Andreas Schenk

Delineation of Urban Footprints From TerraSAR-X Data by Analyzing Speckle Characteristics and Intensity Information

With a spatial resolution of up to 1 m, the German radar satellite TerraSAR-X (TSX) has significantly increased the usability of spaceborne synthetic aperture radar (SAR) imagery in the context of urban applications. This paper presents an approach toward the semiautomated detection of built-up areas (BAs) based on single-polarized TSX images. The proposed methodology includes a specific preprocessing of the SAR data and an automated image analysis procedure. The preprocessing focuses on the analysis of local speckle characteristics in order to provide a texture layer that highlights BAs. In the context of an object-oriented image analysis, this texture layer is used along with the original intensity information to automatically extract settlements. The technique is tested on the basis of 12 TSX scenes covering representative urban agglomerations distributed throughout the world. Overall, accuracies between 76% and 96% for the derived city footprints demonstrate the high potential of both the TSX imagery and the proposed analysis approach in detecting BAs. In order to demonstrate the robustness and transferability of the image analysis concept, we finally transferred the classification strategy from the object-oriented domain to a more general and simplified pixel-based approach.

Land subsidence in Iran caused by widespread water reservoir overexploitation

[1] The increasing demands upon groundwater resources due to expanding metropolitan and agricultural areas are a serious challenge, particularly in semiarid and arid regions. In Iran, decades of unrestrained groundwater extraction for domestic, agricultural, and industrial use have resulted in a precipitous depletion of this valuable resource. Here we show that the decline in groundwater levels is associated with land-surface deformation on local and regional scales. Combining water-level data with satellite radar observations provides evidence for the prevalence of compacting aquifers in the country. Groundwater level decline is often associated with destruction of the aquifers, which appears to be a common problem in the groundwater basins of central and northeast Iran. Global warming and future climate change will affect arid and semiarid areas in the coming decades, further augmenting hazards associated with groundwater-induced land subsidence.

Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information

The appearance of objects and surfaces in synthetic aperture radar (SAR) images significantly differs from the human perception of the environment. In addition, the quality of SAR data is degraded by speckle noise, superposing the true radiometric and textural information of the radar image. Hence, the interpretation of SAR images is considered to be more challenging compared to the analysis of optical data. However, in this paper, we demonstrate how information on the local development of speckle can be used for the differentiation of basic land cover (LC) types in a single-polarized SAR image. For that purpose, we specify the speckle characteristics of the following LC types: 1) water; 2) open land (farmland, grassland, bare soil); 3) woodland; and 4) urban area by means of an unsupervised analysis of scatter plots and standardized histograms of the local coefficient of variation. Next, we use this information for the implementation of a straightforward preclassification of single-polarized TerraSAR-X stripmap images by combining information on the local speckle behavior and local backscatter intensity. The output is either provided as a discrete classification or as a color composite image whose bands can be interpreted in terms of a fuzzy classification. The results of this paper show that unsupervised speckle analysis in high-resolution SAR images supplies valuable information for a differentiation of the water, open land, woodland, and urban area LC types. While the color composite image supports the visual interpretation of SAR data, the outcome of the fully automated discrete LC classification procedure represents a valuable preclassification image, showing overall accuracies of 77%-86%.

Land cover classification based on single-polarized VHR SAR images using texture information derived via speckle analysis

Speckle is a SAR specific noise effect caused by constructive and destructive interference from multiple scattering within the resolution cell of the imaging radar system that superposes the true radiometric and textural information of SAR images as a grainy ‘salt-and-pepper’ pattern. Fully developed speckle basically follows circular Gaussian image statistics. However, this assumption is not applicable for very high resolution SAR systems and for data showing sceneries with a significant amount of directional backscatter — e.g. urban areas. In those cases the multiple scattering processes within a resolution cell show - subject to the true structuring of the imaged area — rather a directional behavior than a random distribution. Consequently, the speckle is no longer fully developed. In our study we demonstrate how information on the local development of speckle can be used to differentiate between basic land cover types such as water, open land — meaning farmland, grassland and bare soil —, woodland and urban area in single-polarized, single-date VHR SAR images. The research is based on the analysis of a TerraSAR-X scene of Munich, Germany.

Integration of InSAR and GNSS Observations for the Determination of Atmospheric Water Vapour

High spatially and temporally variable atmospheric water vapour causes an unknown delay in microwave signals transmitted by space-borne sensors. This delay is considered as a major limitation in Interferometric Synthetic Aperture Radar (InSAR) applications as well as high-precision applications of Global Navigation Satellite Systems (GNSS). On the other hand, the delay could be quantified to derive atmospheric parameters such as water vapour. Temporal variability of water vapour is well estimated from ongoing GNSS measurements, while InSAR provides information about the spatial variations of water vapour. This project aims at assimilating InSAR phase observations and spatially-sparse GNSS measurements for the determination of atmospheric water vapour. In this contribution GNSS-based water vapour calculations and assessment of different strategies are presented. Work in progress is also reported including some preliminary results.

Visual analytics for persistent scatterer interferometry: first steps and future challenges

In this paper, we introduce persistent scatterer interferometry (PSI) as a new and promising application domain for Visual Analytics (VA). PSI studies changes of the Earths topography by analyzing large time-varying point clouds that easily comprise hundreds of millions of data points. We briefly outline the PSI analysis workflow and present a VA approach to the first step in this workflow based on a flexible and interactive filtering mechanism. We further describe challenges for VA in PSI analysis. We want to engage the VA community in a discussion about potential VA solutions because we expect these solutions to not only advance PSI analysis but also provide valuable insights and contributions for the VA community regarding exploration and analysis of spatiotemporal data.

An Inventory of Surface Movements in the Upper Rhine Graben Area, Southwest Germany, from SAR-Interferometry, GNSS and Precise Levelling

Recent surface movements in the Upper Rhine Graben (URG) area are investigated with geodetic techniques. Line of sight (LOS) displacement rates from SAR interferometry (InSAR), horizontal and vertical rates from coordinate time series of permanent GNSS sites and vertical rates from precise levelling measurements are estimated with high accuracy. We show that the data sets are capable of providing detailed insight into the current movements in the URG area, which is required for a better understanding of geodynamic processes as well as for a reasonable exploitation of geopotentials in the URG. This paper focusses on a comparison of results from InSAR and levelling on a regional and on a local scale. A case study highlights temporal differences in the deformation characteristics of an oil extraction area detected from ERS-1/2 and Envisat data as well as from levelling measurements in multiple epochs. In order to benefit from the advantages of each technique, our work aims on a proper combination to consistently link the different observation methods in a rigorous multi-technique approach.