DOI: 10.1016/j.jag.2015.03.012
Scopus记录号: 2-s2.0-84943609393
论文题名: Geo-reCAPTCHA: Crowdsourcing large amounts of geographic information from earth observation data
作者: Hillen F ; , Höfle B
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 40 起始页码: 29
结束页码: 38
语种: 英语
英文关键词: Crowdsourcing
; Geo-reCAPTCHA
; reCAPTCHA
; User-generated geographic information
; Volunteered geographic information
Scopus关键词: digitization
; empirical analysis
; GIS
英文摘要: The reCAPTCHA concept provides a large amount of valuable information for various applications. First, it provides security, e.g., for a form on a website, by means of a test that only a human could solve. Second, the effort of the user for this test is used to generate additional information, e.g., digitization of books or identification of house numbers. In this work, we present a concept for adapting the reCAPTCHA idea to create user-generated geographic information from earth observation data, and the requirements during the conception and implementation are depicted in detail. Furthermore, the essential parts of a Geo-reCAPTCHA system are described, and afterwards transferred, to a prototype implementation. An empirical user study is conducted to investigate the Geo-reCAPTCHA approach, assessing time and quality of the resulting geographic information. Our results show that a Geo-reCAPTCHA can be solved by the users of our study on building digitization in a short amount of time (19.2 s on average) with an overall average accuracy of the digitizations of 82.2%. In conclusion, Geo-reCAPTCHA has the potential to be a reasonable alternative to the typical reCAPTCHA, and to become a new data-rich channel of crowdsourced geographic information. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79530
Appears in Collections: 气候变化事实与影响
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作者单位: Institute for Geoinformatics and Remote Sensing (IGF), University of Osnabrueck, Barbarastr. 22b, Osnabrück, Germany; Institute of Geography, Heidelberg University, Berliner Str. 48, Heidelberg, Germany
Recommended Citation:
Hillen F,, Höfle B. Geo-reCAPTCHA: Crowdsourcing large amounts of geographic information from earth observation data[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,40