Addressing Deer Vehicle Accidents
1 / 33

Addressing Deer Vehicle Accidents at the Community Scale - PowerPoint PPT Presentation

  • Uploaded on

Addressing Deer Vehicle Accidents at the Community Scale. Elizabeth I. Rogers, Ph.D. Dean B. Premo, Ph.D. White Water Associates, Inc. Amasa, MI. Creating a Town Deer-Vehicle Accident Management Plan. Project Goals.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Addressing Deer Vehicle Accidents at the Community Scale' - LeeJohn

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Slide1 l.jpg

Addressing Deer Vehicle Accidents

at the Community Scale

Elizabeth I. Rogers, Ph.D.

Dean B. Premo, Ph.D.

White Water Associates, Inc.

Amasa, MI

Project goals l.jpg
Project Goals

  • Use the existing GIS project to understand deer-vehicle accident patterns

  • Create a deer-vehicle accident management plan

  • Assess data collection and monitoring needs for the future

The starting point town gis project l.jpg
The starting point: Town GIS Project

  • Town of Amherst, (roads, boundary)

  • Land Use Layer (urban, suburban, and rural land uses)

  • Deer-Vehicle Accident Management Zones

Town of amherst ny land uses l.jpg
Town of Amherst, NY, Land Uses

The town has abundant open space that provides habitat for deer.

Multi year record of dva s l.jpg
Multi-year record of DVA’s

  • DVAs 1991-2000

  • Total: 3295 DVAs

  • Raw data difficult (or impossible) to assess visually.

Deer population counts l.jpg
Deer Population Counts

  • Aerial late winter counts by natural resource agency using visual polygons

  • Displayed here as densities (standardized to area)

Population counts by year l.jpg
Population Counts by Year

  • Highest population in 1994 before lethal control took effect [statistically significant]

  • 625 deer killed by bait and shoot and nuisance permits (1994-1996)

  • 2001 count higher than 1998 [statistically significant]

Population densities by management zone l.jpg
Population Densities by Management Zone

Before, During, and After Lethal Control




When do most collisions occur l.jpg
When do most collisions occur?

  • Time of Day?

  • Month?

Dvas by time of day l.jpg
DVAs by Time of Day

  • Most accidents occur in evening and night

Dvas by month l.jpg
DVAs by Month

  • Highest number of collisions occur in the fall and early winter

Nearly 1/2 of all collisions occur in the fall

Where do most collisions occur l.jpg
Where do most collisions occur?

  • In which parts of town?

  • In relation to what features and land uses?

Density of dva s by management zone l.jpg
Density of DVA’s by Management Zone

More accidents in the rural parts of town where development and ample open space are intermixed.

Dva density correlations l.jpg

Open land

Deer population

45 mph roads


Single residences

35 mph roads

Road density

DVA Density Correlations

Examined by Management Zone


Dva density within 1 4 mile of parks l.jpg
DVA Density within 1/4 Mile of Parks

To deer, all parks are not equal.

Even some small parks have a high density of DVAs nearby

Dva hot spots 1991 2000 l.jpg
DVA “Hot Spots” 1991-2000

Calculated DVAs/square mile (using density function in ArcView Spatial Analyst®)

Most accidents concentrate where development and open space interface.

Hot spots and land uses l.jpg
“Hot Spots” and Land Uses

  • Parks and open space may influence movement patterns

  • High traffic volume also plays potential role.

  • New development appears to exacerbate the problem

Detailed view of hot spot l.jpg
Detailed View of “Hot Spot”

A mixture of land uses typifies most “hot spots.”

Typical hot spot land uses l.jpg
Typical “Hot Spot” Land Uses

A mixture of land uses with about 50% open land and most of the rest developed

Typical non hot spot land uses l.jpg
Typical Non - “Hot Spot” Land Uses

Areas without “hot spots” differ in land uses

They are dominated by development or by open land




Urban hot spot l.jpg
Urban “Hot Spot”

  • Combination of:

  • Deer Habitat (green space, office parks, and vacant land)

  • New development (displacing deer)

  • High people density

Dva management plan l.jpg
DVA Management Plan



Whole Town

“Hot Spot”


Influence Human Behavior

Influence Deer Behavior

Affect Deer Population

Support management actions with data l.jpg
Support Management Actions with Data

Use data to...

  • Avoid lawsuits

  • Support environmental assessments

  • Inform adaptive management plans

Whole town focus l.jpg
Whole Town Focus

  • Public education (press releases, pamphlets, posters)

  • Drivers’ education

  • Enforce or enact “no deer feeding” laws

  • Encourage use of nuisance permits

  • If needed, enact professional lethal control

Hot spot focus l.jpg
“Hot Spot” Focus

  • Deploy seasonal warning signs

  • Facilitate press and media coverage of sign deployment and “hot spots”

  • Enforce speed limits in areas of “hot spots”

  • Fence and/or improve roadside visibility with brushing at selected corridor “hot spots”

Hot spot warning sign l.jpg
“Hot Spot” Warning Sign

  • Novel sign

  • Seasonally deployed during high crash period

  • Deploy at selected “hot spots”

Sign from Kent County, MI

Challenges in assessing results l.jpg
Challenges in Assessing Results

  • Small sample sizes

  • Lack of independence

  • Variability in deployment sites

Difficulty in conducting statistical tests has been a perpetual problem in testing of warning reflectors

Information wish list l.jpg
Information Wish List

  • DVA database for theme Georeferenced Driver data (age, gender) Time (24 hours, date)

  • Road (type, speed limit)

  • Land use (including potential deer habitat)

  • Development locations

  • Natural features (streams, lakes, hills)

  • Deer population counts or estimates

Monitoring suggestions l.jpg
Monitoring Suggestions

  • Need ongoing multi-year data on deer populations and DVAs

  • Summarize changes in patterns with GIS spatial analysis

  • Visually examine changes in locations and intensities of “hot spots”

  • Statistically test for significant changes in DVA and population numbers when possible

  • Monitor health of vegetation in parks

Ultimate goal l.jpg
Ultimate Goal

To coexist with deer