Salk, Carl and Sturn, Tobias and See, Linda and Fritz, Steffen
(2016).
Local knowledge and professional background have a minimal impact on volunteer citizen science performance in a land-cover classification task.
Remote sensing. 8
:9
, 1-13
[Journal article]
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Available under License Creative Commons Attribution. 865kB |
Official URL: http://dx.doi.org/10.3390/rs8090774
Abstract
The idea that closer things are more related than distant things, known as Tobler's first law of geography', is fundamental to understanding many spatial processes. If this concept applies to volunteered geographic information (VGI), it could help to efficiently allocate tasks in citizen science campaigns and help to improve the overall quality of collected data. In this paper, we use classifications of satellite imagery by volunteers from around the world to test whether local familiarity with landscapes helps their performance. Our results show that volunteers identify cropland slightly better within their home country, and do slightly worse as a function of linear distance between their home and the location represented in an image. Volunteers with a professional background in remote sensing or land cover did no better than the general population at this task, but they did not show the decline with distance that was seen among other participants. Even in a landscape where pasture is easily confused for cropland, regional residents demonstrated no advantage. Where we did find evidence for local knowledge aiding classification performance, the realized impact of this effect was tiny. Rather, the inherent difficulty of a task is a much more important predictor of volunteer performance. These findings suggest that, at least for simple tasks, the geographical origin of VGI volunteers has little impact on their ability to complete image classifications.
Authors/Creators: | Salk, Carl and Sturn, Tobias and See, Linda and Fritz, Steffen | ||||
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Title: | Local knowledge and professional background have a minimal impact on volunteer citizen science performance in a land-cover classification task | ||||
Series/Journal: | Remote sensing (2072-4292) | ||||
Year of publishing : | 2016 | ||||
Volume: | 8 | ||||
Number: | 9 | ||||
Page range: | 1-13 | ||||
Number of Pages: | 13 | ||||
Publisher: | MDPI | ||||
ISSN: | 2072-4292 | ||||
Language: | English | ||||
Publication Type: | Journal article | ||||
Refereed: | Yes | ||||
Article category: | Scientific peer reviewed | ||||
Version: | Published version | ||||
Copyright: | Creative Commons: Attribution 4.0 | ||||
Full Text Status: | Public | ||||
Agris subject categories.: | P Natural resources > P01 Nature conservation and land resources | ||||
Subjects: | (A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Environmental Sciences (social aspects to be 507) (A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Geosciences, Multidisciplinary | ||||
Keywords: | crowdsourcing, citizen science, data quality, Tobler's Law, local knowledge, remote sensing, land cover, cropland, volunteered geographical information | ||||
URN:NBN: | urn:nbn:se:slu:epsilon-e-4131 | ||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-4131 | ||||
Additional ID: |
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ID Code: | 14274 | ||||
Faculty: | S - Faculty of Forest Sciences | ||||
Department: | (S) > Southern Swedish Forest Research Centre | ||||
Deposited By: | SLUpub Connector | ||||
Deposited On: | 27 Apr 2017 08:11 | ||||
Metadata Last Modified: | 09 Sep 2020 14:17 |
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