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 proceedingConference contributionpeer-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 languageEnglish
Title of host publicationChemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX
EditorsJason A. Guicheteau, Chris R. Howle
PublisherSPIE
ISBN (Electronic)9781510626850
DOIs
StatePublished - 2019
Externally publishedYes
EventChemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019 - Baltimore, United States
Duration: Apr 15 2019Apr 17 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11010
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceChemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX 2019
Country/TerritoryUnited States
CityBaltimore
Period04/15/1904/17/19

Keywords

  • Classification
  • Hyperspectral imagery
  • Underground nuclear explosions
  • Unmanned aerial systems
  • Vegetation

Fingerprint

Dive into the research topics of 'Hyperspectral vegetation identification at a legacy underground nuclear explosion test site'. Together they form a unique fingerprint.

Cite this