Analysis-Ready Data from Hyperspectral Sensors—The Design of the EnMAP CARD4L-SR Data Product

Remote Sensing

Martin Bachmann¹  Martin Habermeyer¹  Nicole Pinnel¹  Stefanie Holzwarth¹  David Marshall¹  Raquel de losReyes²  Peter Schwind²  Harald Krawczyk²  Birgit Gerasch²  Emiliano Carmona²  Kevin Alonso²  Tobias Storch²  Mathias Schneider²  Maximilian Langheinrich²  Miguel Pato² 

[1] German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Data Center, Oberpfaffenhofen, 82234 Wessling, Germany;German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Oberpfaffenhofen, 82234 Wessling, Germany;

关键词: EnMAP;    imaging spectrometer;    hyperspectral;    metadata;    analysis ready data;    ARD;   

DOI  :  10.3390/rs13224536

来源: DOAJ

【 摘 要 】

Today, the ground segments of the Landsat and Sentinel missions provide a wealth of well-calibrated, characterized datasets which are already orthorectified and corrected for atmospheric effects. Initiatives such as the CEOS Analysis Ready Data (ARD) propose and ensure guidelines and requirements so that such datasets can readily be used, and interoperability within and between missions is a given. With the increasing availability of data from operational and research-oriented spaceborne hyperspectral sensors such as EnMAP, DESIS and PRISMA, and in preparation for the upcoming global mapping missions CHIME and SBG, the provision of analysis ready hyperspectral data will also be of increasing interest. Within this article, the design of the EnMAP Level 2A Land product is illustrated, highlighting the necessary processing steps for CEOS Analysis Ready Data for Land (CARD4L) compliant data products. This includes an overview of the design of the metadata, quality layers and archiving workflows, the necessary processing chain (system correction, orthorectification and atmospheric correction), as well as the resulting challenges of this procedure. Thanks to this operational approach, the end user will be provided with ARD products including rich metadata and quality information, which can readily be integrated in analysis workflows, and combined with data from other sensors.

【 授权许可】

Unknown