Tranquillity and Place

The nationally consistent terrestrial Tranquillity & Place resource identifies the strategic and local resource in remote, rural, peri-urban and urban areas for use as an evidence base to inform policy intent, practice and provision for well-being benefits.

The full Tranquillity & Place Resource has been completed over five years as follows:

All datasets can be downloaded from DataMapWales  https://datamap.gov.wales/ 

The full reports for these can be downloaded as follows:

Theme 3 -  Relative dark skies .

Themes 1, 2 and 5 -  Visually tranquil places .

Theme 4 Part 1 -  Sounds other than road and railway noise .

Theme 4 Part 2 -  Sound environments where natural sounds are more prominent than noise and are appropriate to context .

Theme 6 -  full resource - connecting sound and visually tranquil places .

Tranquillity is associated with the degree to which places and ecosystems deliver a state of quiet, calm, peace and well-being. This can be described as a relative abundance, perception or experience of nature, natural landscapes and features (e.g. birdsong, natural sounds, moving water, stars and perceived wildness) and/or a relative freedom from unwanted visual disturbance, signs of human influence and artificial noise (e.g. from people, transport, development, light pollution, power lines).

Tranquillity, as a landscape asset and important cultural service, is highly valued and contributes to landscape value and identity. Tranquillity also contributes to health, well-being, spiritual benefit and quality of life. This in turn can bring economic benefits from tourists and visitors to tranquil areas. Tranquillity has limited resilience in that subtle changes in noise, visual intrusion and light pollution may have marked effects on natural settings and tranquillity.

As this study examines relative tranquillity, there is a need to recognise that pockets of tranquillity within urban areas are important, even if they are not truly tranquil by rural standards. In order to do this, whilst maintaining consistency between the urban and rural areas, a two level approach was taken for the analysis. Both levels of analysis draw on the same aspects of tranqullity (for example, visibility of major roads), but the data used to represent/model the indicator and the spatial resolution of the data differs between them.

Stakeholder workshops supported this study, providing key stakeholders the opportunity to comment on and shape the proposed methodology; including the data to be used.

The new Tranquillity & Place resource has been developed using mapped ‘themes’ that merge to produce an overall relative Tranquillity & Place map. This section explains the different themes and how they come together.

Indicators were identified for theme 1, the relative abundance, perception or experience of nature, natural landscapes and greenspaces and theme 2, the relative freedom from intrusive visual disturbance and human influence. Each indicator looked at a specific component of tranquillity. These indicators formed the building blocks of the themes, but are not designed to be viewed in isolation as a measure of tranquillity.

A key requirement for this study was to design it to be repeatable. As such, all datasets used needed to be easily accessible and wherever possible freely available. The data also needed to cover the whole of Wales, so as to give a fair measurement across the whole country.

As this study is assessing visibility, the analysis requires a Digital Elevation Model (DEM) to simulate the topology of the Earth. Ordnance Survey (OS) Terrain 50 and Terrain 5 were used to develop this surface. OS Terrain 50 and Terrain 5 datasets are both Digital Terrain Models (DTMs), which take into account only the bare surface of the Earth, and do not include features such as trees and buildings that rise above the ground.

Given the importance of buildings and trees in constraining visibility, these DTMs were converted into Digital Surface Models (DSMs) by modelling in the trees and buildings using data from OS Open Map Local, OS Mastermap, and the National Forest Inventory data from NRW (for Wales) and the Forestry Commision (for England).

Visibility analysis is calculated from specific locations, to all pixels within the surface dataset. These specific locations are represented in GIS as ‘points’. Being very computationally intensive, it can take several days to run some of the visibility processes. Striking a balance between accuracy and practicality was considered as part of this methodology development

Once all the visibility analysis was complete, buffers were generated around the source datasets representing the features from which the visibility was being calculated. These were at the following distances: • 500 metres • 1 kilometre • 2 kilometres • 5 - 6 kilometres In order to represent features that are closer having more visual impact than features that are further away, these buffers were then combined with the results of the visibility analysis to work out if a pixel is both within a certain distance, and visible. The pixels were then scored based on these factors. The scoring varies for each indicator, but has a maximum value of 10 and a minimum of 0 (for no visibility).

This section provides an overview of the indicators used to build up theme 1. For each indicator, stakeholders helped to identify the most appropriate data to use in the GIS modelling in the rural and urban contexts.

For all of the maps, the input data is shown in the left panel with the results shown on the right. For all of the results maps, the darker the blue, the higher the score.

This section provides an overview of the indicators used to build up theme 2. For each indicator, stakeholders helped to identify the most appropriate data to use in the GIS modelling in the rural and urban contexts. Input data is shown in the left hand panel and the results maps in the right hand panel. For each of the results maps, darker reds show less tranquil areas.

The data for this theme was created in 2021 as part of a previous phase of this study  Tranquillity and Place – Dark Skies . As part of the 2021 study, the dataset was categorised into 8 bands with the higher scores relating to greater light pollution.

