Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response

F. A. Kruse; A. M. Kim; S. C. Runyon; Sarah C. Carlisle; C. C. Clasen; C. H. Esterline; A. Jalobeanu; J. P. Metcalf; P. L. Basgall; D. M. Trask; R. C. Olsen

doi:10.1117/12.2049725

13 June 2014 Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response

F. A. Kruse, A. M. Kim, S. C. Runyon, Sarah C. Carlisle, C. C. Clasen, C. H. Esterline, A. Jalobeanu, J. P. Metcalf, P. L. Basgall, D. M. Trask, R. C. Olsen

Author Affiliations +

Proceedings Volume 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX; 90880K (2014) https://doi.org/10.1117/12.2049725
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

The Naval Postgraduate School (NPS) Remote Sensing Center (RSC) and research partners have completed a remote sensing pilot project in support of California post-earthquake-event emergency response. The project goals were to dovetail emergency management requirements with remote sensing capabilities to develop prototype map products for improved earthquake response. NPS coordinated with emergency management services and first responders to compile information about essential elements of information (EEI) requirements. A wide variety of remote sensing datasets including multispectral imagery (MSI), hyperspectral imagery (HSI), and LiDAR were assembled by NPS for the purpose of building imagery baseline data; and to demonstrate the use of remote sensing to derive ground surface information for use in planning, conducting, and monitoring post-earthquake emergency response. Worldview-2 data were converted to reflectance, orthorectified, and mosaicked for most of Monterey County; CA. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired at two spatial resolutions were atmospherically corrected and analyzed in conjunction with the MSI data. LiDAR data at point densities from 1.4 pts/m² to over 40 points/ m² were analyzed to determine digital surface models. The multimodal data were then used to develop change detection approaches and products and other supporting information. Analysis results from these data along with other geographic information were used to identify and generate multi-tiered products tied to the level of post-event communications infrastructure (internet access + cell, cell only, no internet/cell). Technology transfer of these capabilities to local and state emergency response organizations gives emergency responders new tools in support of post-disaster operational scenarios.

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F. A. Kruse, A. M. Kim, S. C. Runyon, Sarah C. Carlisle, C. C. Clasen, C. H. Esterline, A. Jalobeanu, J. P. Metcalf, P. L. Basgall, D. M. Trask, and R. C. Olsen "Multispectral, hyperspectral, and LiDAR remote sensing and geographic information fusion for improved earthquake response", Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, 90880K (13 June 2014); https://doi.org/10.1117/12.2049725

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