Developing a Calculation Workflow for Designing and Monitoring Urban Ecological Corridors: A Case Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Land Use
2.3. The Geo-Database OpenStreetMap
- [out:xml] [timeout:25];
- (
- node[“landuse”=“forest”]( {{bbox}});
- node[“natural”=“wood”]( {{bbox}});
- node[“leisure”=“nature_reserve”]( {{bbox}});
- way[“landuse”=“forest”]( {{bbox}});
- way[“natural”=“wood”]( {{bbox}});
- way[“leisure”=“nature_reserve”]( {{bbox}});
- relation[“landuse”=“forest”]( {{bbox}});
- relation[“natural”=“wood”]( {{bbox}});
- relation[“leisure”=“nature_reserve”]( {{bbox}});
- );
- (._;>;);
- out body;
2.4. GIS Software
- -
- -
- least_cost_path function:
- --
- input: the function takes as input the cost grid, the starting and the arrival points;
- --
- initialization: a distance matrix is initialized with infinite values and a matrix to keep track of the predecessors to reconstruct the path. The initial distance of the starting point is set to 0;
- --
- priority queue phase: a priority queue is used to manage the nodes to be explored, while the starting point is added to the queue with cost 0;
- --
- execution of Dijkstra’s algorithm [50]:
- ---
- extracting the node with the lowest cost from the priority queue;
- ---
- check the extracted node because if it is the arrival point, the algorithm ends;
- ---
- neighbor expansion, i.e., for each neighbor of the current node, the cost to reach it is calculated. If this cost is lower than the cost already recorded for the neighbor, the distance and predecessor are updated and the neighbor is added to the priority queue with the new cost;
- --
- route reconstruction: once the arrival point is reached, the route is reconstructed by going back through the predecessors from the arrival point to the starting point;
- --
- output: the function returns the minimum cost path as a list of coordinates and the total cost of the path.
- -
- Raster calculator [51], a tool that allows you to perform advanced mathematical operations on raster data, was used to calculate the cost map;
- -
- Extract patches algorithm, to isolate different patches based on land use;
- -
- Centroids algorithm, to identify the geometric center of gravity of the extrapolated patches that assume the function of starting point in the least cost path algorithm.
2.5. Movement Cost Map
3. Case Study Results
4. Discussion
Future Research Perspectives
- Drones can be used to survey large areas quickly and non-invasively. With high-resolution cameras and thermal sensors, drones can detect the presence of animals and monitor their behavior, especially in areas that are difficult to access. For example, in Canada, drones have been used to map areas along the Bow River [64,65], identifying sections that needed interventions to improve habitat connectivity for aquatic and terrestrial species. Thanks to the high-resolution images obtained from drones, it is possible to plan and implement targeted interventions, such as the creation of wildlife passages and the planting of native vegetation. Drones can fly over large areas at regular intervals, collecting up-to-date data on habitat conditions and wildlife presence. For example, in Australia, drones are used to monitor ecological corridors along the coasts, collecting data on seabird populations and coastal vegetation [66]. This monitoring allows for the early detection of threats, such as the invasion of non-native species or changes in land use, allowing for rapid and targeted interventions.
- Artificial intelligence (AI) is particularly useful for analyzing large amounts of environmental data and modeling species movements, helping to identify the best routes through ecological corridors. AI algorithms can be used to analyze topographic, climate and biological data to design corridors that maximize connectivity and species survival. AI enables the simulation of various scenarios and assessment of the impact of different corridor configurations, optimizing design decisions. AI can analyze data collected from drones and other sources, identifying patterns and trends that may not be apparent to the naked eye [67]. A successful example is the work carried out by the Kenya Wildlife Service which uses drones and AI to map and monitor ecological corridors for elephants [68]. Drones provide up-to-date data on vegetation and elephant movements, while AI analyzes these data to predict the animals’ future routes and identify potential threats. In an urban context, drones could be used to map nests of species with high conservation value, threatened species and very wary species. This approach improves connectivity between national parks and reserves, reducing human–wildlife conflicts and promoting long-term conservation.
- Environmental DNA (eDNA) analysis: This technique involves taking samples of water, soil or air to detect traces of DNA released by animals. eDNA allows for monitoring of the presence of species without the need for direct sightings, offering an effective method to evaluate the fauna that uses ecological corridors.
- Camera traps: These devices are equipped with motion sensors, usually of the passive infrared type, and cameras that take photos or record videos when they detect the presence of animals. Camera traps are particularly useful for monitoring elusive or nocturnal species and can be installed along ecological corridors to record and census the passage of animals and to plan new ones based on their continuous presence in certain areas [69]. The installation of photo traps in areas preferred by animals allows us to identify the areas to be maintained (in which connectivity is not compromised), strengthened (in which it is only partially compromised) and compromised (in which connectivity is strongly compromised). In the two previous cases, the pressure factors must always be analyzed.
- GPS and telemetry: GPS collars can be applied to individuals of various species to track their movements. This technology provides precise data on the paths used by animals, allowing us to evaluate the effectiveness of ecological corridors and identify any barriers to movement. The recorded data can be easily managed with GIS software through which it is possible to obtain all the routes traveled and the movements [70].
- Acoustic sensors: These devices record the sounds produced by animals, such as calls and vocalizations, allowing the identification of many species. Acoustic sensors are particularly used to monitor the biodiversity of birds and amphibians in urban and peri-urban environments.
5. Conclusions
Funding
Data Availability Statement
Conflicts of Interest
References
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Land Use Code | Typology | Friction Value |
---|---|---|
1.1 | Agricultural use: Arable land | 30 |
1.2 | Agricultural use: Forage | 30 |
1.3 | Agricultural use: Permanent crops | 30 |
1.4 | Agricultural use: Agroforestry areas | 10 |
1.6 | Agricultural use: Other agricultural areas | 30 |
2 | Forestry use | 5 |
3 | Mining areas | 90 |
4 | Urban areas | 100 |
5 | Water uses | 2 |
6.1 | Non-economic uses: Wetlands | 1 |
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Massarelli, C. Developing a Calculation Workflow for Designing and Monitoring Urban Ecological Corridors: A Case Study. Urban Sci. 2024, 8, 169. https://doi.org/10.3390/urbansci8040169
Massarelli C. Developing a Calculation Workflow for Designing and Monitoring Urban Ecological Corridors: A Case Study. Urban Science. 2024; 8(4):169. https://doi.org/10.3390/urbansci8040169
Chicago/Turabian StyleMassarelli, Carmine. 2024. "Developing a Calculation Workflow for Designing and Monitoring Urban Ecological Corridors: A Case Study" Urban Science 8, no. 4: 169. https://doi.org/10.3390/urbansci8040169
APA StyleMassarelli, C. (2024). Developing a Calculation Workflow for Designing and Monitoring Urban Ecological Corridors: A Case Study. Urban Science, 8(4), 169. https://doi.org/10.3390/urbansci8040169