From a tranquillity perspective, a value of 0 would be no light emission at all (and so highly tranquil), and higher values would be less tranquil. To enable this data to be combined with themes 1 and 2, values were inverted and normalised to a scale of 0 to 1.

This section provides an overview of the indicators developed to contribute to theme 4 the sound environment part 1.

The full method behind the creation of these maps is  available to view in the accompanying report . Scores were applied using a scale of 0 – 10, with sounds that contribute to tranquillity getting a higher score, decreasing with distance from the source. Sounds that detract from tranquillity were given a lower score, increasing with distance from the source. 

For sounds that contribute to tranquillity, the higher the decibels the higher the score. For detracting factors to tranquillity, it is the absence of them that gives rise to higher scores. For example it’s not the sound of low flying aircraft, but rather the absence, that scores well, whereas it is the contributing sounds to tranquillity where they are present that scores well.

For all of the maps, the input data is shown in the left panel with the results shown on the right. For all of the results maps, the darker the purple, the higher the score.

This section provides an overview of the indicators developed to contribute to theme 4 the sound environment part 2. Part 2 indicators include noise from roads and railways.

Part 2 ‘Combined’ considers all sources of sound that both contribute to and detract from tranquillity bringing part 1 and part 2 together to identify where natural sounds may be expected to be more prominent than noise and are appropriate to context. 

The full methodology behind the creation of these maps is  available to view in the accompanying report . For consistency scores were applied using a scale of 0 – 10, the highest predicted noise levels relate to the lowest tranquillity scores for all indicators.

For all of the maps, the input data is shown in the left panel with the results shown on the right. For all of the results maps, the darker the colour, the higher the tranquillity score.

This indicator considers the effect of hearing noise from low flying military aircraft. The louder the sound from military aircraft, the lower the tranquillity and therefore the lower tranquillity score.  Refer to the report for a fuller explanation and map of this indicator.

Once the data for themes 1 and 2 had been processed, the resultant datasets were combined and theme 3 (relative dark skies) was added. Since the values these layers contain did not have the same range, data was normalised to generate a range of 0 to 1 for each.

However, the scoring worked differently between the three themes. This was because theme 1 was measuring the presence of factors that add to tranquillity, whereas the other two were looking at factors that detract from it. Because of this, for themes 2 and 3, the values were inverted as part of the normalisation process, so that for all three themes, higher values mean more tranquil pixels.

Once these three themes had been normalised, their values were added together to produce the theme 5 map (visually tranquil places). The data on this map has a theoretical maximum range of 0 – 3, with 0 being the least tranquil areas, and 3 the most.

Once all other themes had been created, they were combined into the final Theme 6 result. As with Theme 5, the normalised values between 0 and 1 were added together to give a final value between 0 and 4 for each pixel, with 0 being the least tranquil areas, and 4 the most.

There is a need to recognise that pockets of tranquillity within urban areas are important, even if they are not truly tranquil by rural standards. Urban areas have been defined using the extent of the study areas mapped in the Urban Tree Cover data from the  TreeCover in Wales’ Towns and Cities project. 

This section presents the overview theme maps for the urban analysis. The mapping can be explored in more detail in the interactive webmap found in the next section.

9% of Wales’ urban areas are in the top 3 visually tranquil categories (albeit no urban areas have any percentage in the very highest category).

Of the 214 urban areas assessed, the following five urban areas have the highest percentage within the top 3 visually tranquil categories:      

• Llanmorlais & Crofty Penclawdd (87% within the top 3 visually tranquil areas)    
• Abertysswg (84% within the top 3 visually tranquil areas)
• Brynamman (79% within the top 3 visually tranquil areas) 
• Dolgellau (78% within the top 3 visually tranquil areas)
• Fochriw (78% within the top 3 visually tranquil areas)

Use the webmap below to explore the results of this study.

The results of this study are intended to be used in a number of ways, including:

◼ Highlighting the contribution these areas make to landscape value and identity, and as special qualities in designated landscapes.

◼ Identification of these areas can help to inform policy relating to their protection, conservation and enhancement to ensure their continued contribution to people and nature, including health, well-being, spiritual benefit and quality of life.

◼ Identifying places and areas of tranquillity close to where people live, connecting this to placemaking.

◼ To aid in aligning evidence and advice to positively inform planning application consultations, including an opportunity to target post Covid green recovery developments to consider tranquillity in their design and placemaking, linking to the Placemaking Charter.

◼ Providing evidence that can be incorporated into plans, assessments and evidence reports such as the State of Natural Resources Reporting (SoNaRR), Green Infrastructure Assessments, Area Statements, designated landscapes state of reports and management plans, local landscape character assessments and well-being assessments.

◼ Enabling the addition of quantitative tranquillity data to the LANDMAP Visual & Sensory dataset and landscape monitoring programme.

◼ The  Noise and Soundscape Plan for Wales 2023-2028 

◼ Over time, if this study were to be repeated, changes in tranquillity could be measured and monitored to see if increased awareness of the importance of tranquillity is making a positive difference.