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Last modified by Emily West on 2022/03/08 16:48
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edited by Emily West
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on 2022/02/28 11:30
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1 1  = 2.1.2 Connectivity of green space =
2 2  
3 -(% class="table-bordered" %)
4 4  |(((
5 5  ====== **Social challenge/ impact linked to:** ======
6 6  )))|Environmental
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28 28  Indicators of Green Infrastructure sub-criterion will assess the landscape connectivity and the mosaic diversity.
29 29  )))
30 30  
31 -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.**
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.**
32 32  
33 33  This environmental (biological) indicator evaluates the increases of connectivity related to existing green infrastructures.
34 34  
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44 44  * Assess that impacts of NBS projects on pre-existing green networks;
45 45  * Promote active transport initiatives.
46 46  
46 +
47 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"]]
48 48  
49 49  (Source: N4C CGS - Connectivity of Green Spaces)
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55 55  
56 56  * City
57 57  * Neighborhood
58 +
59 +
60 +
58 58  )))
59 59  |(((
60 -
61 -
62 62  ====== **Data source and input type** ======
63 63  )))|(((
64 64  * Satellite/ map
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72 72  |(((
73 73  ====== **Connection with SDGs** ======
74 74  )))|(((
76 +
77 +
75 75  * Goal 3: Good health and well-being
76 76  * Goal 11: Sustainable cities and communities
77 77  * Goal 15: Life on land
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81 81  )))|(((
82 82  **~ Structural connectivity**
83 83  
84 -* Land use maps e.g. CORINE ([[CORINE Land Cover — Copernicus Land Monitoring Service>>url:https://land.copernicus.eu/pan-european/corine-land-cover]])
87 +* Land use maps e.g. CORINE
85 85  * 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.
86 86  * polygon area of green space
87 87  * Distance to other green spaces
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89 89  **Functional connectivity**
90 90  
91 91  * Distance between study site and other habitat patches within a 2km radius.
95 +
92 92  )))
93 93  |(((
94 94  ====== **Expected Outputs** ======
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221 221  * Wellmann, T., Haase, D., Knapp, S., Salbach, C. Selsam, P., Lausch, A. (2018) Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators. 85. 190-203. 10.1016/j.ecolind.2017.10.029
222 222  * Wessel M, Brandmeier M, Tiede D (2018) Evaluation of Different Machine Learning Algorithms for Scalable Classification of Tree Types and Tree Species Based on Sentinel-2 Data. Remote Sens., 10, 1419. [Google Scholar] [CrossRef]
223 223  
228 +
224 224  **N4C CGS - Connectivity of Green Spaces**
225 225  
226 226  * AUAT. (2015). Pour une approche globale du fonctionnement écologique potentiel des territoires, 8.