Amaia de Miguel

EnMAP Ground Segment Design: An Overview and Its Hyperspectral Image Processing Chain

EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) is the first German hyperspectral remote sensing satellite mission. This chapter focuses on the challenges on the design of the ground segment as a whole and in particular of its image processing chain. In the context of the system response time we investigate the ability of tilting the satellite which allows for frequent revisits and enables meaningful downstream change detection activities on a global scale. In the context of comparable and high-quality controlled products we investigate in detail the processing steps to radiometrically calibrate, spectrally characterize, geometrically and atmospherically correct the data. The status corresponds to the baseline for the production activities of the ground segment, namely only minor changes are expected. The launch is planned for 2016. The establishment and operation of the ground segment is under responsibility of the Earth Observation Center (EOC) and the German Space Operations Center (GSOC) at the German Aerospace Center (DLR).

On the design of the ground segment for the future hyperspectral satellite mission EnMAP

The ground segment of the future German hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) is developed by the Applied Remote Sensing Cluster and the German Space Operations Center at the German Aerospace Center (DLR). The launch is planned for 2013. This paper describes the EnMAP mission - being currently in its detailed design phase - and focuses first on the analysis of the development approach for the ground segment formed by 15 subsystems. Second the ground segment and subsystems designs themselves with their relations to the space and user segments are detailed.

Texture estimation in sar images: The impact of scale and model order

This paper discusses methods and parameter settings that help to estimate texture in SAR images. In general, this is a difficult task for SAR images that are characterized by speckle noise and which span a wide range of pixel magnitudes. We applied Gauss Markov Random Field (GMRF) models and Enhanced Model Based Despeckling (EMBD) to 1 meter resolution amplitude images of the German TerraSAR-X mission. The results demonstrate that one can find appropriate parameter combinations that allow robust texture estimation even for different types of target areas.