The European Union’s efforts towards technological sovereignty in High-Performance Computing are driving research and development of RISC-V-based supercomputers. The DARE SGA1 project, in particular, aims to develop chips designed and owned by Europeans. This paper introduces the Italian contribution to DARE SGA1 regarding pathfinding activities toward future RISC-V-based accelerator designs, reliability improvements, system software, and AI and Quantum Chemistry applications.

NET4EXA aims to develop a next-generation high-performance interconnect for HPC and AI systems, addressing the increasing demands of large-scale infrastructures, such as those required for training Large Language Models. Building upon the proven BXI (Bull eXascale Interconnect) European technology used in TOP15 supercomputers, NET4EXA will deliver the new BXI release, BXIv3, a complete hardware and software interconnect solution, including switch and network interface components. The project will integrate a fully functional pilot system at TRL 8, ready for deployment into upcoming exascale and post-exascale systems from 2025 onward. Leveraging prior research from European initiatives like RED-SEA, the previous achievements of consortium partners and over 20 years of expertise from BULL, NET4EXA also lays the groundwork for the future generation of BXI, BXIv4, providing analysis and preliminary design. The project will use a hybrid development and co-design approach, combining commercial switch technology with custom IP and FPGA-based NICs. Performances of NET4EXA BXIv3 interconnect will be evaluated using a broad portfolio of benchmarks, scientific scalable applications, and AI workloads.

The APEnet project is an established initiative aimed at designing interconnection boards based on FPGAs and tailored for use in HPC clusters whose nodes are arranged in a 3D toroidal network topology. Based on a custom communication protocol and network IPs, deployments of an APEnet Network Interface Card (NIC) can be configured for different operating environments. In this work, we describe APEnetX, the latest version of network architecture in the APEnet family, developed on Alveo U200 boards which leverage the 16 nm technology devices in the Ultrascale+ line by Xilinx. APEnetX features a PCIe Gen3×16 interface driven by the Queue Direct Memory Access (QDMA) Xilinx IP and adheres to the RDMA semantics, ensuring efficient high bandwidth data transfer without the involvement of the host operating system. The communication between adjacent nodes is handled through a proprietary lightweight protocol and enabled by the high-speed serial embedded transceivers of the FPGA, while a custom full crossbar switch and an optimized router allow for the implementation of a direct torus topology. Together with a proprietary software driver, a low level communication library and a dedicated MPI library, APEnetX lines up with current application standards in HPC systems. In addition, the release of an APEnetX network simulator allows for testing network functionalities at large scale. The achievement of this work is twofold: we enhance the performance of the previous APE net cards reaching 2 µs user-level latency over the PCIe for small packet transmission between topologically adjacent host nodes; we define the requirements of the communication generated by a reference spiking neural network simulator (NEST) to drive the co-design of future APE net generation.

The TEXTAROSSA project aims to bridge the technology gaps that exascale computing systems will face in the near future in order to overcome their performance and energy efficiency challenges. This project provides solutions for improved energy efficiency and thermal control, seamless integration of heterogeneous accelerators in HPC multi-node platforms, and new arithmetic methods. Challenges are tacked through a co-design approach to heterogeneous HPC solutions, supported by the integration and extension of HW and SW IPs, programming models, and tools derived from European research.

A novel methodology for detecting anomalous deformation behaviour from satellite-Synthetic Aperture Radar Interferometry (InSAR) is proposed. The representation of InSAR metadata as embeddings within a deep learning framework (EE-DL) is investigated for modelling the spatio-temporal deformation response. To evaluate the performance of the EE-DL approach in SAR interferometry, we conduct experiments over a mining test site (Cadia, Australia) which has been subject to a tailings storage facility failure. This study demonstrates that EE-DL can detect and predict the fine spatial movement patterns that eventually resulted in the failure. We also compare the results with deformation predictions from a common baseline model, Random Forest.

Landslides can be deadly natural disaster events, particularly in Nepal, where large earthquakes along the India-Asian collision zone and intense Monsoon rainfall can trigger widespread landslides. The complex nature of the landslide causal chain makes it difficult to predict these events, and existing derivations of the link between precipitation thresholds and landslides oversimplify the relationship, do not provide predictive abilities, and therefore limit their usefulness in disaster preparedness. This paper proposes to utilize the power of Machine Learning (ML) and Deep Learning (DL) Artificial Intelligence (AI) techniques with open-source, space-based data, to predict landslides at the District-level in Nepal at 7-, 10-, and 14-day temporal resolutions, using calibrated precipitation estimates and geomorphic data as input. Results provide both scientific insight via feature importance analysis, and a strong predictive capability of landslide prediction in Nepal using Random Forest and U-Net models.

