摘要: |
The hazard to infrastructure systems that results from wildfires includes (1) the initial hazard/damage associated with the wildfire and (2) secondary effects that result from the wildfire denuding the soil. In an effort to characterize the risk associated with the potential mudflows or rockslides that occur as a result of wildfires, transportation professionals typically rely upon the use of existing data (burn severity maps, soil maps, geologic maps, topographic maps). The high spatial and temporal resolution of remote sensing data may aid in characterizing the risk to transportation infrastructure that results from wildfires. The research associated with this proposal will evaluate the applicability of ground-based optical, thermal, RADAR, and Light Detection and Ranging (LIDAR) technologies to obtain specific parameters of interest to characterize the risk of mudflows or rockslides at a specific site. Furthermore, these parameters will be used in a remote sensing based decision support system (RSBDSS) for assessing the post-wildfire mudflow or rockslide hazards to roadways. A probabilistic model, contained within a RSBDSS, will help to quantify the future probability of a mudflow or rockslide for a given site. This RBDSS is anticipated to: (1) aid highway managers in determining the risk to the transportation infrastructure; (2) develop plans for required route closures; and (3) ensure safety of the transportation users. |