Reconnaissance of coastal areas using simulated EnMAP data in an ERDAS IMAGINE environment

Merlin Becker; Simon Schreiner; Stefan Auer; Daniele Cerra; Peter Gege; Martin Bachmann; Andreas Roitzsch; Uwe Mitschke; Wolfgang Middelmann

doi:10.1117/12.2325402

9 October 2018 Reconnaissance of coastal areas using simulated EnMAP data in an ERDAS IMAGINE environment

Merlin Becker, Simon Schreiner, Stefan Auer, Daniele Cerra, Peter Gege, Martin Bachmann, Andreas Roitzsch, Uwe Mitschke, Wolfgang Middelmann

Author Affiliations +

Proceedings Volume 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX; 107900L (2018) https://doi.org/10.1117/12.2325402
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Operations in a military naval context require a detailed planning and information gathering. For this purpose, remote sensing is a useful technique without in-situ survey. A collaboration of Fraunhofer IOSB (Institute of Optronics, System Technologies and Image Exploitation), DLR (German Aerospace Center), and Bundeswehr Geoinformation Centre ZGeoBw, engineered a desktop Geoinformation (GIS) plug-in to generate bathymetric charts and land-use-classes (vegetation, soil types and minerals) using hyperspectral data of coastal areas. These data are basis for further analyses like trafficability, barrier detection and change detection. To evaluate the potential of satellites launched in the near future with hyperspectral sensors onboard (EnMAP), aerial hyperspectral data (HySpex, AISA) were collected over a test site near the Wismar Bay in Germany and are used to simulate the satellite hyperspectral data with corresponding recording terms. Additionally, a field campaign was conducted at the Wismar Bay to acquire a ground truth dataset for model validation, including soil spectra and water depths as well. For generating the bathymetric charts, the WASI (Water Color Simulator) approach was adapted, which offers additional information besides water depth (e.g. dissolved matter, brightness of sand, relative amount of sea grass and other properties). Resulting bathymetric charts with a depth up to eight meters and unsupervised classifications of land cover are free of artefacts and accurate. A validation process is in progress. The engineered desktop GIS plug-in for HEXAGON ERDAS IMAGINE software was developed using the native SDK in addition with interoperable scripts like Python. The existing plug-in framework is variable and adaptable to different kind of GIS.

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Merlin Becker, Simon Schreiner, Stefan Auer, Daniele Cerra, Peter Gege, Martin Bachmann, Andreas Roitzsch, Uwe Mitschke, and Wolfgang Middelmann "Reconnaissance of coastal areas using simulated EnMAP data in an ERDAS IMAGINE environment", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 107900L (9 October 2018); https://doi.org/10.1117/12.2325402

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