Comparison of Data Sets Varying in Spatial Accuracy Used to Predict the Occurrence of Wildlife-Vehicle Collisions

Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the...

Full description

Saved in:
Bibliographic Details
Published in:Environmental management (New York) 2009-08, Vol.44 (2), p.268-277
Main Authors: Gunson, Kari E, Clevenger, Anthony P, Ford, Adam T, Bissonette, John A, Hardy, Amanda
Format: Article
Language:English
Subjects:
Accuracy
Animals
Animals, Wild
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Canada
Collisions
Comparative analysis
Data acquisition
Data collection
Databases, Factual - standards
Datasets
Earth and Environmental Science
Ecology
Environment
Environmental Management
Environmental Monitoring
Forestry Management
Geographic information systems
Geography
Global positioning systems
GPS
Humans
Models, Theoretical
Motor Vehicles
Mountains
Nature Conservation
Performance evaluation
Predictions
Remote sensing
Roads
Roads & highways
Safety
Studies
Transportation planning
Variables
Waste Water Technology
Water Management
Water Pollution Control
Wildlife
Wildlife habitats
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the quality of WVC data collection. Two common approaches to describe the location of WVCs are spatially accurate data derived from global positioning systems (GPS) or vehicle odometer measurements and less accurate road-marker data derived from reference points (e.g., mile-markers or landmarks) along the roadside. In addition, there are two common variable types used to predict WVC locations: (1) field-derived, site-specific measurements and (2) geographic information system (GIS)-derived information. It is unclear whether these different approaches produce similar results when attempting to identify and explain the location of WVCs. Our first objective was to determine and compare the spatial error found in road-marker data (in our case the closest mile-marker) and landmark-referenced data. Our second objective was to evaluate the performance of models explaining high- and low-probability WVC locations, using congruent, spatially accurate (
ISSN:0364-152X
1432-1009
DOI:10.1007/s00267-009-9303-y