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.
Highlights
Members of the public, acting as non-expert volunteers, have been involved in scientific research for more than a century [1] yet the rise of citizen science is a much more recent phenomenon [2]
This indicates that more detailed land use is easier to identify than detailed land cover, which would require, e.g., tree type and crop type identification skills, which many people may not possess
The overall agreement between the land cover and land use data at high level (L1) collected by citizens compared with authoritative data from LUCAS was close to 70%
Summary
Members of the public, acting as non-expert volunteers, have been involved in scientific research for more than a century [1] yet the rise of citizen science is a much more recent phenomenon [2]. Other initiatives that involve citizens have emerged, which are better described using the term crowdsourcing [3] This is defined as the outsourcing of micro-tasks to the public, either for small payments using a platform such as Amazon’s Mechanical Turk [4], or for other incentives, e.g., helping to find the missing Malaysian airlines plane (MH370) by collectively examining very high resolution satellite imagery over a vast geographical area [5]. This rise in the active involvement of the public can be attributed to a number of factors including the proliferation of location-enabled mobile devices (which has led to the term Volunteered Geographic Information (VGI), where citizens are sensors. Remote Sens. 2016, 8, 905 of location-based information [6]); access to global, very high resolution satellite imagery via Google and Bing; and the development of Web 2.0 technology, which has led to a whole new generation of user-generated content including online mapping and neogeography [7].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
