Chapter 3 – Positive indicators details
This section gives the full details of the data used, the process followed and any assumptions made for each positive indicator. The level of detail provided will support repeat analysis in the future.
Each indicator is presented with the following structure:
- Datasets – setting out the data sources used for both All South and Vale and Urban analysis;
- Method – describes the way in which the indicator has been modelled for both All South and Vale and Urban; and
- Result – maps of the raw input data and resulting processed indicator for both All South and Vale and Urban.
Indicator P01 - Naturalness of the land cover
Datasets
All South and Vale: Corine Land Cover 2018 (European Environment Agency)
Urban: OS MasterMap
Method
All South and Vale: Each 50 metre pixel in the study area was split into categories based on the Corine land cover type and given a score based on the most natural type it contains. The scores for each Corine land cover type are broken down in Appendix B, Table B-1.
Urban: Each 10 metre pixel in the urban areas was split into categories based on the OS MasterMap Descriptive Term and given a score based on the most natural type it contains. The scores for each Mastermap Descriptive Term are broken down in Appendix B, Table B-2.
Results
The results of the analysis for All South and Vale are shown in Figure 3.1 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.2. Higher scores represent a higher contribution to tranquillity and lower scores contribute less to tranquillity.
Figure 3.1: P01 Naturalness of land cover - all South and Vale data and results
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Figure 3.1: P01 Naturalness of land cover - all South and Vale data and results
Figure 3.2: P01 Naturalness of land cover - Urban data and results
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Figure 3.2: P01 Naturalness of land cover - Urban data and results
Indicator P02 – Seeing rivers and canals
Datasets
All South and Vale: OS OpenRivers (canals and inland rivers)
Urban: OS OpenRivers (canals and inland rivers)
Method
All South and Vale: Points were generated every 100m along rivers and canals and visibility was calculated from each pixel of the analysis. The rivers and canals were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-1: Scoring P02 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: Points were generated every 100m along rivers and canals and visibility calculated from each pixel of the analysis. The rivers and canals were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-2: Scoring P02 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.3 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.4. More visibility increases the contribution towards tranquillity, therefore higher scores represent more contribution to tranquillity and lower scores contribute less to tranquillity.
Figure 3.3: P02 Seeing rivers and canals all South and Vale data and results
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Figure 3.3: P02 Seeing rivers and canals all South and Vale data and results
Figure 3.4: P02 Seeing rivers and canals – Urban data and results
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Figure 3.4: P02 Seeing rivers and canals – Urban data and results
Indicator P03 – Seeing lakes
Datasets
All South and Vale: OS Open Map Local surface water (streams removed, only features > 2ha)
Urban: OS Open Map Local surface water (streams removed, only features > 2ha)
Method
All South and Vale: Points were generated at 100m intervals and intersected with waterbodies larger than 2ha. Another set of points was generated at 100m intervals around the perimeter of the waterbodies. Using these two sets of points, visibility was calculated from each pixel in the analysis area. The waterbodies were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-3: Scoring P03 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: The same method as All South and Vale was applied, with 100m interval points. Buffers were generated and pixels scored as per the table below.
Table 3-4: Scoring P03 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.5 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.6. More visibility increases the contribution to tranquillity, therefore higher scores represent areas with a greater contribution to tranquillity and lower scores represent areas making a lesser contribution to tranquillity.
Figure 3.5: P03 Seeing lakes - all South and Vale data and results
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Figure 3.5: P03 Seeing lakes - all South and Vale data and results
Figure 3.5: P03 Seeing lakes - all South and Vale data and results
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Figure 3.5: P03 Seeing lakes - all South and Vale data and results
Indicator P04 – Seeing broadleaved woodland above 2.5 ha
Datasets
All South and Vale: National Forest Inventory (NFI) 2020 (selected categories: assumed woodland, broadleaved, mixed mainly broadleaved). Woodland >2.5 ha was selected based on the average size of broadleaved woodland ‘patches’ as per NFI in South Oxfordshire and Vale of White Horse Districts
Urban: As data on urban trees were not available, the same woodland categories as for the All South and Vale analysis were selected from the NFI dataset but only within the 6km buffer outside of the urban areas to represent woodland visibility from urban into rural areas.
