This research compares expert and non-expert conceptualisations of land cover data collected through a Google Earth web-based interface. In so doing it seeks to determine the impacts of varying landscape conceptualisations held by different groups of VGI contributors on decisions that may be made using crowdsourced data, in this case to select the best global land cover dataset in each location. Whilst much other work has considered the quality of VGI, as yet little research has considered the impact of varying semantics and conceptualisations on the use of VGI in formal scientific analyses. This study found that conceptualisation of cropland varies between experts and non-experts. A number of areas for further research are outlined. © 2013 Springer International Publishing Switzerland.
CITATION STYLE
Comber, A., Brunsdon, C., See, L., Fritz, S., & McCallum, I. (2013). Comparing expert and non-expert conceptualisations of the land: An analysis of crowdsourced land cover data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8116 LNCS, pp. 243–260). Springer Verlag. https://doi.org/10.1007/978-3-319-01790-7_14
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