Multi-criteria evaluation (MCE) provides a way to integrate different spatial data layers in a geographic information system to create composite maps representing risk. We utilized MCE in a raster GIS to evaluate risk along several paved road segments on the Hopi Reservation in Arizona. In our MCE tests we included risk factors such as proximity to intersections, steepness of slope, proximity to washes, and road curvature. A set of 44 composite risk maps was created using fuzzy sets and variable factor weightings in our analyses. These maps were compared to crash locations (n = 67) obtained through field-based interviews with Emergency Medical Personnel on the Reservation. Statistically significant differences between MCE scores for crash sites and non-crash sites were found in eight of eleven tests involving normally distributed data. We found that the MCE tests tended to produce significant results when more weight was attributed to proximity to intersections and road curvature. These results suggest that these particular factors are the most important in determining risk on paved roads. The results may be generalized more broadly in the region to identify important stretches of roadway where hazard mitigation may be needed.
- Multi-criteria evaluation
- Native American lands
- Rural road safety
ASJC Scopus subject areas
- Geography, Planning and Development
- Environmental Science(all)
- Tourism, Leisure and Hospitality Management