Using geographic information system (GIS) technology to study the impacts of roads on Canadaâs national parks
Notice bibliographique
Résumé
At the national level, Parks Canada employs GIS to support reporting on the ecological integrity of the nation’s national parks, using road development as an indicator. GIS is a critical technology for addressing the spatial and temporal relationship between land use and conservation. Historical and contemporary digital road data were mapped in and surrounding Canada’s 39 National Parks and National Park Reserves. Internal park road density, park area and the ratio of alien to native species were employed as indices to the ecological integrity of the parks. Road density surrounding Canada’s national parks was correlated with other infrastructure, land use and human population to demonstrate that the former was a valid quantitative, spatially and temporally explicit index to the latter. External road density and land use, as well as landscape fragmentation and the measures of loss of park ecological integrity, increased spatially from north to south. External road density increased temporally from the 1950’s to the 1990’s but internal park road density increased in only a minority of parks. Historical and contemporary road data provide a readily available quantitative measure of the constraints to restoring and maintaining the ecological integrity of the national parks with predictive utility for tracking future trends in land use and fragmentation of the native ecosystem. At the field unit level, GIS technology is used as a tool to examine the ecological impacts of roads. The locations of wildlife-vehicle collisions on major highways in the Rocky Mountain Parks were examined to assess factors influencing the frequency of wildlife-vehicle collisions and identify various mitigation measures. On the high traffic volume, high speed, divided section of Highway 1 in Banff National Park various types of overpasses and underpasses are used in combination with fencing to link wildlife habitats and reduce road kill. On lower traffic volume highways it is difficult to justify the cost of this intensive mitigation. Other measures need to be examined. A highway safety study of existing and proposed wildlife warning sign locations along Highway 93 South in Kootenay National Park found that most of the existing highway wildlife warning signs were not located at high animal kill sites (which corresponded to where watershed valleys intersected the highway). The new locations for the highway animal warning signs correspond to accident clusters involving wildlife. Another lower traffic volume highway is Highway 16 in Jasper N.P. The GIS database was used to examine driver (photo log) images of kill sites. The analysis of wildlife kill sites along this route indicated that the physical characteristics of the highway and corridor were good predictors of kill sites. Common factors of high kill sites included good roadside habitat, water supply nearby and long wide straight stretches of road. GIS will be used at the project level for the next phase of twinning Highway 1 in Banff. GIS can produce project displays and base maps to either help conceptualize the project, explain it to the public, or provide base mapping or other data for study and/or planning purposes. GIS has proved to be an essential decision-support tool for integrating road project and ecological information to facilitate more environmentally sensitive management of roads in national parks.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».