Automated delineation of roof planes from LIDAR data

In this paper, we describe an algorithm for roof line delineation from LIDAR data which aims at achieving models of a high level of detail. Roof planes are initially extracted by segmentation based on the local homogeneity of surface normal vectors of a digital surface model (DSM). A case analysis then reveals which of these roof planes intersect and which of them are separated by a step edge. The positions of the step edges are determined precisely by a new algorithm taking into account domain specific information. Finally, all step edges and intersection lines are combined to form consistent polyhedral models. In all phases of this workflow, decision making is based upon statistical reasoning about geometrical relations between neighbouring entities in order to reduce the number of control parameters and to increase the robustness of the method

Time takes space: selective effects of multitasking on concurrent spatial processing.

Many everyday activities require coordination and monitoring of complex relations of future goals and deadlines. Cognitive offloading may provide an efficient strategy for reducing control demands by representing future goals and deadlines as a pattern of spatial relations. We tested the hypothesis that multiple-task monitoring involves time-to-space transformational processes, and that these spatial effects are selective with greater demands on coordinate (metric) than categorical (nonmetric) spatial relation processing. Participants completed a multitasking session in which they monitored four series of deadlines, running on different time scales, while making concurrent coordinate or categorical spatial judgments. We expected and found that multitasking taxes concurrent coordinate, but not categorical, spatial processing. Furthermore, males showed a better multitasking performance than females. These findings provide novel experimental evidence for the hypothesis that efficient multitasking involves metric relational processing

Evaluation of a method for fusing LIDAR data and multispectral images for building detection

In this paper, we describe the evaluation of a method for building detection by the Dempster-Shafer fusion of LIDAR data and multispectral images. For that purpose, ground truth was digitised for two test sites with quite different characteristics. Using these data sets, the heuristic model for the probability mass assignments of the method is validated, and rules for the tuning of the parameters of this model are discussed. Further we evaluate the contributions of the individual cues used in the classification process to the quality of the classification results. Our results show the degree to which the overall correctness of the results can be improved by fusing LIDAR data with multispectral images

The evolution of deep water mixing and weathering inputs in the central Atlantic Ocean over the past 33 Myr

The isotopic composition of Nd in present-day deep waters of the central and northeastern Atlantic Ocean is thought to fingerprint mixing of North Atlantic Deep Water with Antarctic Bottom Water. The central Atlantic Romanche and Vema Fracture Zones are considered the most important pathways for deep water exchange between the western and eastern Atlantic basins today. We present new Nd isotope records of the deepwater evolution in the fracture zones obtained from ferromanganese crusts, which are inconsistent with simple water mass mixing alone prior to 3 Ma and require additional inputs from other sources. The new Pb isotope time series from the fracture zones are inexplicable by simple mixing of North Atlantic Deep Water and Antarctic Bottom Water for the entire past 33 Myr. The distinct and relatively invariable Nd and Pb isotope records of deep waters in the fracture zones appear instead to have been controlled to a large extent by contributions from Saharan dust and the Orinoco/Amazon Rivers. Thus the previously observed similarity of Nd and Pb isotope time series from the western and eastern North Atlantic basins is better explainable by direct supply of Labrador Seawater to the eastern basin via a northern pathway rather than by advection of North Atlantic Deep Water via the Romanche and Vema Fracture Zones

Forecast, observation and modelling of a deep stratospheric intrusion event over Europe

A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU-project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity) with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT) event, encountered during the STACCATO period on 20-21 June 2001, could be followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20-21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one reaching almost a height of 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent measurements of the cosmogenic radionuclides <sup>10</sup>Be and <sup>7</sup>Be and their ratio <sup>10</sup>Be/<sup>7</sup>Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures with many details the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October 1999) from the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model is shown to be in very good agreement with the observations during this case study, which provides the first successful validation of a chemical tracer that is used operationally in a weather forecast model. This suggests that coupling chemistry and weather forecast models may significantly improve both weather and chemical forecasts in the future