Detecting environmental disasters in digital news archives

Automatically extracting events from large, unstructured/semi-structured textual data requires a mechanism for identifying the event, abstracting it from the text, validating the event's occurrence against some known values, and sharing the event with users effectively. Inherent in the challenge of Big Data is that it often exceeds a scale at which humans can effectively operate. In this paper, we focus on the domain of archived newspaper articles, and describe a system that generates a collection of event summaries from unstructured text, extracts a geographic marker for the event, and stores both in an on-line database that can be searched and/or visualized using an interactive map. The system relies on text mining techniques to filter out a dataset of news stories from a digital news archive source and extracts 1-2 sentences from each event to be stored in the database. We illustrate this approach using a flood database case study, automatically extracting descriptions of past flooding events occurring in Nova Scotia, Canada from a 20-year archive of regional newspaper articles. We validate our event extraction in two dimensions (identification of articles mentioning flood events; identification of accurate geographic markers from articles about flood events) using Amazon's Mechanical Turk (MTurk) to obtain human assessments at scale.

[1]  Alice Deschamps,et al.  Geospatial data integration for applications in flood prediction and management in the Red River Basin , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[2]  M. Llasat,et al.  A flood geodatabase and its climatological applications: the case of Catalonia for the last century , 2007 .

[3]  MARY W. DOWNTON,et al.  How Accurate are Disaster Loss Data? The Case of U.S. Flood Damage , 2005 .

[4]  Chang-Tai Tsai,et al.  DEVELOPMENT OF A GIS‐BASED FLOOD INFORMATION SYSTEM FOR FLOODPLAIN MODELING AND DAMAGE CALCULATION , 2000 .

[5]  C. Gaziano,et al.  Measuring the Concept of Credibility , 1986 .

[6]  Jakub Piskorski,et al.  Real-Time News Event Extraction for Global Crisis Monitoring , 2008, NLDB.

[7]  Gregory R. Crane,et al.  The challenge of virginia banks: an evaluation of named entity analysis in a 19th-century newspaper collection , 2006, Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '06).

[8]  B. Pradhan.  Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing , 2010 .

[9]  Hans Peter Luhn,et al.  The Automatic Creation of Literature Abstracts , 1958, IBM J. Res. Dev..

[10]  Jean-Pierre Villeneuve,et al.  DISTRIBUTED WATERSHED MODEL COMPATIBLE WITH REMOTE SENSING AND GIS DATA .I : D ESCRIPTION OF MODEL , 2001 .

[11]  Ewan Klein,et al.  Natural Language Processing with Python , 2009 .

[12]  Michalis Diakakis,et al.  Using a Spatio-Temporal GIS Database to Monitor the Spatial Evolution of Urban Flooding Phenomena. The Case of Athens Metropolitan Area in Greece , 2014, ISPRS Int. J. Geo Inf..

[13]  Anders Grönlund,et al.  Predicting Flood Inundation and Risk Using Geographic Information System and Hydrodynamic Model , 2002, Ann. GIS.

[14]  R. Manmatha,et al.  Word spotting for historical documents , 2006, International Journal of Document Analysis and Recognition (IJDAR).

[15]  Satoshi Sekine,et al.  A survey of named entity recognition and classification , 2007 .

[16]  Allison Woodruff,et al.  GIPSY: automated geographic indexing of text documents , 1994 .

[17]  Kalev Leetaru,et al.  Fulltext Geocoding Versus Spatial Metadata for Large Text Archives: Towards a Geographically Enriched Wikipedia , 2012, D Lib Mag..

[18]  G. Karatzas,et al.  Flood management and a GIS modelling method to assess flood-hazard areas—a case study , 2011 .

[19]  Marin Litoiu,et al.  Toward an Ecosystem for Precision Sharing of Segmented Big Data , 2013, 2013 IEEE Sixth International Conference on Cloud Computing.

[20]  F. Pasquarè,et al.  Geological hazards, disasters and the media: The Italian case study , 2007 .

[21]  Han Tong Loh,et al.  Gather customer concerns from online product reviews - A text summarization approach , 2009, Expert Syst. Appl..

[22]  Jacob P. Kovel,et al.  Using GIS in Emergency Management Operations , 2000 .