Method
All South and Vale: Points were generated at 100m intervals and intersected with the selected woodland areas. Another set of points was generated at 100m intervals around the perimeter of the woodland areas. Using these two sets of points, visibility was calculated from each pixel in the analysis area. The woodland areas were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-5: Scoring P04 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: The same method as All South and Vale was applied, with 100m intervals points. Buffers were generated and pixels scored as per the table below.
Table 3-6: Scoring P04 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.7 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.8. More visibility increases the potential contribution to tranquillity, therefore higher scores represent more contribution towards tranquillity and lower scores contribute less to tranquillity.
Figure 3.7: P04 Seeing broadleaved woodland - all South and Vale data and results
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Figure 3.7: P04 Seeing broadleaved woodland - all South and Vale data and results
Figure 3.8 P04 Seeing broadleaved woodland - Urban data and results
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Figure 3.8 P04 Seeing broadleaved woodland - Urban data and results
Indicator P05 – Seeing plantation/coniferous woodland above 2.5 ha
Datasets
All South and Vale: National Forest Inventory (NFI) 2020 (selected categories: conifer, mixed mainly conifer). Woodland >2.5 ha was selected based on the average size of coniferous woodland as per NFI in South Oxfordshire and Vale of White Horse Districts
Urban: The same categories as for the All South and Vale analysis were selected from the NFI dataset but only within the 6km buffer outside of the urban areas because there were no plantation areas within the urban areas.
Method
All South and Vale: Points were generated at 100m intervals and intersected with the selected woodland areas. Another set of points was generated at 100m intervals around the perimeter of the woodland areas. Using these two sets of points, visibility was calculated from each pixel of the analysis. The woodland areas were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility. Based on findings from a previous tranquillity assessment carried out for Central Bedfordshire Council, the range of scores for plantation/coniferous woodland did not go as high as 5 as it did for broadleaved woodland (P04).
Table 3-7: Scoring P05 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 3 | 2 | 1 | 0 | 0 |
Urban: The same method as All South and Vale was applied, with 100m intervals points. Buffers were generated and pixels scored as per the table below.
Table 3-8: Scoring P05 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 3 | 2 | 1 | 0 | 0 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.9 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.10. More visibility increases the potential contribution to tranquillity, therefore higher scores represent higher contribution towards tranquillity and lower scores less contribution.
Figure 3.9: P05 Seeing plantation / coniferous woodland – all South and Vale data and results
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Figure 3.9: P05 Seeing plantation / coniferous woodland – all South and Vale data and results
Figure 3.10 P05 Seeing plantation / coniferous woodland – Urban data and results
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Figure 3.10 P05 Seeing plantation / coniferous woodland – Urban data and results
Indicator P06 – Seeing the stars at night
Datasets
All South and Vale: LUC Dark Skies Map (output from the Dark Skies Assessment). The original map is 400m resolution, so it was resampled to 50m pixels to match the scale of analysis at All South and Vale level. It must be noted that this does not increase the precision of the data, it merely aligns the pixel sizes.
Urban: LUC Dark Skies Map (output from the Dark Skies Assessment). The original map is 400m resolution, so it was resampled to 10m pixels to match the scale of analysis at the urban areas level. It must be noted that this does not increase the precision of the data, it merely aligns the pixel sizes.
Method
All South and Vale: The dark skies map was re-classified into four categories as per the table below. The darkest pixels (<0.25 nanoW/cm²/sr) were scored with the highest contribution to tranquillity score. Pixels between 0.25 and 0.5 nanoW/cm²/sr were scored with an intermediate contribution to tranquillity score. Pixels between 0.5 and 1 nanoW/cm²/sr were scored with a lower contribution to tranquillity score as they are still dark enough to allow stars to be seen, but not as dark as the previously mentioned pixels. Finally, all other pixels were scored 0 as they are considered to be too bright to allow for a very high quality view of a starry sky (such that it would contribute to tranquillity).
Table 3-9: Scoring P06 All South and Vale
| Brightness (nanoW/cm2/sr) | <0.25 | 0.25 – 0.5 | 0.5 – 1 | >1 |
| Score | 5 | 3 | 1 | 0 |
Urban: The dark skies map was re-classified following the same method as for All South and Vale.
