bluuebunny/crossref_metadata_2025 huggingface dataset:
TREES DETECTION FROM LASER POINT CLOUDS ACQUIRED IN DENSE URBAN AREAS BY A MOBILE MAPPING SYSTEM
Authors: Monnier F. , Vallet B. , Soheilian B.
Published: October 2012

Abstract. 3D reconstruction of trees is of great interest in large-scale 3D city modelling. Laser scanners provide geometrically accurate 3D point clouds that are very useful for object recognition in complex urban scenes. Trees often cause important occlusions on building façades. Their recognition can lead to occlusion maps that are useful for many façade oriented applications such as visual based localisation and automatic image tagging. This paper proposes a pipeline to detect trees in point clouds acquired in dense urban areas with only laser informations (x,y, z coordinates and intensity). It is based on local geometric descriptors computed on each laser point using a determined neighbourhood. These descriptors describe the local shape of objects around every 3D laser point. A projection of these values on a 2D horizontal accumulation space followed by a combination of morphological filters provides individual tree clusters. The pipeline is evaluated and the results are presented on a set of one million laser points using a man made ground truth.
AN AUTOMATED METHOD FOR 3D ROOF OUTLINE GENERATION AND REGULARIZATION IN AIRBONE LASER SCANNER DATA
Authors: Perera S. N. , Nalani H. A. , Maas H.-G.
Published: October 2012

Abstract. In this paper, an automatic approach for the generation and regularization of 3D roof boundaries in Airborne Laser scanner data is presented. The workflow is commenced by segmentation of the point clouds. A classification step and a rule based roof extraction step are followed the planar segmentation. Refinement on roof extraction is performed in order to minimize the effect due to urban vegetation. Boundary points of the connected roof planes are extracted and fitted series of straight line segments. Each line is then regularized with respect to the dominant building orientation. We introduce the usage of cycle graphs for the best use of topological information. Ridge-lines and step-edges are basically extracted to recognise correct topological relationships among the roof faces. Inner roof corners are geometrically fitted based on the closed cycle graphs. Outer boundary is reconstructed using the same concept but with the outer most cycle graph. In here, union of the sub cycles is taken. Intermediate line segments (outer bounds) are intersected to reconstruct the roof eave lines. Two test areas with two different point densities are tested with the developed approach. Performance analysis of the test results is provided to demonstrate the applicability of the method.
A LINE-BASED 3D ROOF MODEL RECONSTRUCTION ALGORITHM: TIN-MERGING AND RESHAPING (TMR)
Authors: Rau J.-Y.
Published: October 2012

Abstract. Three-dimensional building model is one of the major components of a cyber-city and is vital for the realization of 3D GIS applications. In the last decade, the airborne laser scanning (ALS) data is widely used for 3D building model reconstruction and object extraction. Instead, based on 3D roof structural lines, this paper presents a novel algorithm for automatic roof models reconstruction. A line-based roof model reconstruction algorithm, called TIN-Merging and Reshaping (TMR), is proposed. The roof structural line, such as edges, eaves and ridges, can be measured manually from aerial stereo-pair, derived by feature line matching or inferred from ALS data. The originality of the TMR algorithm for 3D roof modelling is to perform geometric analysis and topology reconstruction among those unstructured lines and then reshapes the roof-type using elevation information from the 3D structural lines. For topology reconstruction, a line constrained Delaunay Triangulation algorithm is adopted where the input structural lines act as constraint and their vertex act as input points. Thus, the constructed TINs will not across the structural lines. Later at the stage of Merging, the shared edge between two TINs will be check if the original structural line exists. If not, those two TINs will be merged into a polygon. Iterative checking and merging of any two neighboured TINs/Polygons will result in roof polygons on the horizontal plane. Finally, at the Reshaping stage any two structural lines with fixed height will be used to adjust a planar function for the whole roof polygon. In case ALS data exist, the Reshaping stage can be simplified by adjusting the point cloud within the roof polygon. The proposed scheme reduces the complexity of 3D roof modelling and makes the modelling process easier. Five test datasets provided by ISPRS WG III/4 located at downtown Toronto, Canada and Vaihingen, Germany are used for experiment. The test sites cover high rise buildings and residential area with diverse roof type. For performance evaluation, the adopted roof structural lines are manually measured from the provided stereo-pair. Experimental results indicate a nearly 100% success rate for topology reconstruction was achieved provided that the 3D structural lines can be enclosed as polygons. On the other hand, the success rate at the Reshaping stage is dependent on the complexity of the rooftop structure. Thus, a visual inspection and semi-automatic adjustment of roof-type is suggested and implemented to complete the roof modelling. The results demonstrate that the proposed scheme is robust and reliable with a high degree of completeness, correctness, and quality, even when a group of connected buildings with multiple layers and mixed roof types is processed.
THE ISPRS BENCHMARK ON URBAN OBJECT CLASSIFICATION AND 3D BUILDING RECONSTRUCTION
Authors: Rottensteiner F. , Sohn G. , Jung J. , Gerke M. , Baillard C. , Benitez S. , Breitkopf U.
Published: October 2012

