Watching Corn Grow: A Hedonic Study of the Iowa Landscape, april 2007

Landscape amenities can be scarce in places with large areas of open space. Intensely farmed areas with high levels of monocropping and livestock production are akin to developed open space areas and do not provide many services in terms of landscape amenities. Open space in the form of farmland is plentiful, but parks and their services are in short supply. This issue is of particular importance for public policy because it is closely linked to the impact of externalities caused by agricultural activities and to the indirect effects of land use dynamics. This study looks at the impact of landscape amenities on rural residential property values in five counties in North Central Iowa using a hedonic pricing model based on geographic information systems. The effect of cropland, pasture, forest, and developed land as land uses surrounding the property is considered, as well as the impact of proximity to recreational areas. The study also includes the effect of other disamenities, such as livestock facilities and quarries, which can be considered part of the developed open space and are a common feature of the Iowa landscape.

Diagnostic Tools for Identifying Sleepy Drivers in the Field, RB21-012, 2013

The overarching goal of this project was to identify and evaluate cognitive and behavioral indices that are sensitive to sleep deprivation and may help identify commercial motor vehicle drivers (CMV) who are at-risk for driving in a sleep deprived state and may prove useful in field tests administered by officers. To that end, we evaluated indices of driver physiognomy (e.g., yawning, droopy eyelids, etc.) and driver behavioral/cognitive state (e.g. distracted driving) and the sensitivity of these indices to objective measures of sleep deprivation. The measures of sleep deprivation were sampled on repeated occasions over a period of 3.5-months in each of 44 drivers diagnosed with Obstructive Sleep Apnea (OSA) and 22 controls (matched for gender, age within 5 years, education within 2 years, and county of residence for rural vs. urban driving). Comprehensive analyses showed that specific dimensions of driver physiognomy associated with sleepiness in previous research and face-valid composite scores of sleepiness did not: 1) distinguish participants with OSA from matched controls; 2) distinguish participants before and after PAP treatment including those who were compliant with their treatment; 3) predict levels of sleep deprivation acquired objectively from actigraphy watches, not even among those chronically sleep deprived. Those findings are consistent with large individual differences in driver physiognomy. In other words, when individuals were sleep deprived as confirmed by actigraphy watch output they did not show consistently reliable behavioral markers of being sleep deprived. This finding held whether each driver was compared to him/herself with adequate and inadequate sleep, and even among chronically sleep deprived drivers. The scientific evidence from this research study does not support the use of driver physiognomy as a valid measure of sleep deprivation or as a basis to judge whether a CMV driver is too fatigued to drive, as on the current Fatigued Driving Evaluation Checklist.. Fair and accurate determinations of CMV driver sleepiness in the field will likely require further research on alternative strategies that make use of a combination of information sources besides driver physiognomy, including work logs, actigraphy, in vehicle data recordings, GPS data on vehicle use, and performance tests.