干旱区生态环境知识资源中心(Arid): Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

Arid

DOI	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.; Craven, Julia M.; Miller, Elizabeth D.; Collins, Adam D.; Swanson, Erika M.; Schultz-Fellenz, Emily S.
通讯作者	Redman, BJ (corresponding author), Sandia Natl Labs, 1515 Eubank Blvd SE, Albuquerque, NM 87123 USA.
会议名称	20th Conference on Chemical Biological, Radiological, Nuclear and Explosives (CBRNE) Sensing held at SPIE Defense + Commercial Sensing Conference
会议日期	APR 15-17, 2019
会议地点	Baltimore, MD
英文摘要	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 km(2) 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.
英文关键词	hyperspectral imagery underground nuclear explosions unmanned aerial systems vegetation classification
来源出版物	CHEMICAL, BIOLOGICAL, RADIOLOGICAL, NUCLEAR, AND EXPLOSIVES (CBRNE) SENSING XX
ISSN	0277-786X
EISSN	1996-756X
出版年	2019
卷号	11010
ISBN	978-1-5106-2686-7
出版者	SPIE-INT SOC OPTICAL ENGINEERING
类型	Proceedings Paper
语种	英语
开放获取类型	Green Submitted
收录类别	CPCI-S
WOS记录号	WOS:000502066600022
WOS关键词	CLASSIFICATION ; IMAGES ; UAV
WOS类目	Chemistry, Applied ; Remote Sensing ; Optics ; Spectroscopy
WOS研究方向	Chemistry ; Remote Sensing ; Optics ; Spectroscopy
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/370162
作者单位	[Redman, Brian J.; van der Laan, John D.; Anderson, Dylan Z.; Craven, Julia M.] Sandia Natl Labs, 1515 Eubank Blvd SE, Albuquerque, NM 87123 USA; [Miller, Elizabeth D.; Collins, Adam D.; Swanson, Erika M.; Schultz-Fellenz, Emily S.] Los Alamos Natl Lab, POB 1663, Los Alamos, NM 87545 USA
推荐引用方式 GB/T 7714	Redman, Brian J.,van der Laan, John D.,Anderson, Dylan Z.,et al. Hyperspectral vegetation identification at a legacy underground nuclear explosion test site[C]:SPIE-INT SOC OPTICAL ENGINEERING,2019.