Synergy between green stormwater infrastructure and active mobility: A comprehensive literature review

Lemieux, Charlotte; Bichai, Françoise; Boisjoly, Geneviève

doi:10.1016/j.scs.2023.104900

Cited by 3 publications

(3 citation statements)

References 87 publications

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“…Previous studies have indicated that improving the urban environment through green infrastructure and sustainable city planning can encourage residents to choose cycling, fostering a healthier lifestyle [19]. Measures such as constructing dedicated bike lanes, optimizing urban green spaces, and planning roadside vegetation significantly encourage residents to opt for cycling as their primary mode of transportation [20]. Specifically, with the acceleration of urbanization, the development of sustainable transportation provides a new environment for cycling [21].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior

Qin,

Xu,

Huang

2024

Sustainability

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Cycling is a flexible way of traveling that can promote the development of urban public transportation. Previous studies on the influence of cycling have focused more on the cyclists themselves, ignoring the influences of the features of natural environments, such as streetscapes and land surface temperatures (LSTs), on cycling behavior. Therefore, in this study, street view image data and Landsat 8 imagery were utilized to extract streetscape and LST features; in particular, a framework was established for a single-indicator analysis and a multiple-indicator interaction analysis based on the random forest model with GeoDetector. The model was used to explore the effects of streetscapes and surface temperatures on cycling behavior. The results of this study for the main urban area of Beijing show that (1) high-density buildings and high population activity exacerbated the heat island effect at the city center and certain areas in the east, with the highest LST reaching 46.93 °C. In contrast, the greenery and water bodies in the northwestern and northeastern areas reduced the LST, resulting in a minimum temperature of 11.61 °C. (2) The optimal analysis scale was a 100 m buffer pair, and the regression fitting accuracy reached 0.83, confirming the notable influences of streetscape and LST characteristics on cycling behavior. (3) The random forest (RF) model results show that the importance of LST features and vegetation and sky conditions exceeded 0.07, and a reasonable sky openness and open building ventilation became the first choices for promoting cycling behavior. (4) According to the GeoDetector model, the LST features alone exhibited an importance of more than 0.375 for cycling behavior, while interactions with streetscapes greatly reduced the negative effect of LST on cycling behavior. The interaction between walls and plants reached 0.392, while the interaction between multiple environmental factors and greenery and favorable ventilation counteracted the negative impact of high-temperature heat waves on the residents’ choice of bicycles.

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Section: Introductionmentioning

confidence: 99%

Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior

Qin,

Xu,

Huang

2024

Sustainability

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“…GSI encompasses features such as bioretention areas, rain gardens, bioswales, green roofs, permeable pavements, green spaces, and wetlands, all of which utilize vegetation, substrate (or media), soils, and natural processes. GSIs have numerous environmental, social, and economic benefits, including stormwater-runoff reduction [4], air-quality improvement [5], heat-island-effect reduction [6], carbon storage and sequestration, resilience of drainage-system improvement, pollutant reduction, water-quality improvement, urban beautification, land-value increment, and energy-demand reduction [4][5][6][7]. Consequently, there is a global surge in interest and implementation of GSIs aimed at mitigating adverse impacts such as flooding, waterway contamination, and stream degradation.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, there is a global surge in interest and implementation of GSIs aimed at mitigating adverse impacts such as flooding, waterway contamination, and stream degradation. This is achieved by disconnecting the expanding impervious surfaces such as pavements and rooftops in the cities from the storm sewer systems [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Plant Density and Health Evaluation in Green Stormwater Infrastructure Using Unmanned-Aerial-Vehicle-Based Imagery

Xue,

Qian,

Kang

et al. 2024

Applied Sciences

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Over the past few decades, there has been a notable surge in interest in green stormwater infrastructure (GSI). This trend is a result of the need to effectively address issues related to runoff, pollution, and the adverse effects of urbanization and impervious surfaces on waterways. Concurrently, umanned aerial vehicles (UAVs) have gained prominence across applications, including photogrammetry, military applications, precision farming, agricultural land, forestry, environmental surveillance, remote-sensing, and infrastructure maintenance. Despite the widespread use of GSI and UAV technologies, there remains a glaring gap in research focused on the evaluation and maintenance of the GSIs using UAV-based imagery. This study aimed to develop an integrated framework to evaluate plant density and health within GSIs using UAV-based imagery. This integrated framework incorporated the UAV (commonly known as a drone), WebOpenDroneMap (WebDOM), ArcMap, PyCharm, and the Canopeo application. The UAV-based images of GSI components, encompassing trees, grass, soil, and unhealthy trees, as well as entire GSIs (e.g., bioretention and green roofs) within the Morgan State University (MSU) campus were collected, processed, and analyzed using this integrated framework. Results indicated that the framework yielded highly accurate predictions of plant density with a high R2 value of 95.8% and lower estimation errors of between 3.9% and 9.7%. Plant density was observed to vary between 63.63% and 75.30% in the GSIs at the MSU campus, potentially attributable to the different types of GSI, varying facility ages, and inadequate maintenance. Normalized difference vegetation index (NDVI) maps and scales of two GSIs were also generated to evaluate plant health. The NDVI and plant density results can be used to suggest where new plants can be added and to provide proper maintenance to achieve proper functions within the GSIs. This study provides a framework for evaluating plant performance within the GSIs using the collected UAV-based imagery.

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‘Green or short: choose one’ - A comparison of walking accessibility and greenery in 43 European cities

Willberg,

Fink,

Klein

et al. 2024

Computers, Environment and Urban Systems

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Synergy between green stormwater infrastructure and active mobility: A comprehensive literature review

Cited by 3 publications

References 87 publications

Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior

Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior

Plant Density and Health Evaluation in Green Stormwater Infrastructure Using Unmanned-Aerial-Vehicle-Based Imagery

‘Green or short: choose one’ - A comparison of walking accessibility and greenery in 43 European cities

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