bluuebunny/crossref_metadata_2025 huggingface dataset:
Balance of assimilative and dissimilative nitrogen processes in a diatom-rich tidal flat sediment
Authors: Dähnke K. , Moneta A. , Veuger B. , Soetaert K. , Middelburg J. J.
Published: October 2012

Abstract. Tidal flat sediments are subject to repetitive mixing and resuspension events. In a short-term (24 h) 15N-labelling experiment, we investigated reactive nitrogen cycling in a tidal flat sediment following an experimentally induced resuspension event. We focused on (a) the relative importance of assimilatory versus dissimilatory processes and (b) the role of benthic microalgae therein. 15N-labelled substrate was added to homogenized sediment, and 15N was subsequently traced into sediment and dissolved inorganic nitrogen (DIN) pools. Integration of results in a N-cycle model allowed us to quantify the proportion of major assimilatory and dissimilatory processes in the sediment. Upon sediment disturbance, rates of dissimilatory processes like nitrification and denitrification were very high, but declined rapidly towards a steady state. Once this was reached, the balance between assimilation and dissimilation in this tidal mudflat was mainly dependent on the nitrogen source: nitrate was utilized almost exclusively dissimilatory via denitrification, whereas ammonium was rapidly assimilated, with about a quarter of this assimilation due to benthic microalgae (BMA). Benthic microalgae significantly affected the nitrogen recycling balance in sediments, because in the absence of BMA activity the recovering sediment turned from a net ammonium sink to a net source. The driving mechanisms for assimilation or dissimilation accordingly appear to be ruled to a large extent by external physical forcing, with the entire system being capable of rapid shifts following environmental changes. Assimilatory pathways gain importance under stable conditions, with a substantial contribution of BMA to total assimilation.
The impact of sea-level rise on organic matter decay rates in Chesapeake Bay brackish tidal marshes
Authors: Kirwan M. L. , Langley J. A. , Guntenspergen G. R. , Megonigal J. P.
Published: October 2012

Abstract. The balance between organic matter production and decay determines how fast coastal wetlands accumulate soil organic matter. Despite the importance of soil organic matter accumulation rates in influencing marsh elevation and resistance to sea-level rise, relatively little is known about how decomposition rates will respond to sea-level rise. Here, we estimate the sensitivity of decomposition to flooding by measuring rates of decay in 87 bags filled with milled sedge peat, including soil organic matter, roots and rhizomes. Experiments were located in field-based mesocosms along 3 mesohaline tributaries of the Chesapeake Bay. Mesocosm elevations were manipulated to influence the duration of tidal inundation. Although we found no significant influence of inundation on decay rate when bags from all study sites were analyzed together, decay rates at two of the sites increased with greater flooding. These findings suggest that flooding may enhance organic matter decay rates even in water-logged soils, but that the overall influence of flooding is minor. Our experiments suggest that sea-level rise will not accelerate rates of peat accumulation by slowing the rate of soil organic matter decay. Consequently, marshes will require enhanced organic matter productivity or mineral sediment deposition to survive accelerating sea-level rise.
Autonomous distributed temperature sensing for long-term heated applications in remote areas
Authors: Kurth A.-M. , Dawes N. , Selker J. , Schirmer M.
Published: October 2012

Abstract. Distributed Temperature Sensing (DTS) is a fiber-optical method enabling simultaneous temperature measurements over long distances. Electrical resistance heating of the metallic components of the fiber-optic cable provides information on the thermal characteristics of the cable's environment, providing valuable insight into processes occurring in the surrounding medium, such as groundwater-surface water interactions, dam stability or soil moisture. Until now, heated applications required direct handling of the DTS instrument by a researcher, rendering long-term investigations in remote areas impractical due to the often difficult and time-consuming access to the field site. Remote-control and automation of the DTS instrument and heating processes, however, resolve the issue with difficult access. The data can also be remotely accessed and stored on a central database. The power supply can be grid-independent, although significant infrastructure investment is required here due to high power consumption during heated applications. Solar energy must be sufficient even in worst case scenarios, e.g. during long periods of intense cloud cover, to prevent system failure due to energy shortage. In combination with storage batteries and a low heating frequency, e.g. once per day or once per week (depending on the season and the solar radiation on site), issues of high power consumption may be resolved. Safety regulations dictate adequate shielding and ground-fault protection, to safeguard animals and humans from electricity and laser sources. In this paper the autonomous DTS system is presented to allow research with heated applications of DTS in remote areas for long-term investigations of temperature distributions in the environment.
Impacts of inhomogeneous landscapes in oasis interior on the oasis self-maintenance mechanism by integrating numerical model with satellite data
Authors: Meng X. , Lu S. , Zhang T. , Ao Y. , Li S. , Bao Y. , Wen L. , Luo S.
Published: October 2012

