Reprint

Geoinformatics in Citizen Science

Edited by
July 2019
206 pages
  • ISBN978-3-03921-072-5 (Paperback)
  • ISBN978-3-03921-073-2 (PDF)

This book is a reprint of the Special Issue Geoinformatics in Citizen Science that was published in

Computer Science & Mathematics
Environmental & Earth Sciences
Summary

The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science.

Format
  • Paperback
License
© 2019 by the authors; CC BY-NC-ND licence
Keywords
volunteer geographic information; positional accuracy; land administration systems; location-based social networks (LBSNs); clustering; user preference; social relationship effect; spatial proximity; crowdsourcing; volunteered geographic information (VGI); ensemble; classification accuracy; latent class analysis; OpenStreetMap; VGI; community mapping; data analysis; GIS education; data import; citizen science; marine mammal; opportunistic data; Alaska; spatial bias; sample size; volunteer; education; recruitment; Pentatomidae; Environmental niche modeling; citizen science; crowdsourcing; MaxEnt; QGIS; brown marmorated stink bug; air quality estimation; air pollution; citizen science; sky images; social media; data fusion; citizen science; volunteered geographic information (VGI); toponym; crowdsourced data collection; data quality; GIS; digital cartography; algorithms; spatial accuracy; analysis; OpenStreetMap; citizen science; geoinformatics; projects survey; geoinformation in citizen science; VGI in citizen science; crowdsourced geoinformation collection and analysis