As the so-called "developing" world marches rapidly forward on the paths of urban expansion, Henri Lefebvre’s hypothesis of planetary urbanisation seems increasingly inevitable. However, this article demonstrates, through the first remote sensing analysis of an informal urban agricultural practice dubbed chengshi kaihuang (urban homesteading), that the massive urbanisation of the rural can create a bottom-up countermovement that ruralizes the urban and in doing so assert significant ecological and social alterations to Western conceptions of urbanism. Taking Wuhan as the study area, this paper leverages optical remote sensing data from the Sentinel-2 and Landsat-8 missions in conjunction with open access LU/LC products to study the spatial, temporal, and ecological dynamics of urban homesteading. Through machine learning techniques, the study shows that urban homesteading has constituted ~5% of Wuhan’s urban center since 2017. This paper is one of the first in-depth studies of urban homesteading, and the first to leverage remote sensing techniques.

Ground deformation measurements from Synthetic Aperture Radar Interferometry (InSAR) and ground-based prism mon-itoring are compared to Finite Element (FE) simulation over a collapsed tailings dam. InSAR monitoring captured the complex spatial and temporal variability of TSF deformation that is not be possible from the sparse measurements offered by traditional monitoring. Potentially anomalous deformation over the failed area have been detected from InSAR one year before the failure. The InSAR monitoring data and FE modelling results were in broad agreement with ground based prism measurements, both in terms of magnitude and trends. The results, however, deviate significantly immediately pre-ceding the failure, associated to the construction of buttresses. Finally, this study illustrates the complementarity of remote sensing and geotechnical approaches for the monitoring of tailings dams.

Detailed and complete data on physical assets are required in order to adequately assess environment-related risk and impact exposure and the diffusion of these risks and impacts through the financial system. Investors need to know where the physical assets (e.g., power plant, factory, farm) are located of companies in their portfolios, and what their polluting characteristics are. This is essential to manage these environment-related risks and to channel investments to more sustainable alternatives. At present, data on physical assets is typically incomplete, inaccurate, or not released in a timely manner. As a result, key stakeholders including asset owners, asset managers, regulators and policymakers are frequently forced to make crucial decisions with incomplete information. Accurate and comprehensive global asset-level databases are a prerequisite for meaningful innovation in green and digital finance. They provide the link between the financial system and the “real economy” and allows the wealth of EO datasets and insights that we have available to be made actionable for sustainable finance decision making. We created a framework to derive a global database of pollutant plants, such as cement, iron, and steel, which represent about 15% of the global CO2 emissions. Our solution makes use of state-of-the-art deep learning architectures coupled with Earth observation data.

This article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge's own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies.

The NovaSAR mission successfully started on the 16 September 2018 with the launch of NovaSAR-1, a S-band spaceborne Synthetic Aperture Radar (SAR). This paper provides an overview of the sensor capabilities and describes the approach taken for the construction of its background mission.

Widespread deterioration of ageing infrastructure and the recent collapses of bridge structures highlight the vital importance of structural health monitoring. Satellite Interferometric Synthetic Aperture Radar (InSAR) provides remote measurements at millimetre scale over large areas, but the interpretation of such data into civil engineering contexts remains more than a trivial task. This work presents the monitoring of Waterloo Bridge to investigate the potential for InSAR to be used to support bridge management activities. Corner reflectors and target prisms for automated total station measurements have been installed at key points of interest as part of a wider structural monitoring system, and displacement data from traditional and satellite monitoring systems are compared and studied.

This paper presents an overview of a large research project involving collaboration from the government, academia and industry on lithium (Li) exploration in South-West Cornwall, UK. Scope of the study is to assess the utility of remote sensing technologies in the mining sector, with a particular focus on lithium. A wide range of datasets (including multispectral and Synthetic Aperture Radar (SAR)) are used to delineate the various steps of the project. The ultimate aims are the generation of a map with the probability of lithium occurrence and a complementary environmental baseline study. For the first aim, geological and vegetation anomalies maps indicating proxies for the presence of lithium, derived from multi- and hyperspectral data, and fault lines, derived from SAR imagery, are integrated with in-situ data and a ground-based campaign. The second aim involves the generation of a high-resolution land cover classification and a historical time series analysis to provide an environmental baseline study for the assessment of the impact of mining activities.

