Next Article in Journal
Characterizing Forest Fuel Properties and Potential Wildfire Dynamics in Xiuwu, Henan, China
Next Article in Special Issue
Fire Source Determination Method for Underground Commercial Streets Based on Perception Data and Machine Learning
Previous Article in Journal
Validation of NWCG Wildfire Directional Indicators in Test Burns in Coastal California
Previous Article in Special Issue
Recent Advances and Emerging Directions in Fire Detection Systems Based on Machine Learning Algorithms
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas

1
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
2
GIPSA-Lab, Université Grenoble Alpes, CNRS, Grenoble INP, 38402 Saint Martin d’Heres, France
*
Author to whom correspondence should be addressed.
Submission received: 5 October 2023 / Revised: 20 November 2023 / Accepted: 19 December 2023 / Published: 21 December 2023
(This article belongs to the Special Issue Intelligent Fire Protection)

Abstract

Natural hazards such as wildfires have proven to be more frequent in recent years, and to minimize losses and activate emergency response, it is necessary to estimate their impact quickly and consequently identify the most affected areas. Volunteered geographic information (VGI) data, particularly from the social media platform Twitter, now X, are emerging as an accessible and near-real-time geoinformation data source about natural hazards. Our study seeks to analyze and evaluate the feasibility and limitations of using tweets in our proposed method for fire area assessment in near-real time. The methodology involves weighted barycenter calculation from tweet locations and estimating the affected area through various approaches based on data within tweet texts, including viewing angle to the fire, road segment blocking information, and distance to fire information. Case study scenarios are examined, revealing that the estimated areas align closely with fire hazard areas compared to remote sensing (RS) estimated fire areas, used as pseudo-references. The approach demonstrates reasonable accuracy with estimation areas differing by distances of 2 to 6 km between VGI and pseudo-reference centers and barycenters differing by distances of 5 km on average from pseudo-reference centers. Thus, geospatial analysis on VGI, mainly from Twitter, allows for a rapid and approximate assessment of affected areas. This capability enables emergency responders to coordinate operations and allocate resources efficiently during natural hazards.
Keywords: natural hazards; wildfires; volunteered geographic information (VGI); geospatial analysis; near-real-time geoinformation; fire area assessment; emergency response natural hazards; wildfires; volunteered geographic information (VGI); geospatial analysis; near-real-time geoinformation; fire area assessment; emergency response

Share and Cite

MDPI and ACS Style

Florath, J.; Chanussot, J.; Keller, S. Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas. Fire 2024, 7, 6. https://doi.org/10.3390/fire7010006

AMA Style

Florath J, Chanussot J, Keller S. Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas. Fire. 2024; 7(1):6. https://doi.org/10.3390/fire7010006

Chicago/Turabian Style

Florath, Janine, Jocelyn Chanussot, and Sina Keller. 2024. "Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas" Fire 7, no. 1: 6. https://doi.org/10.3390/fire7010006

APA Style

Florath, J., Chanussot, J., & Keller, S. (2024). Utilizing Volunteered Geographic Information for Real-Time Analysis of Fire Hazards: Investigating the Potential of Twitter Data in Assessing the Impacted Areas. Fire, 7(1), 6. https://doi.org/10.3390/fire7010006

Article Metrics

Back to TopTop