Utilizing fuzzy set theory to assure the quality of volunteered geographic information

被引:14
作者
Yan Y. [1 ]
Feng C.-C. [1 ]
Wang Y.-C. [1 ]
机构
[1] Department of Geography, 1 Arts Link, National University of Singapore, Singapore
基金
新加坡国家研究基金会;
关键词
Data quality; Fuzzy system; Species surveillance; Volunteered geographic information;
D O I
10.1007/s10708-016-9699-x
中图分类号
学科分类号
摘要
This paper presents a fuzzy system to assure the quality of volunteered geographic information (VGI) collected for the purposes of species surveillances. The system uses trust as a proxy of quality. It defines the trust using both the provenance of user expertise and the fitness of geographic context and quantifies it using fuzzy set theory. The system was applied to a specific scenario—VGI-based crop pest surveillance—to demonstrate its usefulness in handling VGI quality. A case study was conducted in Jiangxi province of China, where location-based rice pest surveillance reports generated by the local farmers were collected. A field pest survey was conducted by the local pest management experts to verify the farmer-generated reports, and the survey results were used as ground truth data. The quality of the farmer-generated reports were also assessed through the fuzzy system and compared to the pest survey results. It was observed that the degree to which these two sets of results agreed to each other was satisfactory. © 2016, Springer Science+Business Media Dordrecht.
引用
收藏
页码:517 / 532
页数:15
相关论文
共 55 条
[1]  
Adhikari B., Li J., Modelling ambiguity in urban planning, Annals of GIS, 19, 3, pp. 143-152, (2013)
[2]  
Al-kheder S., Wang J., Shan J., Fuzzy inference guided cellular automata urban-growth modelling using multi-temporal satellite images, International Journal of Geographical Information Science, 22, 11-12, pp. 1271-1293, (2008)
[3]  
Bishr M., Weaving space into the web of trust: An asymmetric spatial trust model for social networks. In Proceedings of the 1st conference on social semantic web, Leipzig, Germany, pp. 35-46, (2007)
[4]  
Bishr M., Janowicz K., Can we trust information? The case of volunteered geographic information. In Proceedings of the workshop “towards digital earth: Search, discover and share geospatial data” at future internet symposium, Berlin, Germany, pp. 11-16, (2010)
[5]  
Bishr M., Mantelas L., A trust and reputation model for filtering and classifying knowledge about urban growth, GeoJournal, 72, 3, pp. 229-237, (2008)
[6]  
Bordogna G., Carrara P., Criscuolo L., Pepe M., Rampini A., A linguistic decision making approach to assess the quality of volunteer geographic information for citizen science, Information Sciences, 258, pp. 312-327, (2014)
[7]  
Bordogna G., Carrara P., Criscuolo L., Pepe M., Rampini A., On predicting and improving the quality of volunteer geographic information projects, International Journal of Digital Earth, pp. 1-22, (2014)
[8]  
Brando C., Bucher B., Quality in user generated spatial content: A matter of specifications. In Proceedings of the 13th AGILE international conference on geographic information science, Guimarães, Portugal, pp. 1-8, (2010)
[9]  
Caha J., Tucek P., Vondrakova A., Paclikova L., Slope analysis of fuzzy surfaces, Transactions in GIS, 16, 5, pp. 649-661, (2012)
[10]  
Carnevale C., Finzi G., Pisoni E., Volta M., Neuro-fuzzy and neural network systems for air quality control, Atmospheric Environment, 43, 31, pp. 4811-4821, (2009)