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.     

GIS Course Planning: A Comparison of Syllabi at US College and Universities

Despite the enormous growth of college courses dealing with spatial information, curriculum planning involving geographic information science (GIS) courses and programs has received little attention within the GIS literature. As the number and variety of GIS courses expands, so too does the importance of both systematic and inclusive planning and campus‐wide coordination. In this article we explore course planning through an exploration of 312 GIS course syllabi used at US colleges and universities with the goal of characterizing the degree to which learning resources, student evaluation methods, and course topics have become standardized across institution types, academic levels, and disciplines. Our findings reveal a consensus in the use of GIS software across courses but no similar agreement in the use of textbooks. Hands‐on activities were used as evaluation methods in nearly every course in the sample regardless of institution type or academic level. However, quizzes, tests and final exams were used more often in community colleges while papers and projects were used more frequently in four‐year and comprehensive research universities. The frequency of topic categories listed on syllabi was relatively consistent across institutions, academic levels and disciplines with a few topics such as vector analytic operations, data models, and data creation/acquisition/editing included on more than 50% of syllabi.     

Exploring Mobility Indoors: an Application of Sensor‐based and GIS Systems

The popularization of tracking devices, such as GPS, accelerometers and smartphones, have made it possible to detect, record, and analyze new patterns of human movement and behavior. However, employing GPS alone for indoor localization is not always possible due to the system's inability to determine location inside buildings or in places of signal occlusion. In this context, the application of local wireless networks for determining position is a promising alternative solution, although they still suffer from a number of limitations due to energy and IT‐resources. Our research outlines the potential for employing indoor wireless network positioning and sensor‐based systems to improve the collection of tracking data indoors. By applying various methods of GIScience we developed a methodology that can be applicable for diverse human indoor mobility analysis. To show the advantage of the proposed method, we present the result of an experiment that included mobility analysis of 37 participants. We tracked their movements on a university campus over the course of 41 days and demonstrated that their movement behavior can be successfully studied with our proposed method.     

Singular Unit Restoration in Interferograms Based on Complex-Valued Markov Random Field Model for Phase Unwrapping

In generating a digital elevation map from an interferogram obtained by interferometric synthetic aperture radar, the filtering process is as important as the phase unwrapping process. Before unwrapping, we usually have to restore the data image by reducing so-called singular points (SPs) by filtering process without destroying or smearing delicate fringes. Previously, an effective SP restoration method was proposed based on the complex-valued Markov random field (CMRF) model. However, there is still room for improvement in the definition of SPs and in the formulation of CMRF parameter estimation. In this letter, we propose a novel scheme by introducing a new concept, namely, the ldquosingular unit.rdquo We also estimate CMRF parameters locally as a weighted sum by taking the distance and SP numbers in sample sites into account. By using this restoration method, we demonstrate a high-performance removal of SPs. We also find that delicate landscape features, which are often lost in conventional filtering, are preserved appropriately. We confirm the quality in higher signal-to-noise ratios obtained against actual height data.     

3-D Radargrammetric Modeling of RADARSAT-2 Ultrafine Mode: Preliminary Results of the Geometric Calibration

The geometry and the accuracy of the 3-D cartographic localization of RADARSAT-2 images are being evaluated as part of the Canadian Space Agency's Science and Operational Applications Research program. In a first step, the Toutin's 3-D physical model, previously developed for RADARSAT-1, was adapted to RADARSAT-2 sensor and applied to two ultrafine mode images (U2 and U25) acquired over an area in Beauport, Quebec. Both the 3-D modeling computed with only 12 ground control points and its geometric localization were evaluated with different check data: 1) independent check points; 2) the two quasi-epipolar images; 3) the two orthoimages; and 4) 1-m accurate orthophotos. All four results and validations are in agreement and confirm that the 3-D geometric localization and restitution accuracy are 1 m in planimetry and 2 m in elevation. The checked data error being included in these evaluations and the relative error computed from the quasi-epipolar comparison provided a high level of confidence that the precision of Toutin's 3-D radargrammetric model is better than 0.25 m.     

Recent Retreat of Wilkins Ice Shelf Reveals New Insights in Ice Shelf Breakup Mechanisms

The disintegration of various ice shelves on the Antarctic Peninsula has demonstrated their vulnerability and impacts on tributary glaciers. A satellite image of Wilkins Ice Shelf (WIS) from July of 2007 reveals the formation of a large new double fracture, accompanied by numerous small fractures. We show that bending stresses induced by buoyancy forces were responsible for fracture formation. On February 28-29, 2008, an area of about 425 km² broke up at a narrow connection of the WIS to one of its confining islands. In contrast to Larsen B Ice Shelf, melt ponds that drain into crevasses played no role in this breakup process. A further breakup of 160 km² in the same area occurred on May 30-31, 2008 and documented that breakup can occur during austral winter. Radar images reveal a frozen surface, which demonstrates that in this breakup, surface melt water did not play a role. We conclude that ice shelves with strong thickness contrasts carry potential for disintegration. The fact that the WIS experienced two breakup events under two widely contrasting surface conditions (one during the melt season and one during winter) reveals that there may be several reasons for the disintegration of ice shelves that operate under differing circumstances.     

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.