Abstract. For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of airborne image and laserscanner data, has been made available to the scientific community. Researchers were encouraged to submit results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current airborne sensor data, but also common problems of state-of-the-art methods.
DEVELOPING SPECIES SPECIFIC VEGETATION MAPS USING MULTI-SPECTRAL HYPERSPATIAL IMAGERY FROM UNMANNED AERIAL VEHICLES
Authors: Strecha C. , Fletcher A. , Lechner A. , Erskine P. , Fua P.
Published: October 2012

Abstract. In remote, rugged or sensitive environments ground based mapping for condition assessment of species is both time consuming and potentially destructive. The application of photogrammetric methods to generate multispectral imagery and surface models based on UAV imagery at appropriate temporal and spatial resolutions is described. This paper describes a novel method to combine processing of NIR and visible image sets to produce multiband orthoimages and DEM models from UAV imagery with traditional image location and orientation uncertainties. This work extends the capabilities of recently developed commercial software (Pix4UAV from Pix4D) to show that image sets of different modalities (visible and NIR) can be automatically combined to generate a 4 band orthoimage. Reconstruction initially uses all imagery sets (NIR and visible) to ensure all images are in the same reference frame such that a 4-band orthoimage can be created. We analyse the accuracy of this automatic process by using ground control points and an evaluation on the matching performance between images of different modalities is shown. By combining sub-decimetre multispectral imagery with high spatial resolution surface models and ground based observation it is possible to generate detailed maps of vegetation assemblages at the species level. Potential uses with other conservation monitoring are discussed.
OPTICAL FLOW FOR GLACIER MOTION ESTIMATION
Authors: Vogel C. , Bauder A. , Schindler K.
Published: October 2012

Abstract. Quantitative measurements of glacier flow over time are an important ingredient for glaciological research, for example to determine the mass balances and the evolution of glaciers. Measuring glacier flow in multi-temporal images involves the estimation of a dense set of corresponding points, which in turn define the flow vectors. Furthermore glaciers exhibit rather difficult radiometry, since their surface usually contains homogeneous areas as well as weak texture and contrast. To date glacier flow is usually observed by manually measuring a sparse set of correspondences, which is labor-intensive and often yields rather irregular point distributions, with the associated problems of interpolating over large areas. In the present work we propose to densely compute motion vectors at every pixel, by using recent robust methods for optic flow computation. Determining the optic flow, i.e. the dense deformation field between two images of a dynamic scene, has been a classic, long-standing research problem in computer vision and image processing. Sophisticated methods exist to optimally balance data fidelity with smoothness of the motion field. Depending on the strength of the local image gradients these methods yield a smooth trade-off between matching and interpolation, thereby avoiding the somewhat arbitrary decision which discrete anchor points to measure, while at the same time mitigating the problem of gross matching errors. We evaluate our method by comparing with manually measured point wise ground truth.
3D MODELLING AND ACCURACY ASSESSMENT OF GRANITE QUARRY USING UNMMANNED AERIAL VEHICLE
Authors: D. González-Aguilera  , J. Fernández-Hernández  , J. Mancera-Taboada  , P. Rodríguez-Gonzálvez  , D. Hernández-López  , B. Felipe-García  , I. Gozalo-Sanz  , B. Arias-Perez
Published: October 2012

