Okanagan Mountain Park Fire (Kelowna, BC, 2003) 64000 acres, $33.8 - - PowerPoint PPT Presentation

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Okanagan Mountain Park Fire (Kelowna, BC, 2003) 64000 acres, $33.8 - - PowerPoint PPT Presentation

Jun 30, 2023 252 likes •536 views

V ISUALIZING W ILDFIRE N ARRATIVES LAS 2015 D ECEMBER 2, 2015 C HRISTOPHER G. H EALEY B RANDA N OWELL AJ F AAS N ORTH C AROLINA S TATE U NIVERSITY S AN J OSE S TATE U NIVERSITY SIC PARVIS MAGNA NC STATE UNIVERSITY

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SLIDE 1

VISUALIZING WILDFIRE NARRATIVES

LAS 2015

DECEMBER 2, 2015

CHRISTOPHER G. HEALEY BRANDA NOWELL AJ FAAS

NORTH CAROLINASTATE UNIVERSITY SAN JOSE STATE UNIVERSITY

SIC PARVIS MAGNA

NC STATE UNIVERSITY

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SLIDE 2

Okanagan Mountain Park Fire (Kelowna, BC, 2003)

64000 acres, $33.8 million,239 homes destroyed http://www.icarus.ca/icarus/?p=1024

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SLIDE 3

NATIONAL COHESIVE STRATEGY

To safely and effective extinguish fire, when needed; use fire where allowable; manage our natural resources; and as a Nation, live with wildland fire.

National Cohesive Wildland Fire Management Strategy April, 2014

http://www.forestsandrangelands.gov/strategy

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SLIDE 4

National Interagency Fire Center

http://www.nifc.gov/fireInfo/fireInfo_stats_totalFires.html

2,000 4,000 6,000 8,000 10,000 12,000 50 100 150 200 250 300 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Acres Thousands Fires Thousands Year

Number of Fires and Acres Burned

Fires Acres

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SLIDE 5

National Interagency Fire Center

http://www.nifc.gov/fireInfo/fireInfo_stats_histSigFires.html

Miramachi, 3M Great Fire, 1.5M Yaquina, 450K Coos, 300K Lower Michigan, 2.5M South Carolina, 3M Adirondack, 637K Great Idaho, 3M Cloquet-Moose Lake, 1.2M Tillamook, 311K Seige of '87, 640K Yellowstone, 1.6M Inowak, 610K Dunn-Glen, 288K Rodeo-Chediski, 462K Cedar, 275K Taylor, 1.3M East Amarillo, 907K Big Turnaround, 388K Murphy, 652K Long Butte, 300K Wallow, 538K Whitewater-Baldy, 298K Long Draw, 558K Rim, 257K 500 1,000 1,500 2,000 2,500 3,000 3,500 1825 1845 1853 1868 1881 1898 1903 1910 1918 1933 1987 1988 1997 1999 2002 2003 2004 2006 2007 2007 2010 2011 2012 2012 2013

Acres Thousands Year

Twenty-Five Largest Fires By Acres

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SLIDE 6

National Interagency Fire Center

http://www.nifc.gov/fireInfo/fireInfo_documents/SuppCosts.pdf

200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Dollars Millions Year

USFS / DOI Wildfire Costs

US Forest Service Department of Interior

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SLIDE 7

PROJECT OBJECTIVES

  • What are dominant wildfire and

risk narratives communicated through social media?

  • How are narratives shaped by

ecological, social, and political characteristics?

  • How do narratives evolve over

time and in response to actual wildfire events?

  • How can social media be used to engage the public and

wildfire risk and risk-mitigation?

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SLIDE 8

Colorado Springs Fire Department Wildfire Mitigation

http://www.springsgov.com/Page.aspx?NavID=101

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SLIDE 9

PROJECT PLAN

  • 1. Capture, index, store wildfire

incident Twitter communication

  • 2. Perform thematic and

sentiment analysis of tweets

  • 3. Analyze and visualize information

flow within socialmedia networks

  • Community engagement: for risk mitigation prior to a

wildfire

  • Communication: between emergency management and

communities during wildfire events

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SLIDE 10

DATA CAPTURE

  • Capturing tweets with keywords “wildfire” and “forest

service” since May 14, 2013

– 3 million tweets stored in MySQL database

  • Extracting relevant tweet properties

– date and time – author – body – geolocation

  • DenverCP | -104.994593,39.746012 | Wildfire burning SW of Beulah

closes Hwy. 165: BEULAH, Colo. A small wildfire burned in Pueblo County just... http://t.co/FfPeLrpIS6 | Sun Jun 01 02:21:12 +0000 2014

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SLIDE 11

TEXT VISUALIZATION

  • Visualize properties of “documents” in a “collection”
  • We analyze individual tweets as short text documents

– sentiment, topics, term frequency, geolocation, affinity

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SLIDE 12

SINGLE TWEET VISUALIZATION

unpleasant pleasant

pleasure hue

sedate active

arousal luminance

low confidence high confidence

rating variation

  • pacity

low confidence high confidence

rating frequency size

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SLIDE 13

SENTIMENT SCATTERPLOT

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 14

SENTIMENT VALUES

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 15

TOPIC CLUSTERS

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 16

TOPIC CLUSTERS

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 17

SENTIMENT HEATMAP

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 18

SENTIMENT TAG CLOUD

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 19

SENTIMENT TIMELINE

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 20

GEOLOCATION

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 21

AFFINITY GRAPH

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 22

TWEET TEXT

King Fire (El Dorado County, CA, 2014)

97717 acres, $91 million, 80 residences destroyed

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SLIDE 23

CURRENT RESEARCH CHALLENGES

  • Contextual tweet filtering: via natural language processing
  • Narrative threads: construction and visualization
  • Real-world validation: with JFS public information officers

Visualizing character threads from “Star Wars IV: A New Hope”

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SLIDE 24

TWITTER NARRATIVE

  • Identify narrative threads passing through “anchor” tweet

anchor tweet thread 1 thread 2 thread 3

Sep 23, 10:15am psapconnectnews: Californi a Wildfire Crews Brace For Weather Shift: The King Fire region is expected to experience erractic win… http://t.co/Qg9RKNC10B

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SLIDE 25

THREAD CONSTRUCTION

  • 1. Find all tweets above similarity ε to anchor tweet
  • 2. Bundle similar tweets plus anchor into “similarity sets”
  • 3. Convert similarity sets into DAGs where:

– tweets connected if pairwise similarity > τ, τ < ε – edge direction based on time, older to newer

  • 4. Identify source nodes as nodes with no incoming edges
  • 5. Apply Bellman-Ford on DAGs to find longest path from

every source node

  • 6. Keep any longest paths that contain anchor, these form

narrative threads

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SLIDE 26

CONTACT INFORMATION

CHRISTOPHER G. HEALEY

HEALEY@NCSU.EDU WWW.CSC.NCSU.EDU/FACULTY/HEALEY

FIRE CHASERS PROJECT

RESEARCH.CNR.NCSU.EDU/BLOGS/FIRECHASERS

TWEET VISUALIZER

WWW.CSC.NCSU.EDU/FACULTY/HEALEY/TWEET_VIZ/TWEET_APP

NC STATE UNIVERSITY