Inside-outside park planning: A mathematical approach to assess and support the design of ecological connectivity between Protected Areas and the surrounding landscape

Monaco, Roberto; Negrini, Gabriella; Salizzoni, Emma Paola Germana; Soares, Ana Jacinta; Voghera, Angioletta

doi:10.1016/j.ecoleng.2020.105748

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…Unlike small-scale ecological planning 12 , 46 , 47 as a planning method based on the large-scale data, provincial ecological network and node identification is mainly used to guide macro-planning and provide guidance for further detailed planning and design. The identification results need to be highly generalized and combined with manual selection.…”

Section: Discussionmentioning

confidence: 99%

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Identification of ecological networks and nodes in Fujian province based on green and blue corridors

Zhou

Bosch

Chen

et al. 2021

Sci Rep

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China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward.

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Section: Discussionmentioning

confidence: 99%

“…The data quantification method was used to identify ecological networks mostly used in ecological planning 39 , 41 , 47 , 68 , 69 . However, the cross-disciplinary nature of GSSP is in line with a broader development trend in China 31 , 70 – 72 and elsewhere 73 – 79 .…”

Section: Discussionmentioning

confidence: 99%

Identification of ecological networks and nodes in Fujian province based on green and blue corridors

Zhou

Bosch

Chen

et al. 2021

Sci Rep

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“…LESP optimization aims to construct a scientific optimization spatial structure and ecological network with a practical guiding significance for protecting the ecological environment and promoting regional coordinated development. Currently, the graph theory and spatial simulation methods are adopted in the field of LESP optimization to realize its research objectives (Li et al 2010;Yu et al 2018;Monaco et al 2020).…”

Section: Introductionmentioning

confidence: 99%

How can the landscape ecological security pattern be quantitatively optimized and effectively evaluated? An integrated analysis with the granularity inverse method and landscape indicators

Guan

Jiang

Cheng

2022

Environ Sci Pollut Res

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The optimization of the landscape ecological security pattern aims to construct a suitable ecological environment and promote the harmonious development between humans and nature. The optimization model of the ecological security pattern for the main urban area of Chongqing was constructed with the granularity inverse method, minimum cumulative resistance model, and spatial network analysis method. We used ecological nodes to optimize the landscape ecological security pattern by organically combining the landscape quantity and spatial structure. The results were as follows: (1) The optimal granularity for selecting the ecological source in the study area was 500 m. There were 220 ecological sources with a total area of 188691.03 hm 2 and a minimum area of 75.15 hm 2 . (2) The ecological buffer zone, protection and utilization zone, key development zone, coordinated control zone, and restricted development zone accounted for 57.78%, 20.87%, 12.36%, 6.48% and 2.50%, respectively, of the total area. (3) The constructed of the landscape ecological security pattern contained 70 ecological corridors with a total length of 415.89 km. The longest and shortest ecological corridors had lengths of 20.33 km and 1153.23 m, respectively. There were 17 ecological nodes of corridor-resistance and 27 ecological nodes of corridor-corridor. (4) 41 ecological node service areas were constructed, with a total area of approximately 236.0723 hm 2 , accounting for 0.04% of the total study area, and the largest and smallest ecological node areas were 6.0744 hm 2 and 0.0057 hm 2 , respectively. (5) The optimized result of the landscape ecological security pattern converted 209.1384 hm 2 of nonecological land into ecological land.

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“…From the viewpoint of stochastics, there is no such thing as a "virus of randomness" that infects some phenomena to make them random, leaving other phenomena uninfected. Rather, both randomness and predictability coexist and are intrinsic to natural systems, which can be deterministic [50][51][52] and random at the same time, depending on the prediction horizon and the time scale [53]. This research aims to develop a stochastic analysis method to quantify both the spatial structures in terms of clustering as well as the temporal evolution thereof.…”

Section: Introductionmentioning

confidence: 99%

Landscape Planning of Infrastructure through Focus Points’ Clustering Analysis. Case Study: Plastiras Artificial Lake (Greece)

et al. 2021

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Even though landscape quality is largely a subjective issue, the integration of infrastructure into landscapes has been identified as a key element of sustainability. In a spatial planning context, the landscape impacts that are generated by infrastructures are commonly quantified through visibility analysis. In this study, we develop a new method of visibility analysis and apply it in a case study of a reservoir (Plastiras dam in Greece). The methodology combines common visibility analysis with a stochastic tool for visual-impacts evaluation; points that generate high visual contrasts in landscapes are considered Focus Points (FPs) and their clustering in landscapes is analyzed trying to answer two questions: (1) How does the clustering of Focus Points (FPs) impact the aesthetic value of the landscape? (2) How can the visual impacts of these FPs be evaluated? Visual clustering is calculated utilizing a stochastic analysis of generated Zones of Theoretical Visibility. Based on the results, we argue that if the visual effect of groups of FPs is positive, then the optimal sitting of FPs should be in the direction of faint clustering, whereas if the effect is negative, the optimal sitting of FPs should be directed to intense clustering. In order to optimize the landscape integration of infrastructure, this method could be a useful analytical tool for environmental impact assessment or a monitoring tool for a project’s managing authorities. This is demonstrated through the case study of Plastiras’ reservoir, where the clustering of positively perceived FPs is found to be an overlooked attribute of its perception as a highly sustainable infrastructure project.

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Inside-outside park planning: A mathematical approach to assess and support the design of ecological connectivity between Protected Areas and the surrounding landscape

Cited by 11 publications

References 15 publications

Identification of ecological networks and nodes in Fujian province based on green and blue corridors

Identification of ecological networks and nodes in Fujian province based on green and blue corridors

How can the landscape ecological security pattern be quantitatively optimized and effectively evaluated? An integrated analysis with the granularity inverse method and landscape indicators

Landscape Planning of Infrastructure through Focus Points’ Clustering Analysis. Case Study: Plastiras Artificial Lake (Greece)

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