Abstract. The impacts of inhomogeneity of the oasis interior on the oasis self-maintenance mechanism are investigated by using the mesoscale model MM5 (the fifth-generation Pennsylvania State University National Center for Atmospheric Research (NCAR) mesoscale model) with satellite observations of land use types, vegetation fraction and surface-layer soil moisture from MODIS (Moderate Resolution Imaging Spectroradiometer) data. Four simulations were performed, among which the CTL (control simulation) and MOD (moderated simulation with parameters replaced by MODIS data) were used to validate the model results; EXP1 (experiment 1) and EXP2 (experiment 2) were designed to study the inhomogeneity of oasis interior. Results show that the changes of oasis heterogeneity influence the surface heat-flux partitioning, which leads to a larger "cold-wet" effect over the oasis. Vertical sections of humidity illustrate the existence of a moisture-inversion level, and the deeper moisture inversion of EXP1 and EXP2 further indicates that the relative homogeneity in the oasis interior helps produce stronger humidity inversion over the oasis, thus limiting evaporation. This is further verified by the analysis of the secondary circulation, which shows that the more homogeneous land surface conditions lead to stronger secondary circulation and less turbulent drafts over the oasis interior, playing a positive role in the oasis self-maintenance and development.
Hydrology of the Po River: looking for changing patterns in river discharge
Authors: Montanari A.
Published: October 2012

Abstract. Scientists and public administrators are devoting increasing attention to the Po River, in Italy, in view of concerns related to the impact of increasing urbanisation and exploitation of water resources. A better understanding of the hydrological regime of the river is necessary to improve water resources management and flood protection. In particular, the analysis of the effects of hydrological and climatic change is crucial for planning sustainable development and economic growth. An extremely interesting issue is to inspect to what extent river flows can be naturally affected by the occurrence of long periods of water abundance or scarcity, which can be erroneously interpreted as irreversible changes due to human impact. In fact, drought and flood periods alternatively occurred in the recent past in the form of long-term fluctuations. This paper presents advanced graphical and analytical methods to gain a better understanding of the temporal distribution of the Po River discharge. In particular, we present an analysis of river flow variability and persistence properties, to gain a better understanding of natural patterns, and in particular long-term changes, which may affect the future flood risk and availability of water resources.
A new top boundary condition for modeling surface diffusive exchange of a generic volatile tracer: theoretical analysis and application to soil evaporation
Authors: Tang J. Y. , Riley W. J.
Published: October 2012

Abstract. We describe a new top boundary condition (TBC) for representing the air-soil diffusive exchange of a generic volatile tracer. This new TBC (1) accounts for the multi-phase flow of a generic tracer; (2) accounts for effects of soil temperature, pH, solubility, sorption, and desorption processes; (3) enables a smooth transition between wet and dry soil conditions; (4) is compatible with the conductance formulation for modeling air-water volatile tracer exchange; and (5) is applicable to site, regional, and global land models. Based on the new TBC, we developed new formulations for bare-soil resistance and corresponding soil evaporation efficiency. The new soil resistance is predicted as the reciprocal of the harmonic sum of two resistances: (1) gaseous and aqueous molecular diffusion and (2) liquid mass flow resulting from the hydraulic pressure gradient between the soil surface and center of the topsoil control volume. The resulting soil evaporation efficiency reasonably explains the two-stage soil evaporation curves typically observed in field and laboratory soil evaporation measurements. Comparison with the soil evaporation efficiency equation of Lee and Pielke (1992; hereafter LP92) indicates that their equation can overestimate soil evaporation when the atmospheric resistance is low and underestimate soil evaporation when the soil is dry. Using a synthetic inversion experiment, we demonstrated that using inverted soil resistance data from field measurements to derive empirical soil resistance formulations resulted in large uncertainty because (1) the inverted soil resistance data is always severely impacted by measurement error and (2) the derived empirical equation is very sensitive to the number of data points and the assumed functional form of the resistance. We expect the application of our new TBC in land models will provide a consistent representation for the diffusive tracer exchange at the soil–air interface.
ACCURACY ANALYSIS OF A LOW-COST PLATFORM FOR POSITIONING AND NAVIGATION
Authors: Hofmann S. , Kuntzsch C. , Schulze M. J. , Eggert D. , Sester M.
Published: October 2012

