Using Social Networks and Commercial Remote Sensing to Assess Impacts of Natural Events on Transportation Infrastructure

Waters, Nigel; Cervone, Guido

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Using Social Networks and Commercial Remote Sensing to Assess Impacts of Natural Events on Transportation Infrastructure

2015-04-01
By Waters, Nigel ; Cervone, Guido

File Language:

English

Details

Creators:

Waters, Nigel ; Cervone, Guido
Corporate Creators:

George Mason University ; The Carbon Project
Contributors:

Singh, Caesar ; Schnebele, Emily ; Harrison, Jeff ; Mattson, Mark
Corporate Contributors:

National Center for Geographic Information & Analysis (U.S.) ; United States. Department of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:
Publication/ Report Number:

RITARS-12-H-GMU
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Contracting Officer:

Caesar Singh
Corporate Publisher:

United States. Dept. of Transportation. Research and Innovative Technology Administration
Abstract:

This project develops a new capability to use social networks for cueing commercial remote sensing of transportation infrastructure conditions, in response to natural events. To meet these challenges, this project will develop and deliver a capability to access real-time social networks and then convert information into interoperable geospatial services. These services can be used to 'scan' for geosocial inputs to natural event impacts on transportation infrastructure, and improve the speed and accuracy of commercial imagery satellite collection of transportation infrastructure impacts. Once cueing data is available, commercial high-resolution imaging satellites will use the information to task collection over potentially affected transportation infrastructure.
Content Notes:

Publication date estimated from PDF Document Properties.
Format:

PDF
Funding:

CFD
Download URL:

https://rosap.ntl.bts.gov/view/dot/60452/dot_60452_DS1.pdf
File Type:

[PDF - 2.33 MB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:27d2b5edd78be7b1f3dd9220d4c87e7fdb001bc08e2bff03bf50f8af353a1792

File Language:

English

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