详情

Rapid Exploitation of Commercial Remotely Sensed Imagery for Disaster Response & Recovery

项目名称：	Rapid Exploitation of Commercial Remotely Sensed Imagery for Disaster Response & Recovery
摘要：	Natural disasters can severely impact transportation networks. In the hours and days following a major flooding event, knowing the location and extent of the damage is crucial for incident managers for a number of reasons: it allows for emergency vehicle access to affected areas; it facilitates the efficient rerouting of traffic; it raises the quality and reduces the cost of repairs; and it allows repairs to be completed faster, in turn reducing the duration of costly detours. Commercial Remote Sensing (CRS) imagery is increasingly being used in disaster response and recovery, but the ability to acquire CRS data far surpasses the ability to extract actionable information from it. An automated approach to damage assessment is needed, but traditional automated image analysis techniques are inadequate for identifying or characterizing transportation infrastructure damage from high-resolution CRS imagery. Furthermore, new CRS technologies, such as Unmanned Aircraft Systems (UAS) provide a novel approach to gathering imagery during a crisis in which traditional satellite and aerial systems are either cost prohibitive, ineffective, or unresponsive. The proposed project has two objectives: 1) to develop, calibrate and deploy a decision support system capable of identifying road and bridge damage from high- resolution commercial satellite images and; b) to estimate the amount and type of fill material required for repairs using digital surface models derived from lightweight Unmanned Aerial Vehicles (UAS) programmed to fly over damage road segments. This approach would employ state-of-the-art, object-based image analysis techniques, cost-based image matching, and other advanced computing techniques. The project also propose to collaborate with state departments of transportation to develop a web-based interface to share information derived from CRS Imagery.
状态：	Completed
资金：	234063
资助组织：	Department of Transportation
项目负责人：	Singh, Caesar
执行机构：	University of Vermont, Burlington
开始时间：	20120901
预计完成日期：	20141231
实际结束时间：	20160728
主题领域：	Data and Information Technology；Environment；Highways