COMPARING NATIONAL DIFFERENCES IN WHAT PEOPLE PERCEIVE TO BE <i>THERE</i>: MAPPING VARIATIONS IN CROWD SOURCED LAND COVER
This paper describes a simple comparison of the distributions of land cover features identified from volunteered data contributed by different social groups – in this case comparing two groups of Geo-Wiki campaigns. Understanding the impacts on analyses of citizen science data contributed by differe...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-08-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/71/2015/isprsarchives-XL-3-W3-71-2015.pdf |
| Summary: | This paper describes a simple comparison of the distributions of land cover features identified from volunteered data contributed by
different social groups – in this case comparing two groups of Geo-Wiki campaigns. Understanding the impacts on analyses of
citizen science data contributed by different groups is critical to ensure robust scientific outputs and to fully realise the potential
benefits to formal scientific research. It is well known that different people, with different backgrounds and subject to different
cultural factors, hold varying landscape conceptualisations. This paper analyses volunteered geographical information on land cover
to generate land cover maps. It uses a geographically weighted approach to generate land cover mappings. The mappings generated
by different groups (in this case a from a specific unnamed country) are compared and the results show how the predicted land cover
distributions vary, with large differences in some classes (e.g. Barren land, Shrubland, Wetland) and little difference in others (e.g.
Tree cover). This suggests that for some landscape features cultural and national differences matter when it comes to using
crowdsourced data in formal scientific analyses and highlights the potential problems of not considering contributor backgrounds in
citizen science. This is important because such data re now routinely being used to develop global land cover data, to generate
uncertainty estimates of existing global land cover products and to generate global forest inventories. These in turn are being
suggested as suitable inputs to such things as global climate models. A number of critical research directions arising from these
findings are discussed. |
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| ISSN: | 1682-1750 2194-9034 |