees emphasised the local level constraints that needed to be considered, such as local housing needs, affordability, and geographies of work. To further support effective decision-making they also agreed on the need for better sharing of information, clarity on assumptions, and more frequent reporting of data.

Sites identification needs well-defined criteria for land for housing

Our subsequent workshop in March 2023 aimed to explore ways in which existing academic work and models could help DLUHC achieve its aims. Attendees agreed that existing models and maps, such as ITRC Urban Development Model and the OS MasterMap could help guide decision making on land for housing. During the first half of the workshop attendees also identified datasets and characteristics that would need to be considered in land use modelling and mapping to make informed decisions. This included factors that may impact the suitability of land for housing developments, such as:

• Economic datasets including land costs and housing affordability
• Environmental concerns such as nutrient neutrality, flooding, and land contamination
• Information on the distance from site to transport hubs, centres of employment, and amenities.

To ensure the models effectively support decision making, it was stated that regular and consistent updating of databases such as the Brownfield Registers and standardisation of definitions and model parameters (i.e. land cover type colour) are needed. Several data gaps were also mentioned, including spatiotemporal dynamics of land use change, biodiversity impacts, and aspects such as housing delivery timescales.

Insights from the Land Use Dialogues policy theme 3: Water security

First published 4 May 2023

With a growing population and the impacts of climate change, demands on our water supply are growing. Locating sites for new water infrastructure, while tackling water pollution is vital to ensuring we have enough water for a range of national priorities, ranging from new housing developments to securing domestic food supplies. The Government’s commitments in these areas are outlined in the Plan for Water (2023) and the Environmental Act (2021). 

To help balance these competing demands, we need to understand many aspects of water supply and demand spatially. To help map out these issues, and understand how the latest spatial modelling techniques could help, we held a series of discussions with officials from Department for Levelling Up, Housing and Communities (DLUHC) and the Department for Environment, Food, and Rural Affairs (DEFRA), alongside Ofwat, the Environmental Agency, and academics who are working on modelling tools to better assist local and national policy decisions.

Data sharing and collaborative water planning

During wide ranging conversations, we covered a diverse set of issues, including flooding, stormwater and sewage discharge, and water security. Officials generally agreed that multifunctional water management tools, that could help develop a shared picture of our water system across the various public agencies and companies which manage our water system, could help understand interdependencies and reduce the risks of unintended consequences emerging down the line. 

Some examples of integrated land use modelling tools already being used or developed by public bodies were also highlighted, such as the Land Use Choice Tool (LUTC) prototype and the National Simulating Systems Model (NSSM).

Integrated models and virtual environments for support decision making

Subsequent conversations with academic experts revealed even more sophisticated integrated modelling projects outside government, such as the OpenCLIM framework, the VENTURA project and CAFlood system. These could be used to further augment government work, and help coordinate water planning and environmental decisions in the context of socio-economic and climate changes. 

Academic work has also highlighted the importance of model flexibility and scenario testing to ensure that models can be tailored to policy requirements, while also needing to be computationally efficient. Experts we spoke to  emphasised the importance of good meta-data, the reporting of assumptions, and spatiotemporal scale alignment between models to ensure reliable outputs. 

Finally, we talked about where the current generation of models could be further improved. Areas highlighted included:

• The integration of catchment information to provide an assessment of the impacts of each catchment water resources, pollution, and management on one another.
• The inclusion of more sectors and parameters to provide a more holistic analysis for policy makers, for example health, transport and infrastructure. 
• Consideration of more socio-economic and climate change scenarios and hazards.
• Sharing of data between the water companies, public bodies and academics to further improve local and national scale modelling.

How tools can help with Land Use Decision Making

How GIS and land use modelling can help improve local authority decision-making

First published Feb 13, 2023 

Local authorities are tasked with local land-use planning and planning application decisions. In this interview, Richard Kay, Manager of Planning Policy and Environment Lead, East Cambridgeshire District Council, reflects on some of the challenges involved and how data and software might be used to support decision-making.  

