Topographic estimation by terrasar-X

SAR Interferometry (InSAR) is a technique to derive Digital Elevation Model (DEM) from at least two complex SAR images. The data are either taken simultaneously (single-pass mode) or sequentially (repeat-pass mode) by airborne or space-born sensors (carriers: plane, satellite, shuttle etc.). To date, one of the most important single-pass interferometry measurement campaigns is the Shuttle Radar Topography Mission (SRTM) completing its mission successfully after 11 days of operation between 11th and 22nd of February 2000. On the other hand, repeat-pass InSAR has been used by several satellite systems: ENVISAT, ERS 1-2, RADARSAT 1-2, ALOS, JERS-1 etc. One of the most advanced systems is the German TerraSAR-X (TSX) satellite launched on June 15th , 2007. TSX offers high resolution (∼1m by Spotlight mode) imagery which could not been achieved from radar technologies up to this time similar to high resolution optical imagery. In contrast to optical sensors, TSX can be operated under all weather conditions without being influenced by clouds. The data sets provided by TSX newly obtained by scientific community and evaluations are currently being performed. As mentioned above, utilizing the advantages of SAR technology, indeed the planimetric locations of target ground objects, elevations of them can be determined using interferometry. Through the interferometric data, interferograms (fringe maps) can be generated and applying interferometric processing steps height models can be created for large coverage interest areas. The main targets of this investigation can be summarized as; generation of height models derived from TSX InSAR image-pairs and evaluation by comparison with more accurate reference height models as well as height models based on high resolution optical satellite images. Absolute and relative accuracy, stability, homogeneity and dependency upon various parameters are determined. The approach will be demonstrated using TSX data covering Istanbul area, Turkey.TUBITAKDL

A graph based model for the detection of tidal channels using marked point processes

In this paper we propose a new method for the automatic extraction of tidal channels in digital terrain models (DTM) using a sampling approach based on marked point processes. In our model, the tidal channel system is represented by an undirected, acyclic graph. The graph is iteratively generated and fitted to the data using stochastic optimization based on a Reversible Jump Markov Chain Monte Carlo (RJMCMC) sampler and simulated annealing. The nodes of the graph represent junction points of the channel system and the edges straight line segments with a certain width in between. In each sampling step, the current configuration of nodes and edges is modified. The changes are accepted or rejected depending on the probability density function for the configuration which evaluates the conformity of the current status with a pre-defined model for tidal channels. In this model we favour high DTM gradient magnitudes at the edge borders and penalize a graph configuration consisting of non-connected components, overlapping segments and edges with atypical intersection angles. We present the method of our graph based model and show results for lidar data, which serve of a proof of concept of our approach.Ministry of Environment, Energy, and Climate ProtectionMinistry of Science and Culture of Lower Saxon

Hierarchical higher order crf for the classification of airborne lidar point clouds in urban areas

We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next iteration of the point-based layer. This framework iterates and mutually propagates context to improve the classification results. Potentially wrong decisions can be revised at later stages. The output is a labelled point cloud as well as segments roughly corresponding to object instances. Moreover, we present two new contextual features for the segment classification: the distance and the orientation of a segment with respect to the closest road. It is shown that the classification benefits from these features. In our experiments the hierarchical framework improve the overall accuracies by 2.3% on a point-based level and by 3.0% on a segment-based level, respectively, compared to a purely point-based classification

Comparison of three airborne laser bathymetry data sets for monitoring the German Baltic Sea Coast

Airborne laser bathymetry (ALB) can be used for hydrographic surveying with relative high resolution in shallow water. In this paper, we examine the applicability of this technique based on three flight campaigns. These were conducted between 2012 and 2014 close to the island of Poel in the German Baltic Sea. The first data set was acquired by a Riegl VQ-820-G sensor in November 2012. The second and third data sets were acquired by a Chiroptera sensor of Airborne Hydrography AB in September 2013 and May 2014, respectively. We examine the 3D points classified as seabed under different conditions during data acquisition, e.g. the turbidity level of the water and the flight altitude. The analysis comprises the point distribution, point density, and the area coverage in several depth levels. In addition, we determine the vertical accuracy of the 3D seabed points by computing differences to echo sounding data. Finally, the results of the three flight campaigns are compared to each other and analyzed with respect to the different conditions during data acquisition. For each campaign only small differences in elevation between the laser and the echo sounding data set are observed. The ALB results satisfy the requirements of IHO Standards for Hydrographic Surveys (S-44) Order 1b for several depth intervals. © 2015 SPIE

Evaluation of insar dem from high-resolution spaceborne sar data

In recent years a new generation of high-resolution SAR satellites became operational like the Canadian Radarsat-2, the Italian Cosmo/Skymed, and the German TerraSAR-X systems. The spatial resolution of such devices achieves the meter domain or even below. Key products derived from remote sensing imagery are Digital Elevation Models (DEM). Based on SAR data various techniques can be applied for such purpose, for example, Radargrammetry (i.e., SAR Stereo) and SAR Interferometry (InSAR). In the framework of the ISPRS Working Group VII/2 "SAR Interferometry" a long term scientific project is conducted that aims at the validation of DEM derived from data of modern SAR satellite sensors. In this paper, we present DEM results yield for the city of Barcelona which were generated by means of SAR Interferometry.DL