Table 3-10: Scoring P06 Urban
| Brightness (nanoW/cm2/sr) | <0.25 | 0.25 – 0.5 | 0.5 – 1 | >1 |
| Score | 5 | 3 | 1 | 0 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.11 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.12. Darker skies provide the potential for a higher quality view of the stars at night, therefore these areas were given a higher score as seeing a starry sky contributes to tranquillity.
Figure 3.11: P06 Seeing the stars at night - all South and Vale data and results
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Figure 3.11: P06 Seeing the stars at night - all South and Vale data and results
Figure 3.11: P06 Seeing the stars at night - all South and Vale data and results
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Figure 3.11: P06 Seeing the stars at night - all South and Vale data and results
Indicator P07 – Hearing nature
This indicator assumes all sounds of nature contribute to tranquillity. It encompasses hearing bird song, wildlife, silence, peace and quiet and no human sounds. The louder the sound, the more it is expected to contribute positively to tranquillity, therefore higher scores are more tranquil and lower scores mean a lower contribution to tranquillity from hearing nature and natural sounds.
There is no dataset to directly map this indicator. Therefore a proxy indicator is required. For this indicator, scores were applied to locations depending on their likelihood of being able to hear enhanced sounds of nature and natural sounds. For instance, in an urban area it may be more unlikely for nature to be heard than it would be outside of an urban area. Higher scores were therefore given for pixels outside of urban areas, as well as pixels within nature conservation related designations and sites. This is based on the assumption that within these designated areas, management and conservation of nature is prioritised and so the chances of having an opportunity to hear nature and natural sounds are likely to be higher.
Datasets
All South and Vale: National Forest Inventory (NFI) 2020 (selected categories: assumed woodland, broadleaved, mixed mainly broadleaved, mixed mainly conifer, shrub), Ancient Woodland Inventory (AWI), Special Area Conservation (SAC), Site of Special Scientific Interest (SSSI), Local Nature Reserve (LNR), National Nature Reserve (NNR), Country Parks and Local Wildlife Sites.
Urban: The same categories as for the All South and Vale analysis were selected from the NFI dataset, AWI, SAC, SSSI, LNR, NNR, Country Parks, Local Wildlife Sites, Natural England Green Infrastructure (selected categories: Access Land, Activity Spaces Provision, Allotments and Community Growing Spaces, Cemeteries and Religious Grounds, Golf Course, Millenium or Doorstep Green, Other Sports Facilities, Play Space Provision, Playing Fields, Public Park – general)
Method
All South and Vale: All pixels outside of the urban areas were given a score of 4. Any pixels outside of the urban areas and which fall within the datasets listed in the Datasets section above were given the highest score for tranquillity of 5. This means that smaller towns and villages outside of the larger urban areas selected for the tranquillity urban analysis will be given high scores. To exclude those a definition of how large these settlements need to be before they cause a decrease in the likelihood of hearing nature would be needed. Since this information was not available in the literature these smaller settlements were left in.
Urban: The same method as All South and Vale was applied, with pixels outside of the selected urban areas scoring 4 and pixels within the listed datasets scoring 5.
Results
The results of the analysis for All South and Vale are shown in Figure 3.13 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.14. Scores are based on the likelihood of being able to hear natural sounds, with higher scores attributed to locations with a higher likelihood of hearing these sounds.
Figure 3.13: P07 Hearing nature - all South and Vale data and results
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Figure 3.13: P07 Hearing nature - all South and Vale data and results
Figure 3.14 P07 Hearing nature - Urban data and results
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Figure 3.14 P07 Hearing nature - Urban data and results
Indicator P08 – Seeing elevated areas
Datasets
This indicator represents the ability to see elevated areas. Stakeholders gave feedback on this indicator following the pilot mapping, pointing out the initial lack of variation in scoring. For instance, the lower-lying farmland in the Vale of White Horse should score high as it is an area where one can stand and see both the National Landscapes and the Corallian Ridge and feel part of this large scale landscape, which contributes to tranquillity. The pilot mapping for this indicator was revised and the classification method improved in order to pick up these areas where elevated areas are visible from and therefore the contribution to tranquillity is higher.
All South and Vale: grid of points at 200m intervals over all South and Vale
Urban: Grid of points at 200m intervals over the 6km buffer outside of the urban areas
Method
All South and Vale: Points were generated at 200m intervals over the South Oxfordshire and Vale of White Horse districts. Visibility was calculated from each pixel of the analysis using this grid of points. The pixels were then grouped into five categories based on the number of visible points. Scores were given to these five categories, with the highest score given to the top 20% with the most visibility, the second highest score given to the 20% with the next most visibility and so on as per the table below.