Abstract. This paper presents an accuracy analysis of a platform based on low-cost components for landmark-based navigation intended for research and teaching purposes. The proposed platform includes a LEGO MINDSTORMS NXT 2.0 kit, an Android-based Smartphone as well as a compact laser scanner Hokuyo URG-04LX. The robot is used in a small indoor environment, where GNSS is not available. Therefore, a landmark map was produced in advance, with the landmark positions provided to the robot. All steps of procedure to set up the platform are shown. The main focus of this paper is the reachable positioning accuracy, which was analyzed in this type of scenario depending on the accuracy of the reference landmarks and the directional and distance measuring accuracy of the laser scanner. Several experiments were carried out, demonstrating the practically achievable positioning accuracy. To evaluate the accuracy, ground truth was acquired using a total station. These results are compared to the theoretically achievable accuracies and the laser scanner’s characteristics.
CORRECTION OF FAULTY LINES IN MUSCLE MODEL, TO BE USED IN 3D BUILDING NETWORK CONSTRUCTION
Authors: Karas I. R. , Atila U. , Abdul-Rahman A.
Published: October 2012

Abstract. This paper describes the usage of MUSCLE (Multidirectional Scanning for Line Extraction) Model for automatic generation of 3D networks in CityGML format (from raster floor plans). MUSCLE (Multidirectional Scanning for Line Extraction) Model is a conversion method which was developed to vectorize the straight lines through the raster images including floor plans, maps for GIS, architectural drawings, and machine plans. The model allows user to define specific criteria which are crucial for acquiring the vectorization process. Unlike traditional vectorization process, this model generates straight lines based on a line thinning algorithm, without performing line following-chain coding and vector reduction stages. In this method the nearly vertical lines were obtained by scanning the images horizontally, while the nearly horizontal lines were obtained by scanning the images vertically. In a case where two or more consecutive lines are nearly horizontal or nearly vertical, raster data become unmanageable and the process generates wrongly vectorized lines. In this situation, to obtain the precise lines, the image with the wrongly vectorized lines is diagonally scanned. By using MUSCLE model, the network models are topologically structured in CityGML format. After the generation process, it is possible to perform 3D network analysis based on these models. Then, by using the software that was designed based on the generated models, a geodatabase of the models could be established. This paper presents the correction application in MUSCLE and explains 3D network construction in detail.
DATA-ORIENTED ALGORITHM FOR ROUTE CHOICE SET GENERATION IN A METROPOLITAN AREA WITH MOBILE PHONE GPS DATA
Authors: Nakamura T. , Sekimoto Y. , Usui T. , Shibasaki R.
Published: October 2012

Abstract. Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path) algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map) as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a result, the proposed route generation algorithm and GPS data cleaning process work well and a huge variety of routes that have high potential to be used in the real world can be generated.
AN OPEN SOURCE GEOVISUAL ANALYTICS TOOLBOX FOR MULTIVARIATE SPATIO-TEMPORAL DATA IN ENVIRONMENTAL CHANGE MODELLING
Authors: Bernasocchi M. , Coltekin A. , Gruber S.
Published: October 2012

Abstract. In environmental change studies, often multiple variables are measured or modelled, and temporal information is essential for the task. These multivariate geographic time-series datasets are often big and difficult to analyse. While many established methods such as PCP (parallel coordinate plots), STC (space-time cubes), scatter-plots and multiple (linked) visualisations help provide more information, we observe that most of the common geovisual analytics suits do not include three-dimensional (3D) visualisations. However, in many environmental studies, we hypothesize that the addition of 3D terrain visualisations along with appropriate data plots and two-dimensional views can help improve the analysts’ ability to interpret the spatial relevance better. To test our ideas, we conceptualize, develop, implement and evaluate a geovisual analytics toolbox in a user-centred manner. The conceptualization of the tool is based on concrete user needs that have been identified and collected during informal brainstorming sessions and in a structured focus group session prior to the development. The design process, therefore, is based on a combination of user-centred design with a requirement analysis and agile development. Based on the findings from this phase, the toolbox was designed to have a modular structure and was built on open source geographic information systems (GIS) program Quantum GIS (QGIS), thus benefiting from existing GIS functionality. The modules include a globe view for 3D terrain visualisation (OSGEarth), a scattergram, a time vs. value plot, and a 3D helix visualisation as well as the possibility to view the raw data. The visualisation frame allows real-time linking of these representations. After the design and development stage, a case study was created featuring data from Zermatt valley and the toolbox was evaluated based on expert interviews. Analysts performed multiple spatial and temporal tasks with the case study using the toolbox. The expert interviews were helpful to gain initial insight into the usability of the tools and to highlight further improvements and challenges; revealing certain usability issues and indicating that analysts consider the linked views to be potentially very beneficial and they appreciate seeing the data in its spatial context.
GENERALISATION OF SUBMARINE FEATURES ON NAUTICAL CHARTS
Authors: Guilbert E. , Zhang X.
Published: October 2012