Failure of bridges due to scour is of great concern to bridge asset owners, and is currently very difficult to predict and monitor regularly using conventional assessment methods. This paper presents evidence of how InSAR techniques can be used to monitor bridges at risk of scour, using Tadcaster Bridge, England, as a case study. Tadcaster Bridge suffered a partial collapse due to river scour on the evening of December 29th, 2015 following a period of severe rainfall and flooding. SAR scenes over the bridge from the two-year period prior to the collapse are analysed using SBAS interferometry methods, highlighting a distinct movement in the region of the bridge where the collapse occurred prior to the actual event. This precursor to failure observed in the data suggests the possible use of InSAR in structural health monitoring of bridges at risk of scour, as a means of an early warning system.

To access the valuable information contained within Earth observation data, users are required to undertake a series of complex pre-processing steps to turn the data from a `raw' unprocessed format into a state that can be analysed. In a move to remove barriers to accessing Earth observation datasets the concept of ARD has been proposed to improve opportunities for exploitation. This paper seeks to explore whether true interoperability can be achieved for Sentinel 1 ARD through application of a standardised set of pre-processing steps.

This paper presents a nonlocal interferometric synthetic aperture radar (InSAR) filter with the goal of generating digital elevation models (DEMs) of higher resolution and accuracy from bistatic TanDEM-X strip map interferograms than with the processing chain used in production. The currently employed boxcar multilooking filter naturally decreases the resolution and has inherent limitations on what level of noise reduction can be achieved. The proposed filter is specifically designed to account for the inherent diversity of natural terrain by setting several filtering parameters adaptively. In particular, it considers the local fringe frequency and scene heterogeneity, ensuring proper denoising of interferograms with considerable underlying topography as well as urban areas. A comparison using synthetic and TanDEM-X bistatic strip map data sets with existing InSAR filters shows the effectiveness of the proposed techniques, most of which could readily be integrated into existing nonlocal filters. The resulting DEMs outclass the ones produced with the existing global TanDEM-X DEM processing chain by effectively increasing the resolution from 12 to 6 m and lowering the noise level by roughly a factor of two.

We investigate the feasibility of generating highly accurate digital elevation models (DEM) from TanDEM-X interferograms by using nonlocal filters for phase denoising. Some of the shortcomings of existing nonlocal filters that render them not applicable to our goal are briefly described and a new filter is proposed that alleviates these problems. The most significant new properties are addressing the slope dependent denoising performance of existing nonlocal InSAR filters and several measures to bolster denoising near edgelike features. We evaluate the proposed filter using synthetic interferograms and by visual inspection of a DEM generated from a TanDEM-X interferogram.

Space-borne interferometric SAR has advanced significantly in the last decades, with many successful Earth monitoring applications. The key point of this success lies in the fact that interferometric SAR supplies unprecedented phase and amplitude information characterizing target's physical parameters. This paper presents the role of interferometric SAR, specifically considering the bistatic mission TanDEM-X, for shallow lake water level estimation by using sediment storage.

This paper presents the first results generated with the TanDEM-X mission for the monitoring of the topographical changes caused by the series of earthquakes that hit central Italy between summer and autumn 2016. For the purpose, two 300 km long data takes acquired between the Tyrrhenian and the Adriatic coasts and covering the October, 30, earthquake epicenter location have been considered. The takes have an about 5 years' temporal baseline, thus helpful to reveal the large and small scale terrain changes occurred after the 2016 seismic events.

This paper reports a study aimed to detect changes at the northern part of the Vatnajökull glacier, Iceland, by exploiting a stack of Digital Elevation Models (DEMs) generated with Synthetic Aperture Radar (SAR) imagery. The stack is covering the Bardarbunga volcanic system, subject to large topographical variations during the 2014-2015 eruption. In particular, the collapse of the caldera and the restructuring of the glacier, with for instance the formation of new cauldrons, is well represented by the DEM stack, and a quantitative and a geophysical analysis of the results becomes feasible.