How well do stakeholders work together to make decisions around land use? 

For a long time, there was a lot of siloed working. Everyone tried to do their best for their area of responsibility, whether that was town planning, highways planning, farming subsidies and so on. But no-one really thought about what was best for the collective. Recently, I’ve seen a big change. It’s early days, but people from different disciplines have realised they need to properly talk to each other and work together, often motivated by climate and nature recovery objectives. The Environment Act has also helped bring about conversations with developers because of the requirement for developments to provide at least a 10% biodiversity net gain. 

What challenges do local authorities face when making planning and land use decisions?

Local authorities often have to make decisions around how to best deliver national government policy, such as where to locate new housing or infrastructure requirements. Sometimes it can be hard to reconcile national government policies around house building and environmental goals and understand what the priority is at the local level. 

It can also be challenging to collect together all the relevant information to make the most informed decisions, especially at the site specific level. Critical constraints, like avoiding building on a floodplain, are factored in. But it can often be hard to know where exactly the best site is to achieve an environmental goal, like creating a wildflower meadow. I tend to rely on local knowledge, conversations and connections to gather certain information, but this isn’t always comprehensive. 

How much do you use tools, like Geospatial Information Systems (GIS), to help inform local land use decisions? 

Most councils use a basic, free version of GIS, to help with decisions around where new housing should be located, for example. The problem is that different councils use different GIS systems and databases which makes it hard to ‘talk’ to each other and share data. Some councils don’t have the expertise and resources available to use GIS in the most effective way. Having a designated GIS officer is a good start. 

What do you think could help support better local decision-making? 

I think it would be really helpful to have a centralised place for data and information, at least at the county level. This would include up to date, free to access, high quality data, covering things like key nature sites, flood risk, water quality and information about agricultural land. If these and other important considerations were mapped out, it would help local authorities and other stakeholders make quicker and better informed decisions about land use. It would help us shift from asking ‘which location will cause the least harm?’ to ‘which location has the most potential for making the greatest contribution to a particular policy objective?’, whether that’s tree planting, biodiversity, or new housing.  

Land use decision making tools in the Welsh Government

by James Skates, Welsh Government. First published Feb 6, 2023 

15 minutes with James Skates, Head of Modelling, Monitoring and Geospatial activities in the Welsh Government discussing what an effective land use decision-making tool looks like. 

I lead work on an integrated modelling platform that supports decision-making by policy and operational teams across the Welsh Government. The platform brings together a series of models that enable us to look at the drivers and potential solutions in the area of land use and agriculture. It represents a significant change in how we develop policy as we can evaluate the likely impacts of a policy before it’s operationalised. For example, the platform has been used to explore how potential trade deals will impact the agricultural sector through farmers’ choices about how they use their land, and the knock on effects on things like employment, soil quality and water quality. The underlying aim is always to get the best value for money from public finances. 

Good quality data is essential. We collect rich environmental data so that we can develop complex and detailed spatial models that can be applied to big questions and challenges. The ability to model at the highest resolution (e.g. 0.25 hectare sq) is very important for policymakers, in order to help them understand how land use will change as a consequence of different drivers at a very granular level. From there, you can aggregate upwards to the county or national level as required. However, sometimes the land cover map data we rely on isn’t as spatially detailed as the modelling we’re capable of. In the future, it will be a great step forward if we’re able to utilise high-cadence earth observation data in the model, which would be at a far higher resolution and produce insights in near real time. 

It’s important to allow enough time both to develop your models and then work with policy makers iteratively to use them effectively. The integrated modelling platform we’ve developed is the result of significant investment over a number of years, motivated at least in part by legislation that requires all Welsh Government decisions to take into account long term and environmental impacts, and trade offs with other policy priorities. We work closely with the consortium that delivers the models, led by Paula Harrison at the UK Centre for Ecology and Hydrology, and follow Aqua Book guidance to try to maximise the quality of our analysis for government. 

