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来源类型Article
规范类型其他
DOI10.1016/j.techfore.2015.03.002
Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki.
See L; Fritz S; Perger C; Schill C; McCallum I; Schepaschenko D; Dürauer M; Sturn T
发表日期2015
出处Technological Forecasting and Social Change 98: 324-335
出版年2015
语种英语
摘要Information about land cover and land use is needed for a wide range of applications such as nature protection and biodiversity, forest and water management, urban and transport planning, natural hazard prevention and mitigation, monitoring of agricultural policies and economic land use modelling. A number of different remotely-sensed global land cover products are available but studies have shown that there are large spatial discrepancies between these different products when compared. To address this issue of land cover uncertainty, a tool called Geo-Wiki was developed, which integrates online and mobile applications, high resolution satellite imagery available from Google Earth, and data collection through crowdsourcing as a mechanism for validating and improving globally relevant spatial information on land cover and land use. Through its growing network of volunteers and a number of successful data collection campaigns, almost 5 million samples of land cover and land use have been collected at many locations around the globe. This paper provides an overview of the main features of Geo-Wiki, and then using a series of examples, illustrates how the crowdsourced data collected through Geo-Wiki have been used to improve information on land cover and land use.
主题Ecosystems Services and Management (ESM)
关键词land cover land use crowdsourcing volunteered graphic information validation
URLhttp://pure.iiasa.ac.at/id/eprint/11389/
来源智库International Institute for Applied Systems Analysis (Austria)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/130146
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See L,Fritz S,Perger C,et al. Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki.. 2015.
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