Author
Listed:
- Juan Carlos Laso Bayas
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Linda See
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Hedwig Bartl
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Tobias Sturn
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Mathias Karner
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Dilek Fraisl
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria
Department of Economics and Social Sciences, University of Natural Resources and Life Science Vienna (BOKU), 1180 Vienna, Austria)
- Inian Moorthy
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
- Michaela Busch
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria
Fritsch, Chiari und Partner ZT GmbH, Marxergasse 1B, 1030 Vienna, Austria)
- Marijn van der Velde
(European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy)
- Steffen Fritz
(Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria)
Abstract
There are many new land use and land cover (LULC) products emerging yet there is still a lack of in situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens. Moreover, the photographs submitted through the app were not always of sufficient quality. For these reasons, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree. Furthermore, a near real-time quality assurance system was implemented to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to determine whether citizens can provide high quality in situ data on LULC through crowdsourcing that can complement LUCAS. We compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. As shown by the cost comparisons with LUCAS, FotoQuest can complement LUCAS surveys by enabling continuous collection of large amounts of high quality, spatially explicit field data at a low cost.
Suggested Citation
Juan Carlos Laso Bayas & Linda See & Hedwig Bartl & Tobias Sturn & Mathias Karner & Dilek Fraisl & Inian Moorthy & Michaela Busch & Marijn van der Velde & Steffen Fritz, 2020.
"Crowdsourcing LUCAS: Citizens Generating Reference Land Cover and Land Use Data with a Mobile App,"
Land, MDPI, vol. 9(11), pages 1-18, November.
Handle:
RePEc:gam:jlands:v:9:y:2020:i:11:p:446-:d:445406
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