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Title: Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

Abstract

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

Inventors:
; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1374438
Patent Number(s):
9,727,976
Application Number:
15/159,384
Assignee:
Sandia Corporation SNL-A
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Patent
Resource Relation:
Patent File Date: 2016 May 19
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 58 GEOSCIENCES

Citation Formats

Perkins, David Nikolaus, Brost, Randolph, and Ray, Lawrence P. Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data. United States: N. p., 2017. Web.
Perkins, David Nikolaus, Brost, Randolph, & Ray, Lawrence P. Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data. United States.
Perkins, David Nikolaus, Brost, Randolph, and Ray, Lawrence P. Tue . "Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data". United States. doi:. https://www.osti.gov/servlets/purl/1374438.
@article{osti_1374438,
title = {Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data},
author = {Perkins, David Nikolaus and Brost, Randolph and Ray, Lawrence P.},
abstractNote = {Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 08 00:00:00 EDT 2017},
month = {Tue Aug 08 00:00:00 EDT 2017}
}

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