The results of a two-year precision agriculture project have clearly demonstrated that TanDEM-X can successfully classify crops morphology through cultivation period. It has been found that TanDEM-X mission is capable of tracking the crop height, and the accuracy of the height estimation depends on the crop morphology, which causes a diversity between canopy top and acquisition phase center. In this work, in addition to interferometry with single polarized channels, polarimetric-interferometric acquisitions have been employed to figure out phase center diversity. The analysis showed that there is a diversity between height estimations from HH and VV polarized interferometric channels, which can reach to 10 cm in the reproductive stages of the crops.

The TanDEM-X satellite mission through its bistatic formation provides high horizontal and vertical resolution topographic data. Multi temporal TanDEM-X acquisitions allow short term analysis of variations of the earth surface elevation which in turn can be converted to volume changes. We are investigating the capabilities of the TanDEM-X data to detect and map short term changes at glacier surfaces in two different situations. One study case is Jorge Montt outlet glacier of the South Patagonia Icefield known for its accelerated mass depletion and front retreat. The second example is located on the Vatnajökull Ice Cap in Iceland and is related to the activity of the Bárǒarbunga volcanic system in summer 2014 as a consequence of climate driven depletion as well as due to volcanic activities below the ice surface.

SAR interferometry is a well-known technique to produce digital surface models (DSM). In the global scale, the quality of these models significantly increased with the use of bistatic systems as for the TanDEM-X mission. DSM uncertainty can be measured in two scales: a global and a local one. A global scale analysis involves measures for the complete take, characterizing the whole correctness with a single parameter. A local scale analysis enters instead in the single elevation model cell, evaluating the quality obtained by different terrains and media present in the take. A coherence analysis is a typical measure for InSAR models. Globally, a simple average gives an overall quality measure hint. Locally, it provides a measure of the DSM pixel height error. Unfortunately, this measure lacks in several aspects as not considering unwrapping errors and not being valid for certain types of scattering. In this paper, various strategies for assessing elevation accuracy methods and demonstrate the different capabilities of the bistatic TanDEM-X system are proposed for variegated terrain types.

In this letter, the suitability of alternating bistatic (AB) TanDEM-X data for tomographic processing is demonstrated. The AB acquisition mode allows to acquire data from three different phase centers at the same time by means of a single pass of the TSX-1 and TDX-1 satellites. The channels of an AB acquisition present no temporal decorrelation within them. In addition, the atmospheric delay can be considered equal for all the channels. This letter analyzes the use of a single acquisition in the AB mode for tomographic processing. The theoretical analysis and the experimental result show that it is possible to separate different scattering mechanisms within a resolution cell under certain constraints.

It has been recently shown that the TanDEM-X mission is capable of tracking the plant growth of rice paddies. The precision of the elevation measure depends on the physical interaction between the synthetic aperture radar (SAR) signal and the canopy. In this letter, this interaction is studied by considering the signal polarization. In particular, the vertical and horizontal wave polarizations are compared, and their performance in the temporal mapping of the crop height is analyzed. The temporal elevation difference analysis shows a monotonically increasing trend within the reproductive stage of the canopy, with maximum height discrepancies between polarizations of about 9 cm. From an operational point of view of InSAR-based vegetation height measurements, this letter demonstrates that the oriented structure of the canopy shall be considered not only in polarimetric InSAR studies but also in the interpretation of bistatic spaceborne interferometric elevation models.

This paper evaluates the potential of spaceborne bistatic interferometric synthetic aperture radar images for the monitoring of biophysical variables in wetlands, with a special interest on paddy rice. The assessment is made during the rice cultivation period, from transplanting to harvesting time (May to October) for fields around Gala lake (Turkey), one of the largest and most productive paddy rice planting area in the country. Detailed ground truth measurements describing biophysical parameters are collected in a dedicated campaign. A stack of 16 dual-pol TanDEM-X images is used for the generation of 32 digital elevation models (DEMs) over the studied area. The quality of the data allows the use of the interferometric phase as a state variable capable to estimate crop heights for almost all the growing stages. The early vegetative rice stage, which is characterized by flooded fields, cannot be represented by the interferometric phase due to a low signal-to-noise ratio but can be easily detected by amplitude and interferometric coherence thresholding. A study on the impact of the polarization in the signal backscatter is also performed. An analysis of the differences between HH and VV DEMs shows the varying signal penetration for the two polarizations at different growing stages. The validation with reference data demonstrates the capability to establish a direct relationship between interferometric phase and rice growth. The very high coherence of TanDEM-X data yields elevation estimates with root-mean-square error in a decimetric level, supporting temporal change analysis on a field-by-field basis.

