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Exploring In-Situ Data: Definitions, Sources, and Training Applications

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Exploring In-Situ Data: Definitions, Sources, and Training Applications
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44
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production Year2023
Production PlaceWageningen

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Abstract
In this session a broad introduction to In-situ data and the definitions used was given. It provided an overview of authoritative and non-authoritative data sources, the importance of In-Situ data for training remote sensing deep learning models (showcasing WorldCover and C-GLOPS training data sets, etc.) and other citizen science data (e.g. iNATURALIST etc.). Methods for how in-situ data can be extracted from Mapillay and Streetview were also discussed.
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