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  • 标题:A Semantic Earth Observation Data Cube for Monitoring Environmental Changes during the Syrian Conflict
  • 本地全文:下载
  • 作者:Hanna Augustin ; Martin Sudmanns ; Dirk Tiede
  • 期刊名称:GI_FORUM - Journal for Geographic Information Science
  • 电子版ISSN:2308-1708
  • 出版年度:2018
  • 卷号:1
  • 页码:214-227
  • DOI:10.1553/giscience2018_01_s214
  • 出版社:ÖAW Verlag, Wien
  • 摘要:Freely and openly available, remotely-sensed Earth observation (EO) data are rapidly developing in terms of increased geo-spatial resolution and temporal frequency. This type of data requires automated workflows for handling, processing and analysis, including methods to convert data into valid information. This study presents a proof-of-concept implementation of a generic, semantic EO data cube with automated daily integration and semantic enrichment of Sentinel-2 data. The paper focuses on the technical implementation of an automated dataflow that enables semantic queries in an EO data cube. It proposes a transferable analytical environment with analysis-ready data to facilitate research on replicable extraction of EO-based indicators. Application-independent semantic data cubes can facilitate monitoring of land cover changes and the development of transferable, generic EO-based indicators to support decision-makers in the humanitarian sector, and international initiatives, such as the United Nations’ Sustainable Development Goals. Syria was chosen as the study area because of the on-going conflict and humanitarian demand, paired with the relatively cloud-free climate’s suitability for optical EO time-series analysis.
  • 关键词:remote sensing; Big Earth Data; data cube; semantic enrichment; reproducible
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