Benchmarking spatial joins a la carte

Spatial joins are join operations that involve spatial data types and operators. Spatial access methods are often used to speed up the computation of spatial joins. This paper addresses the issue of benchmarking spatial join operations. For this purpose, we first present a WWW-based benchmark generator to produce sets of rectangles. Using a Web browser, experimenters can specify the number of rectangles in a sample, as well as the statistical distributions of their sizes, shapes, and locations. Second, using the generator and a well-defined set of statistical models we define several tests to compare the performance of three spatial join algorithms: nested loop, scan-and-index, and synchronized tree traversal. We also added two real-life data sets from the Sequoia 2000 storage benchmark. Our results show that the relative performance of the different techniques mainly depends on the selectivity factor of the join predicate. All of the statistical models and algorithms are available on the Web, which allows for easy verification and modification of our experiments.     

Seasonal temperatures for the past ∼400 years reconstructed from diatom and chironomid assemblages in a high-altitude lake (Lej da la Tscheppa,Switzerland)

We analysed a 42 cm long sediment record from Lej da la Tscheppa, a high-altitude lake (2,616 m a.s.l.) in the Upper Engadine valley (Switzerland) for subfossil diatoms, chironomids and pollen. The chronology of the top 21 cm of the record was established using ²¹⁰Pb analysis using a constant-rate-of-supply model, and validated with ¹³⁷Cs measurements and the content of spheroidal carbonaceous particles. A tentative chronology for the lower part of the core was obtained through extrapolation of the sedimentation rates in the uppermost part of the record. Pollen assemblages in the record reflect regional changes in forestation and land-use patterns in the Upper Engadine valley and show no evidence of significant local human activity in the lake’s catchment. Diatom assemblages record a distinct increase in planktonic taxa since the early 19th century, suggesting a decrease in the duration of ice-cover. In contrast, chironomid assemblages remained stable during a large part of the record. We applied an established chironomid-based July air temperature transfer function and a newly developed diatom-based spring air temperature transfer function to reconstruct past seasonal air temperature changes at Lej da la Tscheppa. The reconstructions indicate a diatom-inferred warming trend in spring temperatures during the past ca. 400 years, whereas chironomid-inferred summer temperatures suggest a slight cooling trend. These biota-based reconstructions are in good agreement with the centennial-scale temperature trend in an independent reconstruction of regional temperatures in the Upper Engadine region based on instrumental records and documentary proxy evidence from the Alps. Our results suggest that, in high-altitude lakes, independent chironomid- and diatom-based seasonal temperature reconstruction is possible and can be successfully used to track seasonal temperature trends.     

Characterization of Compass M-1 signals

An analysis of observations from China’s first medium earth orbit satellite Compass M-1 is presented, with main focus on the first orbit and clock solution for this satellite. The orbit is computed from laser ranging measurements. Based on this orbit solution, the apparent clock offset is estimated using measurements from two GNSS receivers, which allow Compass tracking. The analysis of the clock solutions reveals unexpectedly high dynamics in the pseudorange and carrier-phase observations. Furthermore, carrier-to-noise density ratio, pseudorange noise, and multipath are analyzed and compared to GPS and GIOVE. The results of the clock analysis motivate further research on the signals of the geostationary satellites of the Compass constellation.     

In-flight performance analysis of the CHAMP BlackJack GPS Receiver

JPL's BlackJack receiver currently represents the most widely used geodetic grade GPS receiver for space applications. Using data from the CHAMP science mission, the in-flight performance of the BlackJack receiver has been assessed and the impact of various software updates performed during the 2.5 years since launch is described. Key aspects of the study comprise the channel allocation, anomalous data points, and the noise level of the code and carrier data. In addition, it has been demonstrated that the code measurements collected onboard the CHAMP satellite are notably affected by multipath errors in the aft-looking hemisphere, which can be attributed to cross-talk between the occultation antenna string and the primary precise orbit determination antenna. For carrier smoothed 10 s normal points, the code noise itself varies between a minimum of 5 cm at high elevations and 0.5 m (C/A) to 1.0 m (P₁, P₂) at 10° elevation. Carrier-phase data exhibit representative errors of 0.2 to 2.5 mm. The results of the CHAMP GPS data analysis contribute to a better understanding and possible improvement of the BlackJack receiver and support the design of optimal data editing and weighting strategies in precise orbit determination applications.     