Abstract. The unmanned aerial vehicles (UAVs) are automated systems whose main characteristic is that can be remotely piloted. This property is especially interesting in those civil engineering works in which the accuracy of the model is not reachable by common aerial or satellite systems, there is a difficult accessibility to the infrastructure due to location and geometry aspects, and the economic resources are limited. This paper aims to show the research, development and application of a UAV that will generate georeferenced spatial information at low cost, high quality, and high availability. In particular, a 3D modelling and accuracy assessment of granite quarry using UAV is applied. With regard to the image-based modelling pipeline, an automatic approach supported by open source tools is performed. The process encloses the well-known image-based modelling steps: calibration, extraction and matching of features; relative and absolute orientation of images and point cloud and surface generation. Beside this, an assessment of the final model accuracy is carried out by means of terrestrial laser scanner (TLS), imaging total station (ITS) and global navigation satellite system (GNSS) in order to ensure its validity. This step follows a twofold approach: (i) firstly, using singular check points to provide a dimensional control of the model and (ii) secondly, analyzing the level of agreement between the realitybased 3D model obtained from UAV and the generated with TLS. The main goal is to establish and validate an image-based modelling workflow using UAV technology which can be applied in the surveying and monitoring of different quarries.
MEMORY EFFICIENT SEMI-GLOBAL MATCHING
Authors: Hirschmüller H. , Buder M. , Ernst I.
Published: October 2012

Abstract. Semi-GlobalMatching (SGM) is a robust stereo method that has proven its usefulness in various applications ranging from aerial image matching to driver assistance systems. It supports pixelwise matching for maintaining sharp object boundaries and fine structures and can be implemented efficiently on different computation hardware. Furthermore, the method is not sensitive to the choice of parameters. The structure of the matching algorithm is well suited to be processed by highly paralleling hardware e.g. FPGAs and GPUs. The drawback of SGM is the temporary memory requirement that depends on the number of pixels and the disparity range. On the one hand this results in long idle times due to the bandwidth limitations of the external memory and on the other hand the capacity bounds are quickly reached. A full HD image with a size of 1920 × 1080 pixels and a disparity range of 512 pixels requires already 1 billion elements, which is at least several GB of RAM, depending on the element size, wich are not available at standard FPGA- and GPUboards. The novel memory efficient (eSGM) method is an advancement in which the amount of temporary memory only depends on the number of pixels and not on the disparity range. This permits matching of huge images in one piece and reduces the requirements of the memory bandwidth for real-time mobile robotics. The feature comes at the cost of 50% more compute operations as compared to SGM. This overhead is compensated by the previously idle compute logic within the FPGA and the GPU and therefore results in an overall performance increase. We show that eSGM produces the same high quality disparity images as SGM and demonstrate its performance both on an aerial image pair with 142 MPixel and within a real-time mobile robotic application. We have implemented the new method on the CPU, GPU and FPGA.We conclude that eSGM is advantageous for a GPU implementation and essential for an implementation on our FPGA.
AN EVALUATION OF FEATURE LEARNING METHODS FOR HIGH RESOLUTION IMAGE CLASSIFICATION
Authors: Tokarczyk P. , Montoya J. , Schindler K.
Published: October 2012

Abstract. Automatic image classification is one of the fundamental problems of remote sensing research. The classification problem is even more challenging in high-resolution images of urban areas, where the objects are small and heterogeneous. Two questions arise, namely which features to extract from the raw sensor data to capture the local radiometry and image structure at each pixel or segment, and which classification method to apply to the feature vectors. While classifiers are nowadays well understood, selecting the right features remains a largely empirical process. Here we concentrate on the features. Several methods are evaluated which allow one to learn suitable features from unlabelled image data by analysing the image statistics. In a comparative study, we evaluate unsupervised feature learning with different linear and non-linear learning methods, including principal component analysis (PCA) and deep belief networks (DBN). We also compare these automatically learned features with popular choices of ad-hoc features including raw intensity values, standard combinations like the NDVI, a few PCA channels, and texture filters. The comparison is done in a unified framework using the same images, the target classes, reference data and a Random Forest classifier.
DETECTION AND CORRECTION OF CHANGES IN EXTERIOR AND INTERIOR ORIENTATIONS WHILE ESTIMATING 3-D OBJECT DEFORMATIONS FROM MULTIPLE IMAGES WITH WEAK OR STRONG IMAGING GEOMETRY
Authors: Jokinen O. , Haggrén H.
Published: October 2012

