A crustal suture and lineament in North Africa

A possible suture between an old craton in West Africa and the Arabian—Nubian shield is marked by a persistent zone of Phanerozoic weakness. This zone extends between the Nile and Niger deltas and passes through the Qattara embayment, along the Bahariya fault, through the Kufra basin, between the Tibesti and Jabal al Uwaynat massifs, through the Bahr el Ghazal and Lake Chad areas, and along the Benoue trough.     

Airborne gravimetry used in precise geoid computations by ring integration

Two detailed geoids have been computed in the region of North Jutland. The first computation used marine data in the offshore areas. For the second computation the marine data set was replaced by the sparser airborne gravity data resulting from the AGMASCO campaign of September 1996. The results of comparisons of the geoid heights at on-shore geometric control showed that the geoid heights computed from the airborne gravity data matched in precision those computed using the marine data, supporting the view that airborne techniques have enormous potential for mapping those unsurveyed areas between the land-based data and the off-shore marine or altimetrically derived data. Received: 7 July 1997 / Accepted: 22 April 1998     

Space orientation and geodetic azimuths of long lines from observations of the ANNA Satellite

The space orientation and geodetic azimuths of lines ranging from 300 km to 1400 km have been determined from simultaneous optical observations of the ANNA Flashing Satellite. The results of this test prove that the azimuth and the space direction between two stations can be achieved to an accuracy of 0.5″ and 0.8″ second respectively with only a limited amount of data. The reason for the high accuracy is attributed to two factors: [1] the metric quality of the PC-1000's stellar cameras, and [2] the “perfect” simultaneity in the observations provided by the ANNA flashing light. Much of this work was accomplished by the writer while employed by the Geodesy and Gravity Branch of Cambridge Research Laboratories.     

On the theoretical link between LLL-reduction and Lambda-decorrelation

The LLL algorithm, introduced by Lenstra et al. (Math Ann 261:515–534, 1982), plays a key role in many fields of applied mathematics. In particular, it is used as an effective numerical tool for preconditioning the integer least-squares problems arising in high-precision geodetic positioning and Global Navigation Satellite Systems (GNSS). In 1992, Teunissen developed a method for solving these nearest-lattice point (NLP) problems. This method is referred to as Lambda (for Least-squares AMBiguity Decorrelation Adjustment). The preconditioning stage of Lambda corresponds to its decorrelation algorithm. From an epistemological point of view, the latter was devised through an innovative statistical approach completely independent of the LLL algorithm. Recent papers pointed out some similarities between the LLL algorithm and the Lambda-decorrelation algorithm. We try to clarify this point in the paper. We first introduce a parameter measuring the orthogonality defect of the integer basis in which the NLP problem is solved, the LLL-reduced basis of the LLL algorithm, or the $\Lambda $ -basis of the Lambda method. With regard to this problem, the potential qualities of these bases can then be compared. The $\Lambda $ -basis is built by working at the level of the variance-covariance matrix of the float solution, while the LLL-reduced basis is built by working at the level of its inverse. As a general rule, the orthogonality defect of the $\Lambda $ -basis is greater than that of the corresponding LLL-reduced basis; these bases are however very close to one another. To specify this tight relationship, we present a method that provides the dual LLL-reduced basis of a given $\Lambda $ -basis. As a consequence of this basic link, all the recent developments made on the LLL algorithm can be applied to the Lambda-decorrelation algorithm. This point is illustrated in a concrete manner: we present a parallel $\Lambda $ -type decorrelation algorithm derived from the parallel LLL algorithm of Luo and Qiao (Proceedings of the fourth international C $^*$ conference on computer science and software engineering. ACM Int Conf P Series. ACM Press, pp 93–101, 2012).     

Negotiating on location, timing, duration, and participant in agent-mediated joint activity-travel scheduling

Agent-based simulation has become an important modeling approach in activity-travel analysis. Social activities account for a large amount of travel and have an important effect on activity-travel scheduling. Participants in joint activities usually have various options regarding location, participants, and timing and take different approaches to make their decisions. In this context, joint activity participation requires negotiation among agents involved, so that conflicts among the agents can be addressed. Existing mechanisms do not fully provide a solution when utility functions of agents are nonlinear and non-monotonic. Considering activity-travel scheduling in time and space as an application, we propose a novel negotiation approach, which takes into account these properties, such as continuous and discrete issues, and nonlinear and non-monotonic utility functions, by defining a concession strategy and a search mechanism. The results of experiments show that agents having these properties can negotiate efficiently. Furthermore, the negotiation procedure affects individuals’ choices of location, timing, duration, and participants.     

Automatic main road extraction from high resolution satellite imageries by means of particle swarm optimization applied to a fuzzy-based mean calculation approach

Manual extraction of road network by human operator is an expensive and time-consuming procedure. Alternatively, automation of the extraction process would be a great advancement. For this purpose, an automatic method is proposed to extract roads from high resolution satellite images. In this study, using few samples from road surface, a particle swarm optimization is applied to a fuzzy-based mean calculation system to obtain road mean values in each band of high resolution satellite colour images. Then, the images are segmented using the calculated mean values from the fuzzy system. Optimizing the fuzzy cost function by particle swarm optimization enables the fuzzy approach to be the best mean value of road with sub-grey level precision. Initially, this method was applied to simulated images where the calculated mean values are consistent with the hypothetic mean values. Application of the method to IKONOS satellite images has shown a prospective outcome for automatic road extraction. Mathematical morphology is subsequently used to extract an initial main road centreline from the segmented image. Then, small redundant segments are automatically removed. The quality of the extracted road centreline indicates the effectiveness of the proposed approach.     

Changes in timber haul emissions in the context of shifting forest management and infrastructure

Background  

Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport.