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:
- Issue Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1374438
- Patent Number(s):
- 9727976
- Application Number:
- 15/159,384
- Assignee:
- Sandia Corporation
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
- 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. 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 = {2017},
month = {8}
}
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