Neighbourhood green — condition 2016

The geodata layer “neighborhood green” contains all clusters of publicly accessible green space with a minimum area of 1 ha. This geodata layer was obtained through the selection of all “green areas” based on the land use map (state 2016). These green areas were algorithmically clustered on the basis of contiguousness, including physical barriers. Then, only those green areas were kept adjacent to a public road accessible on foot. Based on this, five raster layers (resolution 10x10m²) were formatted where clusters were selected per function level based on a minimum surface area: green (> 1 ha); district green (> 10 ha); district green (> 30 ha); urban green (> 60 ha); city forest (> 200 ha). The selected clusters with a higher function level are therefore always a subset of the selected clusters of a lower function level. Attention, due to the method used, the green type ‘city forest’ consists not only of forest, but of different types of green space. More information can be found in this background document: https://archief-algemeen.omgeving.vlaanderen.be/xmlui/bitstream/handle/acd/768624/Groentypo_2019.pdf The method described therein was applied to the land use map, condition 2016. The presence of greenery has a positive effect on a number of different aspects that determine a qualitative living environment. This includes a positive impact on physical, mental and social health, but also biodiversity, climate resilience, landscape quality,... A common Flemish reference framework (introduced in MIRA-S 2000) to assess the availability of green space states that every resident should have access to neighbourhood green at a maximum of 400 m, neighbourhood green at a maximum of 800 m, urban green at a maximum of 1 600 m, urban green at a maximum of 3 200 m and city forest at a maximum of 5 000 m. This data layer allows, among other things, to calculate the number of inhabitants in a given area that has access to neighbourhood green taking into account the above mentioned maximum distance.