Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake

2010 ◽  
Author(s):  
Matthew Zook ◽  
Mark Graham ◽  
Taylor Shelton ◽  
Sean Gorman
Keyword(s):  
Disaster Relief ◽  
Volunteered Geographic Information ◽  
Geographic Information

scholarly journals A Thematic Similarity Network Approach for Analysis of Places Using Volunteered Geographic Information

2020 ◽  
Vol 9 (6) ◽  
pp. 385 ◽  
Author(s):  
Xiaoyi Yuan ◽  
Andrew Crooks ◽  
Andreas Züfle
Keyword(s):  
New York ◽  
Low Income ◽  
Topic Modeling ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Network Approach ◽  
Similarity Network ◽  
Textural Data ◽  
Restaurant Reviews

The research presented in this paper proposes a thematic network approach to explore rich relationships between places. We connect places in networks through their thematic similarities by applying topic modeling to the textual volunteered geographic information (VGI) pertaining to the places. The network approach enhances previous research involving place clustering using geo-textual information, which often simplifies relationships between places to be either in-cluster or out-of-cluster. To demonstrate our approach, we use as a case study in Manhattan (New York) that compares networks constructed from three different geo-textural data sources—TripAdvisor attraction reviews, TripAdvisor restaurant reviews, and Twitter data. The results showcase how the thematic similarity network approach enables us to conduct clustering analysis as well as node-to-node and node-to-cluster analysis, which is fruitful for understanding how places are connected through individuals’ experiences. Furthermore, by enriching the networks with geodemographic information as node attributes, we discovered that some low-income communities in Manhattan have distinctive restaurant cultures. Even though geolocated tweets are not always related to place they are posted from, our case study demonstrates that topic modeling is an efficient method to filter out the place-irrelevant tweets and therefore refining how of places can be studied.

scholarly journals Approaching Bike Hazards via Crowdsourcing of Volunteered Geographic Information

2020 ◽  
Vol 12 (17) ◽  
pp. 7015
Author(s):  
Rafael Hologa ◽  
Nils Riach
Keyword(s):  
Small Group ◽  
Volunteered Geographic Information ◽  
Smartphone Application ◽  
Geographic Information ◽  
Urban Cycling ◽  
Accident Data ◽  
The Individual ◽  
Key Aspects ◽  
The City

Information on individual hazard perception while cycling and the associated feeling of safety are key aspects to foster sustainable urban cycling mobility. Although cyclist’s perceptions must also be critically reviewed, such crowdsourced Volunteered Geographic Information (VGI) provides wide-ranging insights on diverse hazard categories in cycling. In this case study in the city of Freiburg, Germany, hazard perceptions, information about lane types, and the underlying routes were crowdsourced via an open source smartphone application by a small group with the aim of providing cyclists with effective solutions. By dealing with levels of reliability, we show that even a small group of laypersons can generate an extensive and valuable set of VGI consisting of comprehensive hazard categories. We demonstrate that (1) certain hazards are interlinked to specific lane types, and (2) the individual hazard perceptions and objective parameters, i.e., accident data, are often congruent spatially; consequently, (3) dangerous hot spots can be derived. By considering cyclists’ needs, this approach outlines how a people-based perspective can supplement regional planning on the local scale.

An Integrated Method for Assessing the Text Content Quality of Volunteered Geographic Information in Disaster Management

2017 ◽  
Vol 9 (2) ◽  
pp. 1-17
Author(s):  
Kuo-Chih Hung ◽  
Mohsen Kalantari ◽  
Abbas Rajabifard
Keyword(s):  
Disaster Management ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Content Quality ◽  
Integrated Method ◽  
Needed Information ◽  
Text Content ◽  
Flooding Events

Volunteered geographic information (VGI) has the potential to provide much-needed information for emergency management stakeholders. However, stakeholders often lack scalability to identify useful and high-quality text content from the often-overwhelming amount of information. To solve this problem, most studies have concentrated on using text-related features in supervised learning models to classify text contents. This article proposes an assumption that the geographic attributes of VGI can be integrated into the model as features for enhancing the model's performance. To evaluate this assumption, the authors developed a case study based on VGI collected from two flooding events in Brisbane. They validated the accuracy of associated geographic coordinates and defined the geographic features relevant to the flood phenomenon. From their experiments, model based on this integrated method can have better performance in comparison with the model trained from the text-related features. The results suggest great potential for using the integrated method to harvest useful VGI for the needs of disaster management.

scholarly journals Developing a Workflow to Identify Inconsistencies in Volunteered Geographic Information: A Phenological Case Study

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0140811 ◽  
Author(s):  
Hamed Mehdipoor ◽  
Raul Zurita-Milla ◽  
Alyssa Rosemartin ◽  
Katharine L. Gerst ◽  
Jake F. Weltzin
Keyword(s):  
Volunteered Geographic Information ◽  
Geographic Information
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