The work we do with policy teams is very iterative. We need to fully understand the problem they’re dealing with, including any regulatory frameworks, and then we try to quantify the issue, whether that’s a trade deal or net zero. We work together to explore opportunity spaces in policy and go through several phases where we gradually populate the model. As the policy thinking becomes more informed, so does the model. It’s also very important that the model is transparent and that you have time to ensure that policy colleagues understand its limitations. 

An effective land use decision-making tool has to hit the sweet spot between being useful and overly complex. You have to avoid the temptation to continually make the model more complex as this reduces transparency, increases uncertainties and leads to less confidence in the model’s outputs. 

And finally, don’t always assume that maps are the best outputs. We tailor our outputs for the policy teams we work with, but maps can sometimes be misleading and hard to interpret – they can imply a higher level of certainty than we can really get to with modelling. Sometimes a simple bar chart is a better way of conveying expected changes, whether in farm business income or water quality. 

Insights on creating effective land use decision making tools from the UK Centre for Ecology and Hydrology 

by  Paula Harrison, UK Centre for Ecology and Hydrology, First published Feb 3, 2023  

15 minutes with Professor Paula Harrison, Principal Natural Capital Scientist at the UK Centre for Ecology and Hydrology. In the second of our three guest blogs on the same theme, Paula shares her insights on creating effective land use decision making tools. 

I work with government and the academic community on a range of land use modelling projects. For instance the ERAMMP Integrated Modelling Platform brings together a range of models and helps the Welsh Government to test the likely impacts of policies on agriculture, land use and the natural environment. My academic work includes being part of the Food, Agriculture, Biodiversity, Land-Use, and Energy (FABLE)global consortium, which shares learning on the development of tools for exploring global and national pathways to sustainable land-use and food systems. 

Working with government and academics is quite different. Although both involve collaboration, the co-design process is more intensive and iterative when working with government, and models are usually designed with specific policy goals in mind. My academic work has a broader purpose and is designed to be generally applicable for a wide range of stakeholders. Long-term funding is essential for co-production of effective tools for decision making as it provides more opportunities for iterative and longer-term collaborative work. 

Effective land use decision making tools need to incorporate multiple models within flexible frameworks. Models try to represent a complex real-world situation. Although single sector models are useful (e.g. agricultural models, energy models), running them separately to inform land use decisions can lead to outputs that indicate very different magnitudes of change and even completely different directions of change, compared with running them together in an integrated system. If you want to avoid unintended consequences from decisions and maximise opportunities, you need to understand how different land uses compete and interact with each other.

So, it’s important to link models together and this can be done in different ways. Integrated modelling platforms that are ‘hardwired’ with coded links are relatively easy to run once set-up but can be difficult to adapt. Alternatively, ‘soft coupling’ of models, where inputs and outputs are manually transferred between models, can be more time-consuming to run but are much more flexible and can be rapidly adapted to changing policy and decision-maker needs.   

Automated coupling frameworks could really accelerate progress in land use modelling. Every project you work on has a different question or purpose that requires you to connect different models and there’s currently no easy, automated way of doing this. So you often have to start from scratch, with individual modellers working to match up their measurement units and temporal and spatial scales so that the models can communicate with each other.

It would be a big step forwards to have a collaborative, cloud-based platform that provided a configurable, integrated model coupling framework. This would enable you to build bespoke integrated models for different purposes more easily, flexibly and robustly by coupling different individual models or ‘building blocks’ using automated linkages. 

There’s no such thing as a perfect model, but they need to be fit for purpose. It’s important to use models in an exploratory ‘what if’ way, rather than seeking definitive answers, and there will always be a lot of uncertainty that you need to make decision-makers aware of. This is especially the case when you move beyond modelling biophysical processes to include social and behavioural factors in a model. Modelling tools should ideally be intuitive, accessible and adaptable, which is best achieved through co-designing and co-producing with the end user.