Site and landscape conditions at white-tailed deer/vehicle collisionlocations in Illinois

Autor: Finder, R. A., Woolf, A., Roseberry, J. L.
Předmět:
Zdroj: Landscape & Urban Planning; 5/10/1999, Vol. 44 Issue 2/3, p77, 0p
Abstrakt: Motor vehicle collisions with white-tailed deer (Odocoileus virginianus) present several problems including danger to humans, vehicle damage, and deer mortality. Knowledge of factors influencing deer movements onto or across roads and highways may reduce deer/vehicle collisions on existing roads, and improve planning for future roads. We usedremotely sensed data to determine characteristics associated with high accident areas. Topographic features and highway construction variables considered conducive to deer/vehicle accidents were measured around high accident road segments (greater than or equal to 15 accidents from 1989-1993) and randomly selected control sites. Variables were measured on aerial photographs and topographic maps within a 0.8km radius of the road segments. Landscape composition and spatial structure were quantified with the computer program , using a statewide land cover classification derived from Landsat V TM satellite imagery. Alogistic regression model composed of site variables predicted that greater distance to forest cover decreased the probability of a road segment being a high deer/vehicle accident site. The presence of adjacent gullies, riparian travel corridors crossing the road, and publicrecreational land within the 0.8km radius increased this probability. A model using only landscape metrics derived from satellite imagerypredicted that greater landscape diversity and shorter distances between nearby forest patches increased the probability of a road segment being a high deer/vehicle accident site. Both models discriminated between high and low deer kill sites. Therefore, proactive managementof negative deer/human interactions may be accomplished through remote sensing and geographical information systems. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index