Abstract. On most large scale and middle scale maps, relief is represented by contours and spot heights. In order to adapt the representation to the scale, the terrain is generalised either by smoothing or filtering the terrain model or by simplifying the contours. However this approach is not applicable to nautical chart construction where terrain features are selected according to their importance for navigation. This paper presents an approach for the consideration of feature attributes in the generalisation of a set of contours with respect to nautical chart constraints. Features are defined by sets of contours and a set of generalisation operators applied to features is presented. The definitions are introduced in a multi-agent system in order to perform automatic generalisation of a contour set. Results are discussed on a case study and directions for future work are presented.
EXPERIMENTAL EVALUATION OF LIDAR DATA VISUALIZATION SCHEMES
Authors: Ghosh S. , Lohan B.
Published: October 2012

Abstract. LiDAR (Light Detection and Ranging) has attained the status of an industry standard method of data collection for gathering three dimensional topographic information. Datasets captured through LiDAR are dense, redundant and are perceivable from multiple directions, which is unlike other geospatial datasets collected through conventional methods. This three dimensional information has triggered an interest in the scientific community to develop methods for visualizing LiDAR datasets and value added products. Elementary schemes of visualization use point clouds with intensity or colour, triangulation and tetrahedralization based terrain models draped with texture. Newer methods use feature extraction either through the process of classification or segmentation. In this paper, the authors have conducted a visualization experience survey where 60 participants respond to a questionnaire. The questionnaire poses six different questions on the qualities of feature perception and depth for 12 visualization schemes. The answers to these questions are obtained on a scale of 1 to 10. Results are thus presented using the non-parametric Friedman's test, using post-hoc analysis for hypothetically ranking the visualization schemes based on the rating received and finally confirming the rankings through the Page's trend test. Results show that a heuristic based visualization scheme, which has been developed by Ghosh and Lohani (2011) performs the best in terms of feature and depth perception.
SPATIO-TEMPORAL CLUSTERING OF MOVEMENT DATA: AN APPLICATION TO TRAJECTORIES GENERATED BY HUMAN-COMPUTER INTERACTION
Authors: McArdle G. , Tahir A. , Bertolotto M.
Published: October 2012

Abstract. Advances in ubiquitous positioning technologies and their increasing availability in mobile devices has generated large volumes of movement data. Analysing these datasets is challenging. While data mining techniques can be applied to this data, knowledge of the underlying spatial region can assist interpreting the data. We have developed a geovisual analysis tool for studying movement data. In addition to interactive visualisations, the tool has features for analysing movement trajectories, in terms of their spatial and temporal similarity. The focus in this paper is on mouse trajectories of users interacting with web maps. The results obtained from a user trial can be used as a starting point to determine which parts of a mouse trajectory can assist personalisation of spatial web maps.
VISUALISATION SUPPORT FOR EXPLORING URBAN SPACE AND PLACE
Authors: Pettit C. , Widjaja I. , Russo P. , Sinnott R. , Stimson R. , Tomko M.
Published: October 2012