Layover affects the quality of urban interferometric synthetic aperture radar (InSAR) digital elevation models. Moreover, it is generally difficult to interpret because of the superposition of several contributions in a single SAR pixel. In this paper, a novel technique for the extraction of building layovers is first presented. It makes use of the geocoding stage embedded in the InSAR processor. It is shown that building layovers create a regular pattern in the mapping counter, a map describing the number of occurrences of a SAR pixel in the elevation model. Its exploitation yields a generation of a layover map without the use of external supports. The integration in the processor with a limited additional computational load and the capability to isolate layover signatures are additional benefits. Layover patches are then individually analyzed toward a better understanding of the complex urban signal return. A spectral estimation framework is employed to assess the slopes superimposed in the patches. Fringe-frequency estimation is involved. A set of simulations made for a nonparametric (fast Fourier transform) and a parametric (multiple signal classification) technique is performed prior to testing on real data. It is demonstrated that in X-band, for a single interferogram, just one layover contributor, when it dominates over the others, can be extracted with a sufficient accuracy. The algorithms are tested on a TanDEM-X spotlight acquisition over Berlin (Germany).

This paper deals with the fusion of TanDEM-X raw DEMs in ascending and descending pass over Mumbai test area and enhance its quality. Before applying fusion method, a robust layover and shadow map has been calculated in ITP using TanDEM-X DEM and the corresponding slant range image. The selection of optimum weights for fusion has been based on height error map calculated from interferometric coherence. Results show a substantial reduction in number of invalid pixels after fusion. In the fused DEM, invalid is only 1.2%, while ascending and descending pass DEMs have 6.7% and 5.7% respectively. The improvement in accuracy of the DEM is very slight in this case which is due to the coarse resolution of the SRTM DEM used as reference.

Paddy rice is a staple food that feeds more than half of the world's population. As such, monitoring paddy rice with Synthetic Aperture Radar (SAR) image is a critical area of research. Many possible measures of rice growth as canopy height, LAI, biomass and etc. are considered in the previous works. Among them, canopy height is the most direct measurement and has direct relationship with growth rate. In this study, to monitor paddy rice fields canopy heights are estimated by SAR images containing phase and amplitude information. These two inherent properties of SAR images are examined to retrieve canopy height by a canopy scattering and by a differential interferometric method at X-band. Accuracy analysis showed that differential interferometric technique gives very precise results in terms of canopy height if the canopy is fresh. However, in the case of dry canopy layer, the X-band canopy backscattering model gives much more precise results than the interferometric method as the X-band radar signals penetrate more into canopy in dry case. Even though interferometric techniques do not give detailed information about the physical structure of the canopy as backscattering model do, in this work it is shown that they can be used in operational monitoring.

A strategy to evaluate rice plant growth from TanDEM-X data is assessed in this paper. Single fields are segmented exploiting their early vegetative stage, when they are flooded. Height is then extracted from the bistatic interferometric phase in a field-by-field basis and temporal change maps useful to production estimation are generated. The accuracy of the plant height estimation is in a decimetric level.

Spectral estimation is considered in the paper as an additional instrument towards a better understanding of the physical phenomena behind the layover scattering decomposition. A super-resolution technique is employed to derive the fringe frequencies characterizing the layover portion. Due to the limited estimation support, only the dominant frequency is found to be reliable information. The non-linear relationship with slopes is employed to derive a principal slope map. A bistatic interferometric scenario is tested. It is found that for the majority of the detections the facade contribution is the prevailing one due to the presence of targets with a high backscattered signal return at the vertical slope. The number of layover contributors is assessed prior to the spectral estimation. It has been estimated that the signal return is dominated by a single contribution for the majority of the layovers.

