research-article

Using nightlight remote sensing imagery and Twitter data to study power outages

Authors:

Carolynne Hultquist,

Qunying HuangAuthors Info & Claims

EM-GIS '15: Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management

Article No.: 6, Pages 1 - 6

https://doi.org/10.1145/2835596.2835601

Published: 03 November 2015 Publication History

Abstract

Hurricane Sandy made landfall in one of the most populated areas of the United States, and affected almost 8 million people. The event provides a unique opportunity to study power outages because of the data available and the large impact to a densely populated area. Satellite nightlight imagery of "before" and "after" the landfall of the hurricane is used to quantify the light dimming caused by power outages. Geolocated tweets filtered by keywords provide valuable information on human activity at a high temporal and spatial resolution during the event. Analysis of brightness change in the satellite data and the density of power related tweets points to a spatial relationship that identifies severely impacted areas with human presence. Classification of tweets through text analysis serves to further narrow the information search to find the most relevant and reliable content. Twitter data fused with satellite imagery identifies power outage information at a street-level resolution that is not achievable with satellite imagery alone.

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Cited By

Brelsford CTennille SMyers AChinthavali STansakul VDenman MColetti MGrant JLee SAllen KJohnson EHuihui JHamaker ANewby SMedlen KMaguire DDunivan Stahl CMoehl JRedmon DSanyal JBhaduri B(2024)A dataset of recorded electricity outages by United States county 2014–2022Scientific Data10.1038/s41597-024-03095-511:1Online publication date: 5-Mar-2024
https://doi.org/10.1038/s41597-024-03095-5
Rashid MWei NWang D(2023)A survey on social-physical sensing: An emerging sensing paradigm that explores the collective intelligence of humans and machinesCollective Intelligence10.1177/263391372311708252:2(263391372311708)Online publication date: 25-Apr-2023
https://doi.org/10.1177/26339137231170825
Pal AWang JWu YKant KLiu ZSato K(2023)Social Media Driven Big Data Analysis for Disaster Situation Awareness: A TutorialIEEE Transactions on Big Data10.1109/TBDATA.2022.31584319:1(1-21)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3158431
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Index Terms

Using nightlight remote sensing imagery and Twitter data to study power outages
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Data mining
    2. Spatial-temporal systems

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cover image ACM Conferences

EM-GIS '15: Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management

November 2015

116 pages

ISBN:9781450339704

DOI:10.1145/2835596

Conference Chairs:
Yan Huang,
Jean-Claude Thill,
Hui Zhang

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2015

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SIGSPATIAL

SIGSPATIAL'15: 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 3 - 6, 2015

Washington, Bellevue

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Overall Acceptance Rate 30 of 54 submissions, 56%

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Cited By

Brelsford CTennille SMyers AChinthavali STansakul VDenman MColetti MGrant JLee SAllen KJohnson EHuihui JHamaker ANewby SMedlen KMaguire DDunivan Stahl CMoehl JRedmon DSanyal JBhaduri B(2024)A dataset of recorded electricity outages by United States county 2014–2022Scientific Data10.1038/s41597-024-03095-511:1Online publication date: 5-Mar-2024
https://doi.org/10.1038/s41597-024-03095-5
Rashid MWei NWang D(2023)A survey on social-physical sensing: An emerging sensing paradigm that explores the collective intelligence of humans and machinesCollective Intelligence10.1177/263391372311708252:2(263391372311708)Online publication date: 25-Apr-2023
https://doi.org/10.1177/26339137231170825
Pal AWang JWu YKant KLiu ZSato K(2023)Social Media Driven Big Data Analysis for Disaster Situation Awareness: A TutorialIEEE Transactions on Big Data10.1109/TBDATA.2022.31584319:1(1-21)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3158431
Yamashita OYokoyama S(2022)Preference aware route recommendation using one billion geotagged tweetsProceedings of the 6th ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising10.1145/3557992.3565990(1-10)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557992.3565990
Zhu XWang YKochupillai MWerner MHaberle MHoffmann ETaubenbock HTuia DLevering AJacobs NKruspe AAbdulahhad K(2022)Geoinformation Harvesting From Social Media Data: A community remote sensing approachIEEE Geoscience and Remote Sensing Magazine10.1109/MGRS.2022.321958410:4(150-180)Online publication date: Dec-2022
https://doi.org/10.1109/MGRS.2022.3219584
Xu JQiang Y(2021)Spatial Assessment of Community Resilience from 2012 Hurricane Sandy Using Nighttime LightRemote Sensing10.3390/rs1320412813:20(4128)Online publication date: 15-Oct-2021
https://doi.org/10.3390/rs13204128
Hultquist COravecz ZCervone G(2021)A Bayesian Approach to Estimate the Spatial Distribution of Crowdsourced Radiation Measurements around FukushimaISPRS International Journal of Geo-Information10.3390/ijgi1012082210:12(822)Online publication date: 6-Dec-2021
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Li JLiu ZLei XWang L(2021)Distributed Fusion of Heterogeneous Remote Sensing and Social Media Data: A Review and New DevelopmentsProceedings of the IEEE10.1109/JPROC.2021.3079176109:8(1350-1363)Online publication date: Aug-2021
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Hultquist CCervone G(2020)Integration of Crowdsourced Images, USGS Networks, Remote Sensing, and a Model to Assess Flood Depth during Hurricane FlorenceRemote Sensing10.3390/rs1205083412:5(834)Online publication date: 5-Mar-2020
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Chidziwisano GWyche SOduor EBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)GridAlert: Using a Sensor-Based Technology to Monitor Power Blackouts in Kenyan HomesProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376500(1-13)Online publication date: 21-Apr-2020
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