Abstract. Urban research is fundamentally underpinned by heterogeneous, highly varied data. The availability and quantity of digital data sources is increasing rapidly. In order to facilitate decision-making and support processes related to urban policy and management, such data has to be readily analysed, synthesised and the results readily communicated to support evidence based decision-making. In this paper, we consider the current state of play of visualisation as it supports urban research. In doing so we firstly consider visualisation environments such as geographical information systems (GIS) and Cartography tools, digital globes, virtual simulation environments, building information models and gaming platforms. Secondly, we consider a number of visualisation techniques with a focusing on GIS and Cartography tools including space time cubes, heat maps, choropleth maps, flow maps and brushing. This review of visualisation environments and techniques is undertaken in the context of the Australian Urban Research Infrastructure Network project (www.aurin.org.au). AURIN is tasked with developing a portal and associated e-Infrastructure, which provides seamless access to federated data, modelling and visualisation tools to support the urban researcher community in Australia. We conclude by outlining future research and development opportunities in developing the AURIN visualisation toolkit by reflecting on the value of visualisation as a data exploration and communication tool for researchers and decision-makers to assist with the study and management of the urban fabric.
VISUALIZATION AND ANALYSIS OF LIGHT POLLUTION: A CASE STUDY IN HONG KONG
Authors: Wu B. , Wong H.
Published: October 2012

Abstract. The effects of light pollution problems in metropolitan areas are investigated in this study. Areas of Hong Kong are used as the source of three typical study cases. One case represents the regional scale, a second represents the district scale, and a third represents the street scale. Two light pollution parameters, Night Sky Brightness (NSB) and Street Light Level (SLL), are the focus of the analyses. Light pollution visualization approaches in relation to the different scales include various light pollution maps. They provide straightforward presentations of the light pollution situations in the study areas. The relationship between light pollution and several social-economic factors such as land use, household income, and types of outdoor lighting in the scale areas given, are examined. Results show that: (1) Land use may be one factor affecting light pollution in the regional scale; (2) A relatively strong correlation exists between light pollution and household income in the district scale; (3) The heaviest light pollution in the street scale is created by spotlights and also the different types of lighting from shops. The impact of the latter is in relation to the shop profile and size.
SOLAR RADIATION ESTIMATION ON BUILDING ROOFS AND WEB-BASED SOLAR CADASTRE
Authors: Agugiaro G. , Nex F. , Remondino F. , De Filippi R. , Droghetti S. , Furlanello C.
Published: October 2012

Abstract. The aim of this study is the estimation of solar irradiance on building roofs in complex Alpine landscapes. Very high resolution geometric models of the building roofs are generated by means of advanced automated image matching methods. Models are combined with raster and vector data sources to estimate the incoming solar radiation hitting the roofs. The methodology takes into account for atmospheric effects, site latitude and elevation, slope and aspect of the terrain as well as the effects of shadows cast by surrounding buildings, chimneys, dormers, vegetation and terrain topography. An open source software solution has been developed and applied to a study area located in a mountainous site and containing some 1250 residential, commercial and industrial buildings. The method has been validated by data collected with a pyranometer and results made available through a prototype WebGIS platform.
PREDICTION OF INDIVIDUAL'S MOVEMENT BASED ON INTERESTING PLACES
Authors: Feuerhake U.
Published: October 2012

Abstract. In general, the development of prediction methods is a quite challenging field. However, as difficult the development is, as useful those methods can be in a large variety of use cases. Whether the weather of tomorrow or the destination of a moving individual is to be predicted, in both cases many different aspects have to be considered, because as well as the weather's behaviour the one of individuals, especially human beings, is influenced by many factors. For instance, movements of human beings are either planned, arbitrary or influenced by their environment or social aspects. In most cases a combination of those factors is involved. In this paper, motivated by the context of a decentralized surveillance scenario, we present an approach for predicting movements on the basis of a prediction model generated from the knowledge, which is implicated in spatio-temporal trajectories. This model is based on extracted interesting places and considers several aspects, which contain gained information about the movement behaviour in a given scenario.
A FAST MATCHING APPROACH OF POLYGON FEATURES
Authors: Meng Q. , Fu Z. , Huang Y. , Shen M.
Published: October 2012

Abstract. This paper proposes a new method for the matching of polygon features. Firstly, the main points depicting the shape of the polygon feature are extracted with the method of simplifying the delineation and are represented in the Proximate-tangent Space. Secondly, constructing the analogous estimate function based on the polygon's property that going along the edges of the polygon covers the minimum total area. With the help of the constructed analogous estimate function, the corresponding feature points on the matching features and objective features are found and paired. After pairing all the feature points, the interpolation on the edges and angles realize the quick matching of the polygon features. At last, the polygon features on the two maps with the scale of 1:10000 and 1:2000 respectively are put into the experiment. It turns out that this matching method not only operates with a high speed but also has a strong robustness.
INTEGRATION OF GENETIC ALGORITHMS AND FUZZY LOGIC FOR URBAN GROWTH MODELING
Authors: Foroutan E. , Delavar M. R. , Araabi B. N.
Published: October 2012