Abstract. The paper deals with estimation of 3-D object deformation from multiple images initially in fixed positions with weak or strong imaging geometry. A new method is proposed to detect automatically if the exterior or interior orientations (rotations, translations, focal length, principal point) of one or several images have changed and which image or images contain the error, when the object deforms at the same time. The method is based on comparing novel feature vectors computed for each image from changes in the image coordinates of the object points and from residuals derived from the collinearity equations. Bundle adjustment is performed to simultaneously estimate the deformation of the object and to correct the changed orientations of the images. The rigidity needed in the weak case is obtained by approximating the deformation by a novel shape function containing parameters the values of which are estimated during adjustment. Test results with synthetic data show that even rather small changes in one orientation parameter of one image can be detected with high confidence. Weak imaging geometry allows to detect smaller changes than the strong one. The closer an initial approximation of deformation is available, the higher is the probability of correct detection. Subsequent correction of changed orientations and estimation of deformation may provide a high accuracy of 1:140000 of the object dimensions for both weak and strong imaging geometries, when the noise level in the image measurements is 0.1 pixel. Experiments with real data illustrate the good performance of the methods.
RELATIVE POSE ESTIMATION FROM AIRBORNE IMAGE SEQUENCES
Authors: Reize T. , Müller R. , Kurz F.
Published: October 2012

Abstract. We present a new relative pose estimation method for applications based on airborne image sequences. The performance of the method is tested using simulated test data, with correct and erroneous original conditions, as well as using real data. The calculated results obtained from real images are compared to the on-board measured angles. The results show that the proposed method is very precise and fast. Most matching algorithms are very computation time expensive mainly because they rely on RANSAC methods that need a lot of matching points. Due to the circumstance that only two corresponding points are necessary to solve the equation system, our technique doesn't need much computation time. Outliers are detected by a special back-matching technique. A method based on Polynomial Homotopy Continuation (PHC) is used to solve the complex polynomial equation system. The proposed pose solver method runs without SVD calculations, expensive minimisation or optimisation. Start parameters are not necessary. Furthermore, no a priori knowledge is required, besides focal length in pixel units and overlapping consecutive images. Outcomes are three relative orientation angles and a scaling parameter between two subsequent images, as well as displacement vectors in image pixel coordinate units. In addition, the PHC pose estimation method can balance small pixel errors. All these properties indicate the high applicability of the proposed method.
OPTIMAL CAMERA NETWORK DESIGN FOR 3D MODELING OF CULTURAL HERITAGE
Authors: Alsadik B. S. , Gerke M. , Vosselman G.
Published: October 2012

Abstract. Digital cultural heritage documentation in 3D is subject to research and practical applications nowadays. Image-based modeling is a technique to create 3D models, which starts with the basic task of designing the camera network. This task is – however – quite crucial in practical applications because it needs a thorough planning and a certain level of expertise and experience. Bearing in mind todays computational (mobile) power we think that the optimal camera network should be designed in the field, and, therefore, making the preprocessing and planning dispensable. The optimal camera network is designed when certain accuracy demands are fulfilled with a reasonable effort, namely keeping the number of camera shots at a minimum. In this study, we report on the development of an automatic method to design the optimum camera network for a given object of interest, focusing currently on buildings and statues. Starting from a rough point cloud derived from a video stream of object images, the initial configuration of the camera network assuming a high-resolution state-of-the-art non-metric camera is designed. To improve the image coverage and accuracy, we use a mathematical penalty method of optimization with constraints. From the experimental test, we found that, after optimization, the maximum coverage is attained beside a significant improvement of positional accuracy. Currently, we are working on a guiding system, to ensure, that the operator actually takes the desired images. Further next steps will include a reliable and detailed modeling of the object applying sophisticated dense matching techniques.
BUNDLE ADJUSTMENT FOR MULTI-CAMERA SYSTEMS WITH POINTS AT INFINITY
Authors: Schneider J. , Schindler F. , Läbe T. , Förstner W.
Published: October 2012

Abstract. We present a novel approach for a rigorous bundle adjustment for omnidirectional and multi-view cameras, which enables an efficient maximum-likelihood estimation with image and scene points at infinity. Multi-camera systems are used to increase the resolution, to combine cameras with different spectral sensitivities (Z/I DMC, Vexcel Ultracam) or – like omnidirectional cameras – to augment the effective aperture angle (Blom Pictometry, Rollei Panoscan Mark III). Additionally multi-camera systems gain in importance for the acquisition of complex 3D structures. For stabilizing camera orientations – especially rotations – one should generally use points at the horizon over long periods of time within the bundle adjustment that classical bundle adjustment programs are not capable of. We use a minimal representation of homogeneous coordinates for image and scene points. Instead of eliminating the scale factor of the homogeneous vectors by Euclidean normalization, we normalize the homogeneous coordinates spherically. This way we can use images of omnidirectional cameras with single-view point like fisheye cameras and scene points, which are far away or at infinity. We demonstrate the feasibility and the potential of our approach on real data taken with a single camera, the stereo camera FinePix Real 3D W3 from Fujifilm and the multi-camera system Ladybug 3 from Point Grey.
DEVELOPING AND TESTING A 3D CADASTRAL DATA MODEL A CASE STUDY IN AUSTRALIA
Authors: Aien A. , Kalantari M. , Rajabifard A. , Williamson I. P. , Shojaei D.
Published: October 2012

