全球智库信息集成服务系统(G2TT): Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data.

G2TT

来源类型	Article
规范类型	其他
DOI	10.3390/ijgi7030080 (registering DOI)
	Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data.
	Foody G; See L; Fritz S; Moorthy I; Perger C; Schill D; Boyd D
发表日期	2018
出处	ISPRS International Journal of Geo-Information 7 (3): p. 80
出版年	2018
语种	英语
摘要	Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling.
主题	Ecosystems Services and Management (ESM)
关键词	crowdsourcing volunteered geographic information (VGI) ensemble classification accuracy latent class analysis
URL	http://pure.iiasa.ac.at/id/eprint/15140/
来源智库	International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/131299
推荐引用方式 GB/T 7714	Foody G,See L,Fritz S,et al. Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data.. 2018.

条目包含的文件
文件名称/大小	资源类型	版本类型	开放类型	使用许可
ijgi-07-00080.pdf（536KB）	智库出版物		限制开放	CC BY-NC-SA	浏览