A Semantic Earth Observation Data Cube for Monitoring Environmental Changes during the Syrian Conflict

Hannah Augustin, Martin Sudmanns, Dirk Tiede, Andrea Baraldi
<span title="">2018</span> <i title="Osterreichische Akademie der Wissenschaften"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fr7biv72rfen5cxwllnb5w4zxe" style="color: black;">GI_FORUM - Journal for Geographic Information Science</a> </i> &nbsp;
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
more &raquo; ... 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. Applicationindependent 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 ongoing conflict and humanitarian demand, paired with the relatively cloud-free climate's suitability for optical EO time-series analysis.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1553/giscience2018_01_s214">doi:10.1553/giscience2018_01_s214</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/opw7tzmgqfcszeyuy6jwtduuby">fatcat:opw7tzmgqfcszeyuy6jwtduuby</a> </span>
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