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1 = 2.1.2 Connectivity of green space =
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4 ====== **Social challenge/ impact linked to:** ======
5 )))|Environmental
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7 ====== **Co-creation phase linked to:** ======
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9 A) Understanding & establishing co-creation  
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12 ====== **Level of importance** ======
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14 **1** - High Importance / must have
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17 ====== **Description** ======
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19 Measuring the potential for green or blue areas to amplify the connectivity and multifunctionality of other urban green areas.
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21 One of the major impacts of urbanization is the fragmentation of open spaces into smaller and more isolated patches. Increased fragmentation of green in urbanized areas can reduce intra- and inter-species connectivity and lead to a loss of biodiversity (Kettunen et al., 2007). Fragmentation of green areas and distance between habitat patches is thus an important factor in determining biodiversity. A Green Infrastructure approach, linking parks and other green spaces, is therefore considered essential for the preservation of biodiversity and to counter further habitat fragmentation and increase connectivity (Sylwester, 2009). Connectivity of landscapes can be evaluated in terms of:
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23 * Structural connectivity – relating to the spatial configuration of patches, without considering the movement of individual organisms among these patches (Ioja et al. 2014) and
24 * Functional connectivity – relating to the ability of organisms to move among patches (Tischendorf and Fahrig 2000). (((
25 The index CIi can be calculated by measuring edge-to-edge distances between study site (separately for large and small study sites) and all other habitat patches within the 2-km radius of each landscape.
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27 Indicators of Green Infrastructure sub-criterion will assess the landscape connectivity and the mosaic diversity.
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30 Biodiversity is the measure of biological variety in the environment and it has an important role in functioning ecosystems services and health of environment and society. Biodiversity is an aspect of natural environment that is most directly affected by anthropogenic influence. City biodiversity is seen as an important aspect of sustainable and resilient urban development.** The fragmentation of natural environments is a major threat to biodiversity as scattered and non-connected natural areas are much less efficient in preserving biodiversity than large and connected areas.**
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32 This environmental (biological) indicator evaluates the increases of connectivity related to existing green infrastructures.
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34 The extent and spatial arrangement of accessible green space within each sub-demo area may have an important influence on public health and wellbeing; as well as having the potential to increase biodiversity. Vegetated areas provide cooling on hot days through evapotranspiration; and trees reduce radiant heat by shading, making public space and travelling routes more comfortable for people on days when temperatures in urban areas are high. **This KPI will focus on public accessible greenspace, therefore residential gardens will not be considered here**
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37 Both types of connectivity can be quantified using metrics that span different ranges of scale and complexity.
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39 Evaluation of blue-green space structural and functional connectivity can be used to:
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41 * Underpin green infrastructure and biodiversity spatial planning;
42 * Prioritise sites for interventions;
43 * Assess that impacts of NBS projects on pre-existing green networks;
44 * Promote active transport initiatives.
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47 [[image:https://divairwiki.eco-wise.co.uk/bin/download/5.%20Metrics%20and%20KPIs/Metric%20and%20Key%20Performance%20Indicators/3.2.2%20CGS%20-%20Connectivity%20of%20Green%20Spaces/WebHome/1641805952858-145.png?width=301&height=153&rev=1.1||alt="1641805952858-145.png" height="153" width="301"]]
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49 (Source: N4C CGS - Connectivity of Green Spaces)
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52 ====== **Scale as linked to D2.2 framework** ======
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56 * City
57 * Neighborhood
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63 ====== **Data source and input type** ======
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65 * Satellite/ map
66 * Corine Land Cover
67 * National databases (ex. Urban Atlas (only for big cities) ; OSGE in France…) ; BD TOPO
68 * Local spatial databases / green cadastre
69 * (((
70 Earth observation/Remote sensing methods: Remotely sensed data are inherently suited to provide information on urban vegetation and land cover characteristics, and their change at various geographical scales. However, the higher resolution required, the more expensive would be the RS data needed. In some cases, it would be better to use images provided by drones, but in this case permissions for survey mapping will be required and depends on the local and national/government regulations.
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73 |(((
74 ====== **Connection with SDGs** ======
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78 * Goal 3: Good health and well-being
79 * Goal 11: Sustainable cities and communities
80 * Goal 15: Life on land
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82 |(((
83 ====== **Required Data** ======
84 )))|(((
85 **~ Structural connectivity**
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87 * Land use maps e.g. CORINE
88 * Data on zones in the natural or naturalized conditions in the urban area of interest from, e.g., government agencies, municipalities, nature groups, universities, etc.
89 * polygon area of green space
90 * Distance to other green spaces
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92 **Functional connectivity**
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94 * Distance between study site and other habitat patches within a 2km radius.
