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EXPLOITING VOLUNTEERED GEOGRAPHIC INFORMATION TO EASE LAND USE MAPPING OF AN URBAN LANDSCAPE

机译:利用志愿地理信息,缓解城市景观的土地利用映射

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Remote sensing techniques have eased land use/cover mapping substantially by observing the earth remotely through diminishing field surveying and in-site data collection. However, field measurement is still required to identify training sites for defining the existing land use classes, which requires visiting the study area. This paper is intended to utilize volunteered geographic information (VGI) contributions to the OpenStreetMap (OSM) project as an alternative data source instead of gathering training sites through in-site visits and to evaluate how accurate land use patterns can be mapped. High resolution imagery of RapidEye with 5 meter spatial resolution is selected to derive land use patterns of Koblenz, Germany through a maximum likelihood classification technique. The achieved land use map is compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) and a Kappa Index of 89% is achieved. The outcomes prove that VGI can be integrated within remote sensing processes to facilitate the process of earth observation and monitoring.
机译:通过减少现场测量和现场数据收集,遥感技术基本上通过观察地球远程观察地球而缓解了土地使用/覆盖范围。然而,仍然需要现场测量来识别用于定义现有土地使用类的培训站点,这需要访问研究区域。本文旨在利用志愿地理信息(VGI)贡献OpenStreetMap(OSM)项目作为替代数据源,而不是通过现场访问收集培训网站,并评估可以映射准确的土地使用模式。通过最大似然分类技术选择具有5米空间分辨率的Rapideye的高分辨率图像,以获得德国Koblenz的土地利用模式。将达到的土地使用地图与环境和安全城市地图集(GMESUA)的全球监测进行了比较,并且达到89%的Kappa指数。结果证明了VGI可以集成在遥感过程中,以促进地球观察和监测的过程。

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