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State of the Art Open Access Remote Sensing with ESA Sentinel 1 SAR Data

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dc.contributor.authorMcClelland, Jennifer
dc.contributor.authorRiedel, Tanja
dc.contributor.authorBeyer, Florian
dc.contributor.authorGerighausen, Heike
dc.contributor.authorGolla, Burkhard
dc.contributor.editorKlein, Maike
dc.contributor.editorKrupka, Daniel
dc.contributor.editorWinter, Cornelia
dc.contributor.editorWohlgemuth, Volker
dc.date.accessioned2023-11-29T14:50:19Z
dc.date.available2023-11-29T14:50:19Z
dc.date.issued2023
dc.description.abstractTackling the consequences of climate change has become a global issue. Climate change will clearly influence our common lifestyle enormously in near future. This involves increasingly frequent sudden weather changes and extreme temperatures as well as drastic changes in water quality and availability. Because of our constant growing global population, nutritional habits and agricultural practices, the share of the agricultural impact on global anthropogenic greenhouse gas emissions take on an estimated 10-12 %. At the same time, fulfilling the agricultural demand is becoming increasingly challenging due to unpredictable farming conditions. Without immediate collaborative efforts including focused research, employment and adaption of state of the art technologies, this issue will not be tackled soon enough, to avoid massive limitations and enormous losses. A very promising large-scale technology to monitor agricultural ecosystems and activities is by means of earth observation imagery derived by Synthetic Aperture Radar (SAR). Radar backscatter e.g. allows insights to crop conditions, soil properties and direct mapping of vegetation growth. Open access technologies offer the best solutions for collaborative efforts, thus minimising financial and legal constraints in comparison to technologies residing in the commercial sector. Here, we combine and build on state-of-the-art tools and technologies to provide an easy to employ Sentinel-1 SAR pre-processing tool as well as a Germany wide, open access, pre-processed, analysis- ready database of Sentinel-1 SAR data. All tools used and developed are open source and freely available. With the employment of modern software developing methods and tools for a scalable and maintainable architecture, these products can be easily extended and adapted. By deployment of up to date machine learning methods, combining the resulting datasets with other relevant parameters, not to say the least, e.g. early prediction of optimal sowing, harvesting and fertilisation time points can be determined as well as many more valuable insights for successful, resource-efficient and environmentally friendly farming. Furthermore, the pre-processing of SAR datasets is not only substantial for the field of agriculture but for a wide range of other fields concerning environmental observations.en
dc.identifier.doi10.18420/inf2023_131
dc.identifier.isbn978-3-88579-731-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43054
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2023 - Designing Futures: Zukünfte gestalten
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-337
dc.subjectSentinel-1 SAR
dc.subjectAnalysis ready data
dc.subjectAgriculture
dc.subjectOpen access technologies
dc.subjectGeoinformation systems
dc.titleState of the Art Open Access Remote Sensing with ESA Sentinel 1 SAR Dataen
dc.typeText/Conference Paper
gi.citation.endPage1219
gi.citation.publisherPlaceBonn
gi.citation.startPage1207
gi.conference.date26.-29. September 2023
gi.conference.locationBerlin
gi.conference.sessiontitleÖkologische Nachhaltigkeit - Umweltinformatik zur Gestaltung einer nachhaltigen Zukunft

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P337 - INFORMATIK 2023 - Designing Futures: Zukünfte gestalten