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Title: Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy’s Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models were created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within ~40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90–130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. Thismore » provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.« less
Authors:
 [1] ;  [2] ;  [1] ;  [1] ;  [3]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Coppersmith Consulting Inc., Walnut Creek, CA (United States)
  3. Gresham Smith and Partners, Nashville, TN (United States)
Publication Date:
Report Number(s):
LA-UR-16-29246
Journal ID: ISSN 0033-4553
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Pure and Applied Geophysics
Additional Journal Information:
Journal Name: Pure and Applied Geophysics; Journal ID: ISSN 0033-4553
Publisher:
Springer
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Photogrammetry; unmanned aerial systems; change detection; underground explosions
OSTI Identifier:
1396118

Schultz-Fellenz, Emily S., Coppersmith, Ryan T., Sussman, Aviva J., Swanson, Erika M., and Cooley, James A.. Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry. United States: N. p., Web. doi:10.1007/s00024-017-1649-0.
Schultz-Fellenz, Emily S., Coppersmith, Ryan T., Sussman, Aviva J., Swanson, Erika M., & Cooley, James A.. Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry. United States. doi:10.1007/s00024-017-1649-0.
Schultz-Fellenz, Emily S., Coppersmith, Ryan T., Sussman, Aviva J., Swanson, Erika M., and Cooley, James A.. 2017. "Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry". United States. doi:10.1007/s00024-017-1649-0. https://www.osti.gov/servlets/purl/1396118.
@article{osti_1396118,
title = {Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry},
author = {Schultz-Fellenz, Emily S. and Coppersmith, Ryan T. and Sussman, Aviva J. and Swanson, Erika M. and Cooley, James A.},
abstractNote = {Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy’s Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models were created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within ~40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90–130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. This provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.},
doi = {10.1007/s00024-017-1649-0},
journal = {Pure and Applied Geophysics},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}