All existing examples of current measurements by spaceborne synthetic aperture radar (SAR) along-track (AT) interferometry (ATI) have suffered from short baselines and corresponding low sensitivities. Theoretically, the best data quality at X-band is expected at effective baselines on the order of 30 m, i.e., 30 times as long as the baselines of the divided-antenna modes of TerraSAR-X. In early 2012, we had a first opportunity to obtain data at near-optimum baselines from the TanDEM-X satellite formation. In this paper, we analyze two TanDEM-X interferograms acquired over the Pentland Firth (Scotland) with effective AT baselines of 25 and 40 m. For comparison, we consider a TerraSAR-X dual-receive-antenna (DRA)-mode interferogram with an effective baseline of 1.15 m, as well as velocity fields obtained by Doppler centroid analysis (DCA) of single-antenna data from the same three scenes. We show that currents derived from the TanDEM-X interferograms have a residual noise level of 0.1 m/s at an effective resolution of about 33 m × 33 m, while DRA-mode data must be averaged over 1000 m × 1000 m to reach the same level of accuracy. A comparison with reference currents from a 1-km resolution numerical tide computation system shows good agreement in all three cases. The DCA-based currents are found to be less accurate than the ATI-based ones but close to short-baseline ATI results in quality. We conclude that DCA is a considerable alternative to divided-antenna mode ATI, while our TanDEM-X results demonstrate the true potential of the ATI technique at near-optimum baselines.

The aim of this work is to show two possible applications for Alternating Bistatic TanDEM-X data. The first application is a tomographic processing while the second is a 2D ship velocity estimation. Results over real data are presented for both applications.

In this paper we present two new algorithms designed to reduce the overall time required to process top-k queries. These algorithms are based on the document-at-a-time approach and modify the best baseline we found in the literature, Blockmax WAND (BMW), to take advantage of a two-tiered index, in which the first tier is a small index containing only the higher impact entries of each inverted list. This small index is used to pre-process the query before accessing a larger index in the second tier, resulting in considerable speeding up the whole process. The first algorithm we propose, named BMW-CS, achieves higher performance, but may result in small changes in the top results provided in the final ranking. The second algorithm, named BMW-t, preserves the top results and, while slower than BMW-CS, it is faster than BMW. In our experiments, BMW-CS was more than 40 times faster than BMW when computing top 10 results, and, while it does not guarantee preserving the top results, it preserved all ranking results evaluated at this level.

Our paper reports about temporal changes of the Earth's topography found in first samples of TanDEM-X data when compared to SRTM Digital Elevation Models collected ten years earlier. We give an accuracy prediction and explain the methods to avoid systematic errors from biases and phase unwrapping ambiguities. Our paper provides examples from different Earth surface domains such as glaciers, volcanoes, mining activity and urban areas. We demonstrate and conclude that the higher the resolution of a DEM gets, the more frequent updates are required to keep the DEM valid with time.

Started in June 2010, the TanDEM-X satellite joined the TerraSAR-X satellite in space to perform the conjoint interferometric TanDEM-X mission to acquire a truly global Digital Elevation Model (DEM) of unprecedented accuracy [1]. Since the very first interferometric acquisitions, the Integrated TanDEM-X Processor (ITP) delivered operationally “Raw”-DEMs and complex products of mono- and bistatic data. The RawDEMs are scenes of about 50 km × 30 km, generated for a dedicated DEM Mosaicking and Calibration Processor (MCP) which produces the final DEM. The so-called Coregistered Single-look Slant-range Complex (CoSSC) products are provided for each of these scenes in different flavors for production internal purposes and system performance monitoring as well as for scientific use. The capabilities of the ITP go far beyond the primary mission objective of DEM generation alone: it also provides the operationally available end-user products from different experimental modes as e.g. pursuit monostatic, dual polarization bistatic data, alternating bistatic in single and dual polarization and different bistatic and alternating bistatic spotlight modes. This paper focuses on the accuracy of the generated products, the ITPs contribution to the achieved accuracy of the data and the direct effect of it on the use and interpretation of RawDEM heights for temporal change detection. Also the basic characteristics of the operational experimental products are introduced..