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96 )))
97 |(((
98 ====== **Expected Outputs** ======
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100 **~ Structural connectivity**
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102 * Annual measurements
103 * Connectivity from 1 (very low) to 5 (very high)
104 * Quantitative
105 * Map
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107 **Functional connectivity**
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109 * (% style="background-color:transparent" %)ha of potential habitat
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111 |(((
112 ====== **Calculation methods** ======
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114 **~ Structural connectivity**
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116 * To estimate fragmentation, natural areas are defined and then estimation is made about their connections. A mesh indicator value is calculated. Natural areas are categorized into separate interconnected patches. The area of each patch is summed, squared and these squares are summed and divided by the total area of natural areas.
117 * [[image:https://divairwiki.eco-wise.co.uk/bin/download/5.%20Metrics%20and%20KPIs/5.3%3A%20External%20References%20-%20EU%20independent%20Expert%20Report/4.1%20Structural%20and%20functional%20connectivity%20of%20urban%20green%20and%20blue%20spaces/4.11%20Structural%20connectivity%20of%20green%20space/WebHome/1642496454372-369.png?rev=1.1||alt="1642496454372-369.png"]]
118 * This index (in hectares) is a metric - mesh indicator - used in the indicator value.
119 * Typology map data representing areas of GI both before and after NBS GI interventions will be analysed using a Geographic Information System (GIS) to calculate change in each sub-demo area in
120 ** a) the proportion of the sub demo area represented by GI,
121 ** b) distance between areas of GI, and
122 ** c) the number of street trees
123 * Use of GIS to calculate % change in the following parameters in each sub-demo area following NBS GI interventions:
124 ** The extent of accessible GI. Calculate the proportion of the sub-demo area occupied by GI (select all GI types in typology layer except residential gardens) pre- and post- GI interventions.
125 ** The distance between each accessible GI patch and its nearest accessible GI neighbour within the sub-demo area. If d is the nearest-neighbour (Euclidean) distance from accessible GI patch i to accessible GI patch j; calculate the mean nearest neighbour distance over all patches, both pre- and post-intervention (FRAGSTATS, 2015)
126 ** The distance to the nearest accessible green infrastructure everywhere (for every raster cell) calculated using a raster nearest neighbour approach
127 ** the number of street trees
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129 **N4C CGS - Connectivity of Green Spaces**
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131 * GIS analysis
132 * Formula:
133 ** Buffer (polygon i) = sqrt (Areapolygon i/π)
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135 |(((
136 ====== **Level of expertise required** ======
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138 * High
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140 |(((
141 ====== **Links and references** ======
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143 **EU handbook Structural connectivity of green space**
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145 * Chan, L., Hillel, O., Elmqvist, T., Werner, P., Holman, N., Mader, A., & Calcaterra, E. (2014). User’s Manual on the Singapore Index on Cities’ Biodiversity (also known as the City Biodiversity Index). Singapore: National Parks Board, Singapore.
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147 **EU handbook Publicly accessible green space connectivity**
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149 * URBAN GreenUP KPI: Increased connectivity to existing green infrastructure
150 * URBAN GreenUP Deliverable D2.4 - Monitoring program to Valladolid. https:~/~/www.urbangreenup.eu/insights/deliverables/d2-4~-~-- monitoring-program-to-valladolid.kl
151 * URBAN GreenUP Deliverable D3.4 - Monitoring program to Liverpool https:~/~/www.urbangreenup.eu/insights/deliverables/d3-4~-~-- monitoring-program-to-liverpool.kl
152 * URBAN GreenUP Deliverable D4.4 – Monitoring program to Izmir https:~/~/www.urbangreenup.eu/insights/deliverables/d4-4~-~- monitoring-program-to-izmir.kl
153 * URBAN GreenUP Deliverable D5.3: City Diagnosis and Monitoring Procedures https:~/~/www.urbangreenup.eu/insights/deliverables/d5-3- city-diagnosis-and-monitoring-procedures.kl
154 * Data processing software:
155 ** https:~/~/www.qgis.org/en/site/forusers/download.html#
156 ** https:~/~/docs.qgis.org/2.18/en/docs/user_manual/ :~/~/plugins.qgis.org/plugins/LecoS/
157 ** http:~/~/www.umass.edu/landeco/research/fragstats/fragstats.html.
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159 **EU handbook Functional connectivity of urban green and blue spaces**
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164 **EU handbook Structural and functional connectivity of urban green and blue spaces**
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166 Applied methods:
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229 **N4C CGS - Connectivity of Green Spaces**
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236 Revisions
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238 |**Version**|**Name**|**Date**|**Changes made**
239 |**0.1**|Hyunji (EcoWise)|28/02/2022|Compiled related fact sheets
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