Abstract. Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.
INTEGRATED MANAGEMENT OF HETEROGENEOUS GEODATA WITH A HYBRID 3D GEOINFORMATION SYSTEM
Authors: Becker S. , Walter V. , Fritsch D.
Published: October 2012

Abstract. The availability of 3D geodata is increasing tremendously. However, there is still a lack of appropriate tools for integrated data management and analysis solutions that can cope with the great diversity of geodata. Thus, our goal is a hybrid 3D geoinformation system which is able to combine and analyse heterogeneous 3D geodata in an efficient and consistent way. Based on the accepted standard ISO 19107, we propose a hybrid data model to overcome structural, geometric and topological data heterogeneity on a conceptual level. Our concept is hybrid with respect to data given in different data models, dimensions and quality levels. Through the explicit modelling of geometric correspondences, multiple representations and data inconsistency can be handled.
CAD CONSTRUCTION METHOD OF 3D BUILDING MODELS FOR GIS ANALYSIS
Authors: P. Boguslawski  , C. M. Gold  , A. A. Rahman
Published: October 2012

Abstract. Buildings are often modelled as two-dimensional (2D) footprints which are extruded to simple cubes. Buildings are also represented as more complex objects with roofs, facades, etc. – in this case they are polyhedra, sometimes of a complex shape. These allow for visualisation and analysis of a wide area like a city, but micro-scale analysis of interiors is not possible. An example can be rescue operation simulation where information about the internal structure of a building and the external terrain is crucial to improve the response time. It demands a three-dimensional (3D) model where each room is represented as a separate element; there are also doors, windows, walls and other objects that have to be included. Even complex geometrical models can be easily constructed using Computer-Aided Design (CAD) systems. However, lack of semantic information and topological relations makes such models poor choices for GIS analysis. With the new dual half-edge (DHE) data structure and a set of Euler operators a 3D model can be built as in CAD systems, and represented as a cell complex. Construction of non-manifold objects is also possible. An advantage of the DHE is simplicity – only edges and nodes are used. Because of the 3D duality implemented in the structure volumes (cells) and faces are also present in the model. The geometry of a model is constructed explicitly by using Euler operators: connections between elements are created automatically, and semantic information is represented with attributes which can be assigned to any element of the model.
IMPROVING 3D LIDAR POINT CLOUD REGISTRATION USING OPTIMAL NEIGHBORHOOD KNOWLEDGE
Authors: Gressin A. , Mallet C. , David N.
Published: October 2012

Abstract. Automatic 3D point cloud registration is a main issue in computer vision and photogrammetry. The most commonly adopted solution is the well-known ICP (Iterative Closest Point) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, and assuming that good a priori alignment is provided. A large body of literature has proposed many variations of this algorithm in order to improve each step of the process. The aim of this paper is to demonstrate how the knowledge of the optimal neighborhood of each 3D point can improve the speed and the accuracy of each of these steps. We will first present the geometrical features that are the basis of this work. These low-level attributes describe the shape of the neighborhood of each 3D point, computed by combining the eigenvalues of the local structure tensor. Furthermore, they allow to retrieve the optimal size for analyzing the neighborhood as well as the privileged local dimension (linear, planar, or volumetric). Besides, several variations of each step of the ICP process are proposed and analyzed by introducing these features. These variations are then compared on real datasets, as well with the original algorithm in order to retrieve the most efficient algorithm for the whole process. Finally, the method is successfully applied to various 3D lidar point clouds both from airborne, terrestrial and mobile mapping systems.
TRAJECTORY-BASED REGISTRATION OF 3D LIDAR POINT CLOUDS ACQUIRED WITH A MOBILE MAPPING SYSTEM
Authors: Gressin A. , Cannelle B. , Mallet C. , Papelard J.-P.
Published: October 2012