State‐of‐the‐art search engine ranking methods combine several distinct sources of relevance evidence to produce a high‐quality ranking of results for each query. The fusion of information is currently done at query‐processing time, which has a direct effect on the response time of search systems. Previous research also shows that an alternative to improve search efficiency in textual databases is to precompute term impacts at indexing time. In this article, we propose a novel alternative to precompute term impacts, providing a generic framework for combining any distinct set of sources of evidence by using a machine‐learning technique. This method retains the advantages of producing high‐quality results, but avoids the costs of combining evidence at query‐processing time. Our method, called Learn to Precompute Evidence Fusion (LePrEF), uses genetic programming to compute a unified precomputed impact value for each term found in each document prior to query processing, at indexing time. Compared with previous research on precomputing term impacts, our method offers the advantage of providing a generic framework to precompute impact using any set of relevance evidence at any text collection, whereas previous research articles do not. The precomputed impact values are indexed and used later for computing document ranking at query‐processing time. By doing so, our method effectively reduces the query processing to simple additions of such impacts. We show that this approach, while leading to results comparable to state‐of‐the‐art ranking methods, also can lead to a significant decrease in computational costs during query processing.

The contribution of Polarimetric Synthetic Aperture Radar (PolSAR) images compared with the single-channel SAR in terms of temporal scene characterization has been found and described to add valuable information in the literature. In this paper, a new PolSAR change detector which makes use of Kullback-Leibler divergence is described. Kullback-Leibler divergence (KL-divergence) measures the amount of information in common between coherent temporal multi-channel polarimetric SAR acquisitions. Although in this paper KL-divergence measure has analytically been derived for temporal polarimetric SAR images based on complex Wishart process in time, since the mathematical formulation is general, it can be implemented into any kind of multivariate remote sensing data such as multi-spectral optical and interferometric images. KL-divergence measure is also simplified to give an explicit expressions for temporal single channel SAR images. The new results are simple, easy to be used, and superior in providing detailed structure.

Since July 2010, TerraSAR-X and TanDEM-X jointly acquire interferometric data. Starting their common commissioning phase with a so called pursuit monostatic configuration with 3 seconds time lag between the two passes, they were later put in a close formation in October 2010, acting since then as the first freely configurable bistatic SAR interferometer in space. All operational acquisitions were processed from instrument raw data to DEMs from day one of the data taking on by one single processing system: the Integrated TanDEM-X Processor (ITP) (see [1],[2]). Data take analysis, common parameter calculation, synchronization, bistatic focusing, filtering, co-registration, phase unwrapping and geocoding are all performed in one sequence inside this processor. This approach allows a high precision processing by passing all applied corrections and determined parameters from one step to the next. Specifically the geometric & phase accuracy and stability of the instruments, the processor and the auxiliary data (i.e. the millimetric precision of the baseline products) provide an unprecedented level of relative and absolute geometric accuracy in the bistatic operation. While many challenges of bistatic processing of the TanDEM-X data are encountered, the benefits of this single pass acquisition mode can be used to derive additional information from the data itself for further processing and calibration. In this paper, we will outline the bistatic interferometric processing steps of the ITP and focus on the aspects of geometric accuracy in DEM generation.

On June 21st, 2010, the German radar satellite TanDEM-X was launched and successfully placed in an orbit approaching the TerraSAR-X satellite until both systems will fly in close formation and will establish the only available bi-static interferometer in space. The primary TanDEM-X mission goal is to generate a global Digital Elevation Model (DEM) with a relative point-to-point height accuracy of 2 meters for moderate terrain at 12 m posting. For that purpose interferometric SAR data will be acquired over a period of 3 years in parallel to the operational running TerraSAR-X mission. Systematic processing of SAR raw data to so-called Raw-DEMs is performed by one single processing system, the Integrated TanDEM Processor (ITP). The final global DEM is then calibrated and mosaicked by a second system, the Calibration and Mosaicking Processor (MCP). The scope of this paper is to present an overview of ITP functionalities and to summarize the first processing results.

The purpose of this paper is to investigate the estimation of surface currents directly on stripmap TerraSAR-X data, as an alternative to Along Track Interferometry. The algorithm relies on efficient baseband magnitude-based Doppler estimation, preventing the estimate from possible biases like azimuth ambiguities and strong target reflections. The validation of the algorithm is made with acquisitions over the Elbe estuary river in Germany and the Eyjafjallajökull volcano in Iceland.

The purpose of this paper is to provide an algorithmic overview of the interferometric processing embedded in the Integrated TanDEM-X Processor (ITP), settled to the generation of the raw digital elevation model (DEM). The main processing blocks are described, with a focus on the spectral matching of the azimuth spectra, the high-precision coregistration, the dual-baseline phase unwrapping and the geocoding of the products. The robustness of the algorithms is demonstrated through a dual-pass TerraSAR-X scenario.