Integrating Remote Sensing Data in Decision Support Systems for Transportation Asset Management

The objective of the research summarized in this manuscript is two-fold: to develop and make available a set of novel analysis tools, fully integrated in ArcGIS, that leverages the rich information provided by satellite-based remote sensing data to detect and characterize geohazards of interest to the transportation community; and to provide a modern web-based decision support system (DSS) in which these novel analysis products can be seamlessly integrated with existing datasets. Specifically, interferometric synthetic aperture radar (InSAR) and its derivatives are employed in this work. Each tool is designed to target a specific asset of interest to the transportation community: sinkhole detection, bridge differential settlement detection, slope stability assessment, and pavement distress evaluation. Furthermore, to allow interested parties to test the introduction of remote sensing data into their decision-making process without requiring the full integration with existing workflows, a modern web-based DSS is introduced. Thanks to the large coverage and the high update frequencies offered by satellite-based remote sensing data, datasets augmented with these new products can offer a near real-time overview of the network status and lead to better support in decisions about resources allocation, existing infrastructure monitoring, new infrastructure planning, and post-construction assessment.