Citizen Science in the Age of Neogeography: Utilizing Volunteered Geographic Information for Environmental Monitoring

2012 ◽  
Vol 102 (6) ◽  
pp. 1267-1289 ◽  
Author(s):  
John Patrick Connors ◽  
Shufei Lei ◽  
Maggi Kelly
Author(s):  
H. K. Dhonju ◽  
W. Xiao ◽  
B. Shakya ◽  
J. P. Mills ◽  
V. Sarhosis

Heritage documentation has become increasingly urgent due to both natural impacts and human influences. The documentation of countless heritage sites around the globe is a massive project that requires significant amounts of financial and labour resources. With the concepts of volunteered geographic information (VGI) and citizen science, heritage data such as digital photographs can be collected through online crowd participation. Whilst photographs are not strictly geographic data, they can be geo-tagged by the participants. They can also be automatically geo-referenced into a global coordinate system if collected via mobile phones which are now ubiquitous. With the assistance of web-mapping, an online geo-crowdsourcing platform has been developed to collect and display heritage structure photographs. Details of platform development are presented in this paper. The prototype is demonstrated with several heritage examples. Potential applications and advancements are discussed.


2020 ◽  
pp. 0739456X2097680
Author(s):  
Jerry Shannon ◽  
Kimberly Skobba ◽  
Jermaine Durham ◽  
Chase Polak

This paper evaluates a citizen science initiative to assess housing conditions in multiple rural Georgia communities. Using technologies for digitized collection of volunteered geographic information (VGI) on property conditions and an online dashboard to analyze results, local housing teams identified the characteristics and prevalence of housing problems in their communities. Drawing from a pragmatist framework, we note how this process created new connections between local leaders and residents and brought attention to sometimes unexpected issues. Conversely, participation was uneven within local communities in ways that potentially limit the effectiveness of these local initiatives.


Author(s):  
P. Mooney ◽  
L. Morgan

In the last number of years there has been increased interest from researchers in investigating and understanding the characteristics and backgrounds of citizens who contribute to Volunteered Geographic Information (VGI) and Citizen Science (CS) projects. Much of the reluctance from stakeholders such as National Mapping Agencies, Environmental Ministries, etc. to use data and information generated and collected by VGI and CS projects grows from the lack of knowledge and understanding about who these contributors are. As they are drawn from <i>the crowd</i> there is a sense of the unknown about these citizens. Subsequently there are justifiable concerns about these citizens’ ability to collect, generate and manage high quality and accurate spatial, scientific and environmental data and information. This paper provides a meta review of some of the key literature in the domain of VGI and CS to assess if these concerns are well founded and what efforts are ongoing to improve our understanding of <i>the crowd</i>.


2017 ◽  
Vol 68 (4) ◽  
pp. 835-840
Author(s):  
Daniel Dunea ◽  
Stefania Iordache ◽  
Trond Bohler ◽  
Florian Huber ◽  
Peter Leitner

The paper describes the application of real-time environmental monitoring, local and long-range transport dispersion modeling and Volunteered Geographic Information (VGI) systems that can improve the fast knowledge regarding the air pollution status to determine the actual outdoor conditions for living in a specific urban area. A case study using such techniques is presented for a pollution event with fine particulate matter (PM2.5) in Targoviste, Romania. PM2.5 time series were recorded during the pollution event by two optical monitoring systems providing an average of 184.1, maximum of 323, and minimum of 107 �g m-3 (DustTrackTM 8533 EP system), and 177.4, 321 and 93 �g m-3 (Rokidair microstation), respectively. PM2.5 concentrations and forward trajectories were computed using two programs: BREEZE� AERMOD 7.9 and HYSPLIT dispersion model. The obtained results emphasize the usefulness of embedding dispersion modeling advanced tools to supplement monitoring results and to characterize the source apportionment.


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