[Esip-disasters] Fwd: [agu-essi] CFP- IJDE Special Issue on Social Sensing and Big Data Computing for Disaster Management

Wed Sep 13 13:51:25 EDT 2017

Hi All -

Attached is a call for papers social sensing and big data computing for
disaster management.

Thanks-
Erin
---------- Forwarded message ----------
From: LI, ZHENLONG <ZHENLONG at mailbox.sc.edu>
Date: Tue, Sep 12, 2017 at 12:45 PM
Subject: [agu-essi] CFP- IJDE Special Issue on Social Sensing and Big Data
Computing for Disaster Management
To: "AGU-ESSI at googlegroups.com" <AGU-ESSI at googlegroups.com>

*Open Call for Submissions*

Special Issue on *"**Social Sensing and Big Data Computing for Disaster
Management" in **International Journal of Digital Earth(IJDE)*

http://explore.tandfonline.com/cfp/est/ijde/si-5

*Guest Editors*

Zhenlong Li, Department of Geography, University of South Carolina, SC
29208, USA zhenlong at sc.edu

Qunying Huang, Department of Geography, University of Wisconsin-Madison, WI
53706, USA qhuang46 at wisc.edu

Christopher Emrich, School of Public Administration, University of Central
Florida, FL 32816, USA christopher.emrich at ucf.edu

*Submission Deadline: March 1st, 2018*

*Aims and Scope*

Rapid onset disasters, often difficult to prepare for and respond to, make
disaster management a challenging task worldwide. Disaster and emergency
management effectiveness depends heavily on making good decisions in
near-real time under extreme duress.  These key, often life-saving,
decisions are possible only with real-time data sources and the ability to
timely collect, process, synthesize, and analyze these multi-sourced data.
Traditional data collection practices such as remote sensing and field
surveying often fail to offer timely information during or immediately
following damaging events. For example, stream gauges are only useful for
flood mapping while the stations are functioning properly and before they
are overtopped by floodwaters and rendered inoperable.

Fortunately, sharing information such as texts, images, and videos through
social media platforms enables all citizens to become part of a large
sensor network and a homegrown disaster response team. Compared to
traditional physical sensors, such a citizen-sensor network (social
sensing) is low cost, more comprehensive, and always broadcasting
situational awareness information. Social sensing enables wide-scale
interaction where primary data becomes collectively resourceful,
self-policing, and generates information that is otherwise hard to obtain
in a useful timeframe for disaster areas. For example, with social sensing,
massive amounts of micro-level disaster information (e.g. site specific
damage) can be captured in real-time through social media platforms (e.g.
Twitter, Facebook) and voluntarily reported via dedicated crowdsourcing
applications (volunteered geographic information, VGI), enabling rapid
assessment of evolving disaster situations.

On the other hand, data collected with social sensing is often massive,
heterogeneous, noisy, unreliable, and comes in continuous streams.  This is
inherent “Big Data”, for example, millions of microblog posts from
different social media platforms can be generated in a short time right
after an impactful disaster. Hence, Big Data computing methods and
technologies such as cloud computing, distributed geo-information
processing, spatial statistics/modeling, data mining, spatial database, and
multi-source data fusion become critical components of using social sensing
to understand the impact of and response to the disaster events in a timely
fashion.

Along these lines, this special issue on “Social Sensing and Big Data
Computing for Disaster Management” by the* International Journal of Digital
Earth *aims to capture recent advancements in leveraging social sensing and
big data computing for supporting disaster management in one or more
disaster phases (mitigation, preparedness, response, and recovery).
Specifically, we solicit original unpublished research articles that can
shed light on the opportunities, challenges, and solutions of leveraging
social sensing and big data computing for supporting disaster management.

Potential topics include (but are not limited to) the following:

1.     Innovative approaches to synthesize multi-sourced social sensing
data and/or traditional data (e.g. remote sensing) for disaster management

2.     Analyzing and visualizing human movement patterns before, during,
and after disaster events

3.     Disaster event detection, early warning, and impact/damage
assessment with social sensing

4.     Mining and extracting actionable information for rapid emergency
response and relief coordination

5.     Geovisual analytics of social sensing data during a disaster

6.     Integrating data mining (machines) and crowdsourcing (human) to
support decision-making

7.     New tools and solutions for real-time big social sensing data
collecting, processing, analyzing, and visualizing

8.     Exploring public perception, sentiments, and understanding towards
disaster events

9.     Novel social engagement approaches to effectively link the public in
an organized way toward contributing to emergency response, recovery

10.  Data quality, reliability, and privacy issues of social sensing for
disaster management

11.  Leveraging big social sensing data to enhance social resilience

*Important Dates*

November 15, 2017, 800-word abstract submission to guest editors

December 1, 2017, full paper submission invited

March 1, 2018, full paper submission online

May 1, 2018, revision/rejection notification

August 1, 2018, paper acceptance notification

*Submission Guidelines*

The *International Journal of Digital Earth* is an international
peer-reviewed academic journal (SCI-E with a 2016 impact factor 2.292)
focusing on the theories, technologies, applications, and societal
implications of Digital Earth and those visionary concepts that will enable
a modeled virtual world.

Submissions must follow the instructions to authors outlined on the Taylor
& Francis web page for the International Journal of Digital Earth found:
here
<http://www.tandfonline.com/action/authorSubmission?journalCode=tjde&page=instructions#.VyAehTFKLHI>.
Word templates are available on the web site and papers are typically 5000‐8000
words in length.

Papers should be submitted online at the International Journal of Digital
Earth's Manuscript Central Site: here
<https://mc.manuscriptcentral.com/ijde>. New users should first create an
account. Once a user is logged onto the site submissions should be made via
the Author Centre. *Please indicate the paper is submitted to Special Issue
on “Social Sensing and Big Data Computing for Disaster Management” in the
cover letter.*

Each paper will receive comments from at least three reviewers. The special
issue will include a maximum of 8 papers.

We look forward to your contributions. Please do not hesitate to contact
the Guest Editors in case of questions.

-------------------------

Zhenlong Li, Ph.D.

Assistant Professor, Department of Geography
Hazards and Vulnerability Research Institute

University of South Carolina

Callcott Bldg, 709 Bull Street, Room 320, Columbia, SC 29208

803-777-4590 <(803)%20777-4590>

zhenlong at sc.edu

http://zhenlongsc.com

http://gis.cas.sc.edu/gibd/ <http://artsandsciences.sc.edu/geog/zhenlong-li>

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