Table 3-11: Scoring P08
| Category | 1 | 2 | 3 | 4 | 5 |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: For views out of the urban areas into open countryside (the 6km buffer outside of the urban areas), the same approach as the All South and Vale analysis was used with a 200m grid of points. Visibility was calculated from each pixel of the analysis using this grid of points. Using the same categories as for All South and Vale (table above) the pixels were grouped into five categories and scores were attributed.
Results
The results of the analysis for All South and Vale are shown in Figure 3.15 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.16. More visibility increases the potential contribution to tranquillity, therefore higher scores represent more contribution towards tranquillity and lower scores contribute less to tranquillity. The maps clearly show lower areas where higher ground can be seen in the centre of both districts. However some areas scored lower than expected, such as the south western section of the North Wessex Downs National Landscape.
Figure 3.15: P08 Seeing elevated areas - all South and Vale data and results
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Figure 3.15: P08 Seeing elevated areas - all South and Vale data and results
Figure 3.16: P08 Seeing elevated areas - Urban data and results
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Figure 3.16: P08 Seeing elevated areas - Urban data and results
Indicator P09 – Seeing natural designations
Datasets
All South and Vale: National Landscape, Special Area Conservation (SAC), Site of Special Scientific Interest (SSSI), Local Nature Reserve (LNR), National Nature Reserve (NNR).
Urban: National Landscape, Special Area Conservation (SAC), Site of Special Scientific Interest (SSSI), Local Nature Reserve (LNR), National Nature Reserve (NNR).
Method
All South and Vale: Points were generated at 250m intervals and intersected with the nature conservation designation areas from the datasets listed above. Using the intersected points, visibility was calculated from each pixel of the analysis. The areas were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-12: Scoring P09 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: The same method as All South and Vale was applied, with 250m intervals points. Buffers were generated and pixels scored as per the table below.
Table 3-13: Scoring P09 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.17 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.18. More visibility increases the potential contribution to tranquillity, therefore higher scores represent more contribution towards tranquillity and lower scores contribute less to tranquillity.
Figure 3.17: P09 Seeing natural designations - all South and Vale data and results
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Figure 3.17: P09 Seeing natural designations - all South and Vale data and results
Figure 3.18: P09 Seeing natural designations - Urban data and results
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Figure 3.18: P09 Seeing natural designations - Urban data and results
Indicator P10 – Seeing time depth
Datasets
All South and Vale: Scheduled monuments, historic parks and gardens
Urban: Scheduled monuments, historic parks and gardens
The pilot mapping included listed buildings and conservation areas. These were removed from the final mapping based on stakeholder feedback. Feedback suggested that the inclusion of listed buildings and conservation areas was overstating the contribution to tranquillity in settlements (where the density of listed buildings is typically higher).
Method
All South and Vale: Points were generated at 250m intervals and intersected with the scheduled monuments and historic parks and gardens. These datasets were buffered as per the table below, and the buffers were then combined with the results of the visibility analysis. Pixels were scored based on their distance from the feature and their visibility.
Table 3-14: Scoring P10 All South and Vale
| Distance | 500m | 1km | 2km | 5km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Urban: The same method as All South and Vale was applied, but with a grid of points at 50m intervals. Buffers were generated and pixels scored as per the table below.
Table 3-15: Scoring P10 Urban
| Distance | 100m | 200m | 400m | 1km | 6km |
| Score | 5 | 4 | 3 | 2 | 1 |
Results
The results of the analysis for All South and Vale are shown in Figure 3.19 and can be explored in more details in the Results interactive web map. Urban results are shown in Figure 3.20. More visibility increases the potential contribution to tranquillity, therefore higher scores represent a greater contribution to tranquillity and lower represent areas where the contribution to tranquillity is lower.
Figure 3.19: P10 Seeing time depth - all South and Vale data and results
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Figure 3.19: P10 Seeing time depth - all South and Vale data and results
Figure 3.20: P10 Seeing time depth - Urban data and results
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Figure 3.20: P10 Seeing time depth - Urban data and results