Abstract. Thanks to a hybrid georeferencing unit coupling GNSS and IMU sensors, mobile mapping systems (MMS) with lidar sensors provide accurate 3D point clouds of the acquired areas, mainly urban cities. When dealing with several acquisitions of the same area with the same device, differences in the range of several tens of centimeters can be observed. Such degradation of the georeferencing accuracies are due to two main reasons: inertial drift and losses of GNSS signals in urban corridors. The purpose of this paper is therefore to correct these differences with an accurate ICP-based registration algorithm, and then to correct the MMS trajectory using these retrieved local transformation parameters.The trajectory loop information plays a key role for that purpose. We propose a four-step method starting from a 3D point cloud with overlapping parts, and the trajectory of the mobile mapping system. First, a polygonal approximation of the trajectory is computed in order to first divide the whole registration problem in local sub-issues. Secondly, we aim to find all the potential overlapping acquired areas between these segments using simple bounding box intersections. Thirdly, for each pair of overlapping areas, an efficient variant of the ICP algorithm is proposed to (1) prune cases where segments do not share point clouds of the same areas and (2) retrieve the transformation parameters, for real overlapping cases. Finally, all these transformations are linked together, and fed into a global distance compensation problem, allowing to adjust the MMS trajectories for several passages. As a conclusion, this method is successfully applied to data acquired over Paris (France) with the Stereopolis mobile mapping system.
DEFORMATION DETECTION IN PIPING INSTALLATIONS USING PROFILING TECHNIQUES
Authors: Mapurisa W. T. , Sithole G.
Published: October 2012

Abstract. As-Built surveys of buildings and installations have received greater attention in recent years. An example is the 3D digital reconstruction of existing piping installations at chemical plants for plant maintenance, upgrades and safety standard concerns. This paper is directed at the reconstruction of piping installations with particular emphasis on the detection of deformities in pipes. Reconstruction begins with the automatic detection of individual piping elements which requires a prior segmentation. For segmentation, the profile intersection technique is used. Surfaces are considered as a network of intersecting curves as opposed to surface patches. Recreating such curves on a point set, and intersecting them, segments are identified. The entire scan is partitioned into a series of scan planes referred to as profiles. Points are then connected in each profile based on the surface they represent forming line segments. The line segments, which represent curves, are then intersected to identify segments. For pipes, line segments are elliptical. The centre of an ellipse lies on the pipes’ axis and the semi minor axis is equivalent to the radius of the pipe. Therefore together the centres and semi minor axis are used to describe the position, orientation, size and radius of a pipe. For deformed pipes, the line segments deviate from the elliptical shape. By identifying deviations of the line segments from the elliptical shape deformations are identified. The algorithm allows for cylinders, spheres, cones and tori to be detected including deformities in their shape. Experimental results show the effectiveness of the algorithm.
THE OPALS DATA MANAGER – EFFICIENT DATA MANAGEMENT FOR PROCESSING LARGE AIRBORNE LASER SCANNING PROJECTS
Authors: Otepka J. , Mandlburger G. , Karel W.
Published: October 2012

Abstract. The fast measurement rate of today's Airborne Laser Scanners results in billions of points for single ALS projects. Efficient algorithms and data management methods are, therefore, a precondition for successful project handling. The software package OPALS (Orientation and Processing of Airborne Laser Scanning data) was especially designed to meet those criteria. Central core of the package is the OPALS Data Manager (ODM). It provides both, fast spatial access to huge point clouds, as well as a flexible attribute schema to store additional point related quantities. Concepts of the spatial data organization and implementation details about the attribute handling are presented. Additionally, design rationales of the ODM, its file format and the system performance are described.
AUTOMATIC POWERLINE SCENE CLASSIFICATION AND RECONSTRUCTION USING AIRBORNE LIDAR DATA
Authors: Sohn G. , Jwa Y. , Kim H. B.
Published: October 2012

Abstract. This study aims to introduce new methods for classifying key features (power lines, pylons, and buildings) comprising utility corridor scene using airborne LiDAR data and modelling power lines in 3D object space. The proposed approach starts from PL scene segmentation using Markov Random Field (MRF), which emphasizes on the roles of spatial context of linear and planar features as in a graphical model. The MRF classifier identifies power line features from linear features extracted from given corridor scenes. The non-power line objects are then investigated in a planar space to sub-classify them into building and non-building class. Based on the classification results, precise localization of individual pylons is conducted through investigating a prior knowledge of contextual relations between power line and pylon. Once the pylon localization is accomplished, a power line span is identified, within which power lines are modelled with catenary curve models in 3D. Once a local catenary curve model is established, this initial model progressively extends to capture entire power line points by adopting model hypothesis and verification. The model parameters are adjusted using a stochastic non-linear square method for producing 3D power line models. An evaluation of the proposed approach is performed over an urban PL corridor area that includes a complex PL scene.
AUTOMATIC REGISTRATION OF TERRESTRIAL LASER SCANNER POINT CLOUDS USING NATURAL PLANAR SURFACES
Authors: Theiler P. W. , Schindler K.
Published: October 2012

