eprintid: 13910 rev_number: 17 eprint_status: archive userid: 2 dir: disk0/00/01/39/10 datestamp: 2016-11-02 14:20:27 lastmod: 2022-10-19 05:00:41 status_changed: 2016-11-02 14:20:27 type: article metadata_visibility: show creators_name: Laso Bayas, J.C. creators_name: See, L. creators_name: Fritz, S. creators_name: Sturn, T. creators_name: Perger, C. creators_name: Dürauer, M. creators_name: Karner, M. creators_name: Moorthy, I. creators_name: Schepaschenko, D. creators_name: Domian, D. creators_name: McCallum, I. creators_id: 2106 creators_id: 8571 creators_id: 8130 creators_id: 2051 creators_id: 1899 creators_id: 2013 creators_id: 1983 creators_id: 2089 creators_id: 7435 creators_id: 2070 creators_id: 1731 creators_orcid: 0000-0003-2844-3842 creators_orcid: 0000-0002-2665-7065 creators_orcid: 0000-0003-0420-8549 creators_orcid: 0000-0002-7814-4990 creators_orcid: 0000-0002-5812-9988 title: Crowdsourcing In-Situ Data on Land Cover and Land Use Using Gamification and Mobile Technology ispublished: pub divisions: prog_esm keywords: crowdsourcing; citizen science; volunteered geographic information; photocaching; LUCAS; land cover; land use; gamification; mobile phones abstract: Citizens are increasingly becoming involved in data collection, whether for scientific purposes, to carry out micro-tasks, or as part of a gamified, competitive application. In some cases, volunteered data collection overlaps with that of mapping agencies, e.g., the citizen-based mapping of features in OpenStreetMap. LUCAS (Land Use Cover Area frame Sample) is one source of authoritative in-situ data that are collected every three years across EU member countries by trained personnel at a considerable cost to taxpayers. This paper presents a mobile application called FotoQuest Austria, which involves citizens in the crowdsourcing of in-situ land cover and land use data, including at locations of LUCAS sample points in Austria. The results from a campaign run during the summer of 2015 suggest that land cover and land use can be crowdsourced using a simple protocol based on LUCAS. This has implications for remote sensing as this data stream represents a new source of potentially valuable information for the training and validation of land cover maps as well as for area estimation purposes. Although the most detailed and challenging classes were more difficult for untrained citizens to recognize, the agreement between the crowdsourced data and the LUCAS data for basic high level land cover and land use classes in homogeneous areas (ca. 80%) shows clear potential. Recommendations for how to further improve the quality of the crowdsourced data in the context of LUCAS are provided so that this source of data might one day be accurate enough for land cover mapping purposes. date: 2016 id_number: 10.3390/rs8110905 creators_browse_id: 172 creators_browse_id: 276 creators_browse_id: 98 creators_browse_id: 301 creators_browse_id: 228 creators_browse_id: 73 creators_browse_id: 144 creators_browse_id: 211 creators_browse_id: 279 creators_browse_id: 67 creators_browse_id: 202 full_text_status: public publication: Remote Sensing volume: 8 number: 11 pagerange: e905 refereed: TRUE issn: 2072-4292 projects: Harnessing the power of crowdsourcing to improve land cover and land-use information (CROWDLAND, FP7 617754) coversheets_dirty: FALSE fp7_project: yes fp7_project_id: info:eu-repo/grantAgreement/EC/FP7/617754/EU/Harnessing the power of crowdsourcing to improve land cover and land-use information/CROWDLAND fp7_type: info:eu-repo/semantics/article access_rights: info:eu-repo/semantics/openAccess citation: Laso Bayas, J.C. ORCID: https://orcid.org/0000-0003-2844-3842 , See, L. ORCID: https://orcid.org/0000-0002-2665-7065 , Fritz, S. ORCID: https://orcid.org/0000-0003-0420-8549 , Sturn, T. , Perger, C. , Dürauer, M. , Karner, M. , Moorthy, I. , et al. (2016). Crowdsourcing In-Situ Data on Land Cover and Land Use Using Gamification and Mobile Technology. Remote Sensing 8 (11) e905. 10.3390/rs8110905 . document_url: https://pure.iiasa.ac.at/id/eprint/13910/1/remotesensing-08-00905.pdf