Mobilité active et infrastructures vertes de gestion des eaux pluviales : états des connaissances et analyse des synergies potentielles
Bibliographic record
Abstract
RÉSUMÉ: «RÉSUMÉ: Alors que les villes se densifient, il est essentiel de repenser l’espace urbain afin de construire un milieu de vie agréable pour tous. Par exemple, les villes tentent de mettre en place des infrastructures vertes (IV) afin de revégétaliser les milieux urbains. Les IV peuvent être définies comme un réseau d’espaces verts comprenant notamment les arbres, parcs, toits verts, etc. Selon de récentes études, ces infrastructures pourraient fournir des bénéfices écologiques tels que la réduction des îlots de chaleur et l’amélioration de la qualité de l’air. De plus, un effort considérable est mis en place afin de maximiser les fonctions d’un même espace. Ainsi, un type d’IV est de plus en plus utilisé, soit les infrastructures vertes de gestion des eaux pluviales (IVGEP). Les IVGEP diffèrent des IV par leur fonction première qui vise à collecter les eaux de ruissellement. Ces infrastructures sont parfois mises en place en bordure de rue afin de collecter les eaux pluviales qui ruissellent sur la chaussée et les trottoirs. Les IVGEP permettent de diminuer les volumes et débits d’eau acheminés vers le réseau d’égout pluvial. La construction des IVGEP dans l’emprise routière modifie considérablement la configuration des rues. Par exemple, les noues végétalisées, qui s’apparentent à des fossés végétalisés peu profonds et larges, sont souvent installées en bordure de rue permettant l’isolement du trottoir. Les saillies drainantes sont quant à elles souvent installées aux intersections des rues de façon similaire aux saillies de trottoir qui permettent de réduire la largeur de la rue à traverser pour les piétons. Ces aménagements diffèrent des IV standard comme les arbres de rue ou les bandes de gazon notamment de par leur profondeur, la présence d’une diversité de végétaux et leur empreinte dans le cadre bâti. Afin de mieux concevoir les IVGEP pour maximiser leurs bénéfices secondaires, il est nécessaire d’étudier leurs effets sur la mobilité active. Concevoir les IVGEP en tenant compte des besoins en termes d’infrastructures de transport actif contribue à maximiser les fonctions de l’espace public.» ABSTRACT: «ABSTRACT: As cities become denser, it is essential to rethink the urban space to create a pleasant living environment for everyone. For instance, cities are implementing green infrastructure (GI) to increase the density of vegetation in urban areas. According to some authors, GI consists of a network of green spaces including trees, parks, green roofs, etc. It can provide ecological benefits such as reducing heat islands and improving air quality. Moreover, significant efforts are being made to maximize the functions of public space. Thus, one type of GI increasingly used is green stormwater infrastructure (GSI). GSI differs from traditional GI in its primary function, which aims to collect stormwater runoff. This type of infrastructure is often implemented along streets to collect runoff from roadways and sidewalks. GSI helps reduce the volume and flow of water directed to the storm sewer system. The implementation of GSI within the right-of-way significantly changes the street configuration. For instance, bioswales, which resemble shallow and wide vegetated ditches, are often installed along the roadside, allowing to isolate the sidewalks. Stormwater curb extensions are also frequently installed at street intersections, providing similar benefits as curb extensions that reduce the street crossing width for pedestrians. These vegetation features differ from standard GI features such as street trees or grass strips, mainly due to their depth, the presence of diverse vegetation, and their footprint within the built environment. To better design GSI and maximize their secondary benefits, studying their impact on active mobility is essential. Designing GSI while considering the needs for active transportation infrastructure contributes to enhancing the functions of the public space. »
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".