Abstract. Terrestrial laser scanners have become a standard piece of surveying equipment, used in diverse fields like geomatics, manufacturing and medicine. However, the processing of today's large point clouds is time-consuming, cumbersome and not automated enough. A basic step of post-processing is the registration of scans from different viewpoints. At present this is still done using artificial targets or tie points, mostly by manual clicking. The aim of this registration step is a coarse alignment, which can then be improved with the existing algorithm for fine registration. The focus of this paper is to provide such a coarse registration in a fully automatic fashion, and without placing any target objects in the scene. The basic idea is to use virtual tie points generated by intersecting planar surfaces in the scene. Such planes are detected in the data with RANSAC and optimally fitted using least squares estimation. Due to the huge amount of recorded points, planes can be determined very accurately, resulting in well-defined tie points. Given two sets of potential tie points recovered in two different scans, registration is performed by searching for the assignment which preserves the geometric configuration of the largest possible subset of all tie points. Since exhaustive search over all possible assignments is intractable even for moderate numbers of points, the search is guided by matching individual pairs of tie points with the help of a novel descriptor based on the properties of a point's parent planes. Experiments show that the proposed method is able to successfully coarse register TLS point clouds without the need for artificial targets.
CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION FROM IMAGES AND VIDEOS
Authors: Bulatov D. , Rottensteiner F. , Schulz K.
Published: October 2012

Abstract. Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM), are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance) data sets consisting of (few spatial-temporarily diverse) images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.
GEOMETRICAL CORRELATION AND MATCHING OF 2D IMAGE SHAPES
Authors: Vizilter Y. V. , Zheltov S. Y.
Published: October 2012

Abstract. The problem of image correspondence measure selection for image comparison and matching is addressed. Many practical applications require image matching "just by shape" with no dependence on the concrete intensity or color values. Most popular technique for image shape comparison utilizes the mutual information measure based on probabilistic reasoning and information theory background. Another approach was proposed by Pytiev (so called "Pytiev morphology") based on geometrical and algebraic reasoning. In this framework images are considered as piecewise-constant 2D functions, tessellation of image frame by the set of non-intersected connected regions determines the "shape" of image and the projection of image onto the shape of other image is determined. Morphological image comparison is performed using the normalized morphological correlation coefficients. These coefficients estimate the closeness of one image to the shape of other image. Such image analysis technique can be characterized as an “"ntensity-to-geometry" matching. This paper generalizes the Pytiev morphological approach for obtaining the pure "geometry-to-geometry" matching techniques. The generalized intensity-geometrical correlation coefficient is proposed including the linear correlation coefficient and the square of Pytiev correlation coefficient as its partial cases. The morphological shape correlation coefficient is proposed based on the statistical averaging of images with the same shape. Centered morphological correlation coefficient is obtained under the condition of intensity centering of averaged images. Two types of symmetric geometrical normalized correlation coefficients are proposed for comparison of shape-tessellations. The technique for correlation and matching of shapes with ordered intensities is proposed with correlation measures invariant to monotonous intensity transformations. The quality of proposed geometrical correlation measures is experimentally estimated in the task of visual (TV) and infrared (IR) image matching. First experimental results demonstrate competitive quality and better computational performance relative to state-of-art mutual information measure.
LEARNING A COMPOSITIONAL REPRESENTATION FOR FACADE OBJECT CATEGORIZATION
Authors: Wenzel S. , Förstner W.
Published: October 2012

Abstract. Our objective is the categorization of the most dominant objects in facade images, like windows, entrances and balconies. In order to execute an image interpretation of complex scenes we need an interaction between low level bottom-up feature detection and highlevel inference from top-down. A top-down approach would use results of a bottom-up detection step as evidence for some high-level inference of scene interpretation. We present a statistically founded object categorization procedure that is suited for bottom-up object detection. Instead of choosing a bag of features in advance and learning models based on these features, it is more natural to learn which features best describe the target object classes. Therefore we learn increasingly complex aggregates of line junctions in image sections from man-made scenes. We present a method for the classification of image sections by using the histogram of diverse types of line aggregates.