Objective: The annual rate of impaired driving crashes in the United States has remained nearly constant over the last decade. While engineers, educators, enforcement, and emergency response personnel have worked diligently in their combined efforts to reduce the loss of life, there is still significant progress to be made. One area of recent interest is the use of data driven enforcement. The basis for data driven enforcement is the use of statistical clustering to identify geographic areas that represent the location of problem identification for various criminal or traffic offenses. In the case of impaired driving fatalities, the clustering represents locations with high rates of impaired driving crashes. Law enforcement officers and supervisors may allocate resources towards more specifically and efficiently addressing problem areas.
Methods: While data driven enforcement has been proven to be an effective tool in addressing crime and traffic safety problems, it has been a slow process for agencies to adopt data driven techniques. This study aims to explore the difference in traffic stops made inside and outside of hotspot identified areas. The study uses data from the Stark County Operating a Vehicle Impaired Task Force between 2013 and 2014.
Results: The analysis determined that stop occurring in hotspot defined areas are more likely to result in impaired driving arrests and seatbelt citations. Additionally it is found that the average cost of impaired driving arrests is significantly cheaper for stops occurring inside of hotspot areas.
Conclusion: Clustering as a means of directing law enforcement efforts are a way to increase the productivity and benefits of law enforcement agencies with limited finances or personnel. From this study it is seen that traffic stops made within defined cluster or hot spot areas are more effective in resulting in OVI arrests. 相似文献
Wild salmon stocks in the Pacific Northwest are imperiled by a variety of declining habitat factors, including riparian shade and in-channel large wood. In this paper, a relatively simple lidar model of the riparian canopy was used along anadromous streams in the Skagit River watershed in western Washington State, United States, to delineate where riparian trees were most lacking, and where restoration efforts would have the greatest benefit in terms of shade and large wood recruitment potential. Within a 45-m riparian buffer, 61% of riparian zones were currently incapable of delivering large wood to the stream. Current potential for large wood recruitment is greatest adjacent to stream edges and falls off rapidly with distance from the channel. Approximately 99% of large wood recruitment potential lies within 45 m of the channel edge, and 50% of the wood potential is within 9 m. A hypothetical canopy model in which all trees mature to a 100-year height would provide 18% more shade distributed over the entire watershed, and 90% more shade in the tributaries. Most of the potential gains in improved shade and large wood contributions are in agricultural areas, as opposed to forestry or urban land uses. The shade and large wood models were constructed from widely available geographic information system tools and are readily transferable to other watersheds with similar characteristics. Model outputs are intended for use in planning restoration projects, as an input to stream temperature models, and to inform policy on restoration priorities and regulatory buffer widths. 相似文献
Managers need measurements and resource managers need the length/width of a variety of items including that of animals, logs,
streams, plant canopies, man-made objects, riparian habitat, vegetation patches and other things important in resource monitoring
and land inspection. These types of measurements can now be easily and accurately obtained from very large scale aerial (VLSA)
imagery having spatial resolutions as fine as 1 millimeter per pixel by using the three new software programs described here.
VLSA images have small fields of view and are used for intermittent sampling across extensive landscapes. Pixel-coverage among
images is influenced by small changes in airplane altitude above ground level (AGL) and orientation relative to the ground,
as well as by changes in topography. These factors affect the object-to-camera distance used for image-resolution calculations.
‘ImageMeasurement’ offers a user-friendly interface for accounting for pixel-coverage variation among images by utilizing
a database. ‘LaserLOG’ records and displays airplane altitude AGL measured from a high frequency laser rangefinder, and displays
the vertical velocity. ‘Merge’ sorts through large amounts of data generated by LaserLOG and matches precise airplane altitudes
with camera trigger times for input to the ImageMeasurement database. We discuss application of these tools, including error
estimates. We found measurements from aerial images (collection resolution: 5–26 mm/pixel as projected on the ground) using
ImageMeasurement, LaserLOG, and Merge, were accurate to centimeters with an error less than 10%. We recommend these software packages as a means for expanding
the utility of aerial image data. 相似文献