An Accessible Greenspace Standard (AGST) search is provided via the ‘Search Data layers’ button at the top of the screen and selecting ‘Green Infrastructure standards’.
The search allows users to draw a custom boundary around their project area and obtain a series of returns relating to mapped accessible greenspace & related analysis within the drawn polygon – pulling this information together into one place to provide a custom return.
The results first show area of mapped publicly accessible Green Infrastructure within the search polygon as taken from the site (Section 1. All GI Assets that are thought to be publicly accessible). This is displayed above the table alongside the area of the drawn polygon.
The results then present a table that shows the percentage of the drawn polygon that is occupied by the following mapped AGST dataset listed in section 2. Access to Greenspace Standards datasets listed below (within a drawn search area):
These results are shown in column 3. The location of each of these datasets can be viewed using the eye icon under the ‘view’ heading’ (column 2).
This is then combined with returns that list the attributes from corresponding data analysis from both:
i) Section 8. Accessible Greenspace Inequalities (IMD) – as shown in column 4.
ii) Section 9. Accessible Greenspace Inequalities (population density) – as shown in column 5.
Explanations for the different Classes L1, L2, L3, M1, M2, M3, H1, H2 H3 are provided in Section 8.9 of the GI mapping data guide. Where multiple classes are returned from any of the above datasets, the attributes will be listed in series, e.g., L2, M3. The results are then synthesised to provide an implied area need (expressed in the final column, column 6). This is based on a simple rule set that states that, where L1-3 classes are returned, for either Accessible Greenspace Inequality and Deprivation or Population Density, implied need will be expressed as high. Where the classes H1-3 are returned in the absence of the above a low implied need is suggested. This approach is provisional and may be revised following further feedback. Please note these results are indicative only and are intended to assist the user when interpreting multiple class data.