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QOD-May-2023.md

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**Presenters:** Benjamin Jakimow
**Description:**
Satellite missions like [EnMAP](https://www.enmap.org/) and [PRISMA (Cogliati et al., 2021)](https://doi.org/10.1016/j.rse.2021.112499) observe the Earth surface with hyperspectral resolution. The provided imaging spectroscopy data is highly valuable for biophysical, agricultural, geological hydrological applications. This presentation gives an overview on the typical characteristics of such imaging spectroscopy raster data, where to get it for free, and what makes it different to data from satellites like Landsat and Sentinel-2. We show typical problems that QGIS users and developers are confronted with when using imaging spectroscopy data, and how these problems can be solved exemplary using the [EnMAP-Box plugin](https://enmap-box.readthedocs.io). Finally, we discuss conceptional ideas how QGIS in general may be enhanced to better exploit the spectral in multi-, super- and hyperspectral raster data.
Satellite missions like [EnMAP](https://www.enmap.org/) and [PRISMA](https://doi.org/10.1016/j.rse.2021.112499) observe the Earth surface with hyperspectral resolution. The provided imaging spectroscopy data is highly valuable for biophysical, agricultural, geological hydrological applications.
This presentation gives an overview on the typical characteristics of such imaging spectroscopy raster data, where to get it for free, and what makes it different to data from satellites like Landsat and Sentinel-2. We show typical problems that QGIS users and developers are confronted with when using imaging spectroscopy data, and how these problems can be solved exemplary using the [EnMAP-Box](https://enmap-box.readthedocs.io).
Finally, we discuss conceptional ideas how QGIS in general may be enhanced to better exploit the spectral in multi-, super- and hyperspectral raster data.
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