Location Based Social Networks – Definition,Current State of the Art and Research Agenda

The growing penetration of GPS equipped smartphones allowing users to constantly share geographic information on their current whereabouts has led the way to an augmentation of existing Social Network Sites with location‐based features or the creation of new ones exclusively around geographic information. Within these Location Based Social Networks vast amounts of geographic information are allocated, which attracted the attention of researchers with various scientific backgrounds. This article presents a comprehensive definition of this special type of Social Network Site and an overview of research activities, which are currently conducted using the data. Finally, a research agenda for GIScience is drawn from existing research directions.     

Methodology and use of tensor invariants for satellite gravity gradiometry

Although its use is widespread in several other scientific disciplines, the theory of tensor invariants is only marginally adopted in gravity field modeling. We aim to close this gap by developing and applying the invariants approach for geopotential recovery. Gravitational tensor invariants are deduced from products of second-order derivatives of the gravitational potential. The benefit of the method presented arises from its independence of the gradiometer instrument’s orientation in space. Thus, we refrain from the classical methods for satellite gravity gradiometry analysis, i.e., in terms of individual gravity gradients, in favor of the alternative invariants approach. The invariants approach requires a tailored processing strategy. Firstly, the non-linear functionals with regard to the potential series expansion in spherical harmonics necessitates the linearization and iterative solution of the resulting least-squares problem. From the computational point of view, efficient linearization by means of perturbation theory has been adopted. It only requires the computation of reference gravity gradients. Secondly, the deduced pseudo-observations are composed of all the gravitational tensor elements, all of which require a comparable level of accuracy. Additionally, implementation of the invariants method for large data sets is a challenging task. We show the fundamentals of tensor invariants theory adapted to satellite gradiometry. With regard to the GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite gradiometry mission, we demonstrate that the iterative parameter estimation process converges within only two iterations. Additionally, for the GOCE configuration, we show the invariants approach to be insensitive to the synthesis of unobserved gravity gradients.     

Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition

We develop and apply an efficient strategy for Earth gravity field recovery from satellite gravity gradiometry data. Our approach is based upon the Paige-Saunders iterative least-squares method using QR decomposition (LSQR). We modify the original algorithm for space-geodetic applications: firstly, we investigate how convergence can be accelerated by means of both subspace and block-diagonal preconditioning. The efficiency of the latter dominates if the design matrix exhibits block-dominant structure. Secondly, we address Tikhonov-Phillips regularization in general. Thirdly, we demonstrate an effective implementation of the algorithm in a high-performance computing environment. In this context, an important issue is to avoid the twofold computation of the design matrix in each iteration. The computational platform is a 64-processor shared-memory supercomputer. The runtime results prove the successful parallelization of the LSQR solver. The numerical examples are chosen in view of the forthcoming satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer). The closed-loop scenario covers 1 month of simulated data with 5 s sampling. We focus exclusively on the analysis of radial components of satellite accelerations and gravity gradients. Our extensions to the basic algorithm enable the method to be competitive with well-established inversion strategies in satellite geodesy, such as conjugate gradient methods or the brute-force approach. In its current development stage, the LSQR method appears ready to deal with real-data applications.     

GIOVE-A initial signal analysis

In late December 2005 the GIOVE-A test satellite was launched by the European Space Agency (ESA) to secure the frequencies for the Galileo system and to provide a platform for testing the new navigation signals. We performed an initial assessment of these signals using the 30 m deep space antenna of the DLR ground station in Weilheim (Germany). The antenna gain raised the signals above the noise level, thus allowing a detailed analysis even without knowledge of the ranging codes. The present paper covers the analysis of the L1/E1 signals, which includes a discussion of the spectrum, the time domain signal and a decoding of the spreading codes for the Open Service.