Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

Brian J. Redman; John D. Van Der Laan; Dylan Z. Anderson; Julia M. Craven; Elizabeth D. Miller; Adam D. Collins; Erika M. Swanson; Emily S. Schultz-Fellenz

doi:10.1117/12.2519957

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

Brian J. Redman
, John D. Van Der Laan
, Dylan Z. Anderson
, Julia M. Craven
, Elizabeth D. Miller
, Adam D. Collins
, Erika M. Swanson
, Emily S. Schultz-Fellenz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km² of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. We employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We find a difference in species abundance within a 130 m radius of the center of the test site.

Original language	English
Title of host publication	Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX
Editors	Jason A. Guicheteau, Chris R. Howle
Publisher	SPIE
ISBN (Electronic)	9781510626850
DOIs	https://doi.org/10.1117/12.2519957
State	Published - 2019
Externally published	Yes
Event	Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019 - Baltimore, United States Duration: Apr 15 2019 → Apr 17 2019

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11010
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019
Country/Territory	United States
City	Baltimore
Period	04/15/19 → 04/17/19

Funding

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The authors would like to thank the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development, for sponsoring this work. We would also like to thank the Underground Nuclear Explosion Signatures Experiment team, a multi-institutional and interdisciplinary group of scientists and engineers, for its technical contributions and support at the NNSS.

Keywords

Classification
Hyperspectral imagery
Underground nuclear explosions
Unmanned aerial systems
Vegetation

Access to Document

10.1117/12.2519957

Cite this

Redman, B. J., Van Der Laan, J. D., Anderson, D. Z., Craven, J. M., Miller, E. D., Collins, A. D., Swanson, E. M., & Schultz-Fellenz, E. S. (2019). Hyperspectral vegetation identification at a legacy underground nuclear explosion test site. In J. A. Guicheteau, & C. R. Howle (Eds.), Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX Article 110100R (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11010). SPIE. https://doi.org/10.1117/12.2519957

Redman, Brian J. ; Van Der Laan, John D. ; Anderson, Dylan Z. et al. / Hyperspectral vegetation identification at a legacy underground nuclear explosion test site. Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX. editor / Jason A. Guicheteau ; Chris R. Howle. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).

@inproceedings{fa6eb2f526f24cefaf43a837a8fccc5d,

title = "Hyperspectral vegetation identification at a legacy underground nuclear explosion test site",

abstract = "The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. We employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We find a difference in species abundance within a 130 m radius of the center of the test site.",

keywords = "Classification, Hyperspectral imagery, Underground nuclear explosions, Unmanned aerial systems, Vegetation",

author = "Redman, \{Brian J.\} and \{Van Der Laan\}, \{John D.\} and Anderson, \{Dylan Z.\} and Craven, \{Julia M.\} and Miller, \{Elizabeth D.\} and Collins, \{Adam D.\} and Swanson, \{Erika M.\} and Schultz-Fellenz, \{Emily S.\}",

note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019 ; Conference date: 15-04-2019 Through 17-04-2019",

year = "2019",

doi = "10.1117/12.2519957",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Guicheteau, \{Jason A.\} and Howle, \{Chris R.\}",

booktitle = "Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX",

}

Redman, BJ, Van Der Laan, JD, Anderson, DZ, Craven, JM, Miller, ED, Collins, AD, Swanson, EM & Schultz-Fellenz, ES 2019, Hyperspectral vegetation identification at a legacy underground nuclear explosion test site. in JA Guicheteau & CR Howle (eds), Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX., 110100R, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11010, SPIE, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019, Baltimore, United States, 04/15/19. https://doi.org/10.1117/12.2519957

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site. / Redman, Brian J.; Van Der Laan, John D.; Anderson, Dylan Z. et al.
Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX. ed. / Jason A. Guicheteau; Chris R. Howle. SPIE, 2019. 110100R (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

AU - Redman, Brian J.

AU - Van Der Laan, John D.

AU - Anderson, Dylan Z.

AU - Craven, Julia M.

AU - Miller, Elizabeth D.

AU - Collins, Adam D.

AU - Swanson, Erika M.

AU - Schultz-Fellenz, Emily S.

PY - 2019

Y1 - 2019

N2 - The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. We employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We find a difference in species abundance within a 130 m radius of the center of the test site.

AB - The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. We employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We find a difference in species abundance within a 130 m radius of the center of the test site.

KW - Classification

KW - Hyperspectral imagery

KW - Underground nuclear explosions

KW - Unmanned aerial systems

KW - Vegetation

UR - https://www.scopus.com/pages/publications/85072386836

U2 - 10.1117/12.2519957

DO - 10.1117/12.2519957

M3 - Conference contribution

AN - SCOPUS:85072386836

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX

A2 - Guicheteau, Jason A.

A2 - Howle, Chris R.

PB - SPIE

T2 - Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019

Y2 - 15 April 2019 through 17 April 2019

ER -

Redman BJ, Van Der Laan JD, Anderson DZ, Craven JM, Miller ED, Collins AD et al. Hyperspectral vegetation identification at a legacy underground nuclear explosion test site. In Guicheteau JA, Howle CR, editors, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX. SPIE. 2019. 110100R. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2519957

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

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