Supporting environmental monitoring with remote sensing data considerably increases cost effectiveness and reliability of traditional, manual solutions. Additionally, by means of automation, it bears the potential to prevent contaminations or disasters through the availability of timely and spatially dense data. To this end, we investigate the possibility to monitor gas and oil pipelines of a storage cavern by using optical, multi spectral data from the Copernicus Sentinel 2 satellites. Due to a lack of known disasters/contaminations, we resort to a monitoring approach based on statistical outliers. First results demonstrate the general capability of our approach to detect contaminations and generate warnings.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:34497 |
| Date | 16 July 2019 |
| Creators | Köhler, Christian |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-3-938390-23-8, urn:nbn:de:bsz:105-qucosa2-344551, qucosa:34455 |
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