Persistent scatterer aided facade lattice extraction in single airborne optical oblique images

We present a new method to extract patterns of regular facade structures from single optical oblique images. To overcome the missing three-dimensional information we incorporate structural information derived from Persistent Scatter (PS) point cloud data into our method. Single oblique images and PS point clouds have never been combined before and offer promising insights into the compatibility of remotely sensed data of different kinds. Even though the appearance of facades is significantly different, many characteristics of the prominent patterns can be seen in both types of data and can be transferred across the sensor domains. To justify the extraction based on regular facade patterns we show that regular facades appear rather often in typical airborne oblique imagery of urban scenes. The extraction of regular patterns is based on well established tools like cross correlation and is extended by incorporating a module for estimating a window lattice model using a genetic algorithm. Among others the results of our approach can be used to derive a deeper understanding of the emergence of Persistent Scatterers and their fusion with optical imagery. To demonstrate the applicability of the approach we present a concept for data fusion aiming at facade lattices extraction in PS and optical data

Urban building detection from optical and insar features exploiting context

We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to be a valuable method for context-based building detection with multi-sensor features

Matching persistent scatterers to buildings

Persistent Scatterer Interferometry (PSI) is by now a mature technique for the estimation of surface deformation in urban areas. In contrast to the classical interferometry a stack of interferograms is used to minimize the influence of atmospheric disturbances and to select a set of temporarily stable radar targets, the so called Persistent Scatterers (PS). As a result the deformation time series and the height for all identified PS are obtained with high accuracy. The achievable PS density depends thereby on the characteristics of the scene at hand and on the spatial resolution of the used SAR data. This means especially that the location of PS cannot be chosen by the operator and consequently deformation processes of interest may be spatially undersampled and not retrievable from the data. In case of the newly available high resolution SAR data, offering a ground resolution around one metre, the sampling is potentially dense enough to enable a monitoring of single buildings. However, the number of PS to be found on a single building highly depends on its orientation to the viewing direction of the sensor, its facade and roof structure, and also the surrounding buildings. It is thus of major importance to assess the PS density for the buildings in a scene for real world monitoring scenarios. Besides that it is interesting from a scientific point of view to investigate the factors influencing the PS density. In this work, we fuse building outlines (i.e. 2D GIS data) with a geocoded PS point cloud, which consists mainly in estimating and removing a shift between both datasets. After alignment of both datasets, the PS are assigned to buildings, which is in turn used to determine the PS density per building. The resulting map is a helpful tool to investigate the factors influencing PS density at buildings

Phenotyping of N -acetyltransferase type 2 and xanthine oxidase with caffeine: when should urine samples be collected?

Objectives: Individual activities of N-acetyltransferase 2 (NAT2) and of xanthine oxidase (XO) can be assessed using ratios of urinary caffeine metabolites. We investigated how ratios changed over time and which urine collection interval would be the best for NAT2 and XO activity assessments. Methods: On two occasions separated by 14days, 16 healthy male Caucasians collected urine before and 0-2, 2-4, 4-6, 6-8, 8-12, 12-16 and 16-24h after a dose of 150mg caffeine given in the framework of a phenotyping cocktail study. The metabolites 5-acetylamino-6-formylamino-3-methyluracil (AFMU), 5-acetylamino-6-amino-3-methyluracil (AAMU), 1-methylxanthine (1X), and 1-methylurate (1U) were quantified with LC-MS/MS. The molar ratio (AFMU + AAMU)/(1X + 1U + AFMU + AAMU) was used as a NAT2 metric, while the ratio 1U/(1X + 1U) served as XO metric. Results: The NAT2 ratios were stable in the intervals 4-24h after caffeine dosing. Mean intra-individual coefficients of variation were 11-23% starting 4h post-dose, while inter-individual variability reached 37-75%. The XO ratios increased gradually by 14% from the 2-4 to the 16-24h interval. The mean intra- and inter-individual coefficients of variation of XO activity were 3-18 and 7-10% respectively. No significant differences between study occasions were observed. Conclusions: Any sampling interval at least 4h after caffeine dosing is suitable for NAT2 and XO activity assessments. XO activities can only be compared between volunteers and studies if the same urine collection schedule has been respected. The low intraindividual variability allows for sample sizes of 16 and 6 participants in crossover interaction studies of NAT2 and XO activity respectivel

A stereo line matching technique for aerial images based on a pair-wise relation approach

In this study, we developed a new pair-wise relation based approach for the matching of line features from stereo aerial images. To solve the final matching inconsistencies, we propose an iterative pair based post-processing algorithm in which the matching inconsistencies are eliminated using three novel measures and a final similarity voting scheme. The approach is tested over four urban test sites with various built-up characteristics, and for all test sites, we achieved a stereo line matching performance of 98%. The overall results indicate that the proposed approach is highly robust for the line features extracted in (very) dense urban areas