Mathias Schneider

Automated Georeferencing of Optical Satellite Data with Integrated Sensor Model Improvement

The geometric processing of remotely sensed image data is one of the key issues in data interpretation, added value product generation, and multi-source data integration. Although optical satellite data can be orthorectified without the use of Ground Control Points (GCP) to absolute geometric accuracies of some meters up to several hundred meters depending on the satellite mission, there is still a need to improve the geometric accuracy by using GCP. The manual measurement of GCP is time consuming work, and leads, especially for larger data sets with hundreds of satellite images, to a cost and time ineffective workload. To overcome these shortcomings, an autonomous processing chain to georeference and orthorectify optical satellite data is proposed which uses reference data and digital elevation models to generate GCP and to improve sensor model parameters (namely for rigorous and universal sensor models) for a series of optical Earth observation satellite systems. Using a restrictive blunder removal strategy, the proposed procedure leads to high quality orthorectified products or at least to a geometrically consistent data set in terms of relative accuracy. The geometric processing chain is validated using SPOT-4 HRVIR, SPOT-5 HRG, IRS-P6 LISS III, and ALOS AVNIR-2 optical sensor data, for which a huge amount of satellite data (3,200 scenes) has been processed. Relative and absolute geometric accuracies of approximately half the pixel size (linear Root Mean Square Error) are achieved.

Processors for ALOS Optical Data: Deconvolution, DEM Generation, Orthorectification, and Atmospheric Correction

The German Aerospace Center (DLR) is responsible for the development of prototype processors for PRISM and AVNIR-2 data under a contract of the European Space Agency. The PRISM processor comprises the radiometric correction, an optional deconvolution to improve image quality, the generation of a digital elevation model, and orthorectification. The AVNIR-2 processor comprises radiometric correction, orthorectification, and atmospheric correction over land. Here, we present the methodologies applied during these processing steps as well as the results achieved using the processors.

The processing chain and Cal/Val operations of the future hyperspectral satellite mission EnMAP

The German Aerospace Center DLR - namely the Applied Remote Sensing Cluster CAF and the German Space Operations Center GSOC - is responsible for the establishment of the ground segment of the future German hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program). The Applied Remote Sensing Cluster has long lasting experiences with air- and spaceborne acquisition, processing, and analysis of hyperspectral image data. This paper mainly addresses the concept of the operational and automatic processing chain and the calibration/data quality to generate high quality data products.

Matching of high resolution optical data to a shaded DEM

One of the first essential steps in the analysis of satellite imagery is the orthorectification of the images. Orthorectification without ground control points (GCPs) using only the ephemeris and attitude data provided by the satellite operator provides an absolute accuracy of about 20 m to 1 km (depending on the satellite), which can be improved by measuring precise GCPs. In this paper, a method to obtain GCPs from an existing digital elevation model (DEM) is described and assessed. Since at least the SRTM DEM is available worldwide, DEMs could serve as a valuable additional source for the generation of GCPs. Furthermore, several planned and ongoing missions will increase the availability and accuracy of DEMs or stereo imagery respectively, e.g. ALOS, Tandem-X, etc.

ENMAP data product standards

EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) is a German, Earth observing, imaging spectroscopy, spaceborne mission planned for launch in 2017. In order to ensure data product standards during the complete mission lifetime operational workflows are established. These cover all activities for pre- and in-flight spectral, radiometric, and geometric characterization and calibration as well as for the independent product validation of the quality controlled images. Spectral and radiometric calibration of the hyperspectral imager covering the wavelength range from 420 nm to 2450 nm is especially based on satellite onboard sources and a full aperture diffuser. Geometric calibration and validation is based on acquisitions of selected reference sites, but also compared to further ground-truth, air-, and spaceborne missions. Standardized products including geometric and/or atmospheric corrections are generated by a fully-automatic hyperspectral image processing chain.

Orthorectification and DSM generation with ALOS-Prism data in urban areas

In this paper different methods for deriving digital surface models (DSM) from ALOS Prism three line stereo images are generated and analyzed. The methods used are classical hierarchical stereo matching with forward intersection and two different dense stereo methods. These are digital line warping which was derived from speech recognition algorithms and semi global matching which is originating in computer vision. All these dense stereo methods need epipolar imagery as input and provide so called disparity images as output. For this in a first step the Prism images has to be transformed by pairs to epipolar geometry. For the reprojection of the disparity images to real DSMs rational polynomial coefficients - which were computed from the satellite ephemeris and attitude date - are used. Finally the DSMs generated by all these different methods are compared to a DSM derived from an Ikonos stereo image pair with a ground sampling distance of 1 m.

Pre- and in-flight geometric characterization and calibration concepts for the EnMAP mission

The future hyperspectral satellite mission EnMAP (Environmental Mapping and Analysis Program; www.enmap.org) will substantially improve remote sensing standard products and generate new user-driven information products on the status and evolution of different ecosystems. The launch is planned for 2016 with mission operations of five years. This paper describes the EnMAP mission and focuses on the status and challenges of how to achieve the required accuracies in geometric correction which applies the method of direct georeferencing. The pre-flight activities including simulations and measurements complement the initial and routine in-flight activities. The concepts for geometric characterization and calibration are analyzed and how thereby the absolute geo-location accuracy and the co-registration between the two spectrometers are realized in the operational on-ground processing. One spectrometer covers the spectral range from 420 nm to 1000 nm and 900 nm to 2450 nm is covered by the other one.

Using geometric accuracy of TerraSAR-X data for improvement of direct sensor orientation and ortho-rectification of optical sattelite data

The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations. It is due to the fact that it measures distances which are mainly dependent on the position of the satellite and the terrain height. If the used DEM is of high accuracy, the resulting geocoded data are very precise. This precision can be used to improve the exterior orientation and thereby the geometric accuracy of optical satellite data. The technique used is the measurement of identical points in the images, either by manual measurements or through local image matching using mutual information and to estimate improvements for the attitude data through this information. By adjustment calculations falsely matched points can be eliminated and an optimal improvement can be found. The optical data are orthorectified using these improvements and the available DEM. The results are compared using conventional ground control information from GPS measurements.