Abstract
Tectonic and land surface processes deform and disturb infrastructure and urban environments. Several remote sensing techniques have been developed to measure and monitor these processes. Disasters also can damage or destroy infrastructure and urban environments and one disaster can cascade into subsequent disasters. This chapter discusses hazards and disasters affecting infrastructure. Applicable remote sensing methods and interfaces are described for accessing data and data products. The chapter then presents case studies that illustrate the use of the remote sensing data for various applications.
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Acknowledgements
The work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). The work has been supported by the following NASA programs: Earth Surface and Interior (ESI), Advance Information Systems Technology (AIST), Geodetic Imaging, and Advancing Collaborative Connections for Earth System Science (ACCESS). This work could not have been accomplished without the contributions of numerous other investigators. These include Co-Investigators Gregory Lyzenga, Jay Parker, John Rundle, Lisa Grant Ludwig, Jun Wang, Marlon Pierce, Michael Heflin, and Robert Granat. Work on the Mundo Mud Spring is led by David Lynch of Shannon and Wilson. Numerous interns have contributed to work described here including Lindsay LaBrecque and Nathan Pulver for the landslide work, and Juan Carlos Beltran for the subsidence study. Cathleen Jones assisted with processing and analysis of UAVSAR for constructing time series of subsidence. Postdoctoral fellow Chris Milliner led development of optical techniques for separating types of materials in debris flows.
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Donnellan, A. (2021). Remote Sensing of Deformation and Disturbance to Monitor and Assess Infrastructure in Urban Environments. In: Singhroy, V. (eds) Advances in Remote Sensing for Infrastructure Monitoring. Springer Remote Sensing/Photogrammetry. Springer, Cham. https://doi.org/10.1007/978-3-030-59109-0_6
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