Abstract. Population growth, urbanization and industrialization place more pressure on land use with the need for increased space. To extend the use and functionality of the land, complex infrastructures are being built, both vertically and horizontally, layered and stacked. These three-dimensional (3D) developments affect the interests (Rights, Restrictions, and Responsibilities (RRRs)) attached to the underlying land. A 3D cadastre will assist in managing the effects of 3D development on a particular extent of land. There are many elements that contribute to developing a 3D cadastre, such as existing of 3D property legislations, 3D DBMS, 3D visualization. However, data modelling is one of the most important elements of a successful 3D cadastre. As architectural models of houses and high rise buildings help their users visualize the final product, 3D cadastre data model supports 3D cadastre users to understand the structure or behavior of the system and has a template that guides them to construct and implement the 3D cadastre. Many jurisdictions, organizations and software developers have built their own cadastral data model. Land Administration Domain Model (DIS-ISO 19152, The Netherlands) and ePlan (Intergovernmental Committee on Surveying and Mapping, Australia) are examples of existing data models. The variation between these data models is the result of different attitudes towards cadastres. However, there is a basic common thread among them all. Current cadastral data models use a 2D land-parcel concept and extend it to support 3D requirements. These data models cannot adequately manage and represent the spatial extent of 3D RRRs. Most of the current cadastral data models have been influenced by a very broad understanding of 3D cadastral concepts because better clarity in what needs to be represented and analysed in the cadastre needs to be established. This paper presents the first version of a 3D Cadastral Data Model (3DCDM_Version 1.0). 3DCDM models both the legal and physical extent of 3D properties and associated interests. The data model extends the traditional cadastral requirements to cover other applications such as urban planning and land valuation and taxation. A demonstration of a test system on the proposed data model is also presented. The test is based on a case study in Victoria, Australia to evaluate the effectiveness of the data model.
CHARACTERISING UPLAND SWAMPS USING OBJECT-BASED CLASSIFICATION METHODS AND HYPER-SPATIAL RESOLUTION IMAGERY DERIVED FROM AN UNMANNED AERIAL VEHICLE
Authors: Lechner A. M. , Fletcher A. , Johansen K. , Erskine P.
Published: October 2012

Abstract. Subsidence, resulting from underground coal mining can alter the structure of overlying rock formations changing hydrological conditions and potentially effecting ecological communities found on the surface. Of particular concern are impacts to endangered and/or protected swamp communities and swamp species sensitive to changes in hydrologic conditions. This paper describes a monitoring approach that uses UAVs with modified digital cameras and object-based image analysis methods to characterise swamp landcover on the Newnes plateau in the Blue Mountains near Sydney, Australia. The characterisation of swamp spatial distribution is key to identifying long term changes in swamp condition. In this paper we describe i) the characteristics of the UAV and the sensor, ii) the pre-processing of the remote sensing data with sub-decimeter pixel size to derive visible and near infrared multispectral imagery and a digital surface model (DSM), and iii) the application of object-based image analysis in eCognition using the multi-spectral data and DSM to map swamp extent. Finally, we conclude with a discussion of the potential application of remote sensing data derived from UAVs to conduct environmental monitoring.
THE APPLICATION OF DIGITAL LINE GRAPHS AND MAP IN THE NETWORK ENVIRONMENT
Authors: Guo X. , Zhang B. , Yu J. , Ran H. , Wang L.
Published: October 2012

Abstract. WebGIS is an important research field in GIS. W3C organization established SVG standard, which laid a foundation for WebGIS based on vector data. In China, Digital Line Graphs(DLG) is a significant GIS product and it has been used in many medium and large WebGIS system. Geographic information-portrayal is the common method of DLG visualization. However, the inherent characteristics of Geographic information-portrayal may lead to a relatively higher data production input, still, the visualization effect is not ideal. We put forward a new product named Digital Line Graphs and Map(DLGM), which consists of DLG and DLG's cartographic presentation data. It provides visualization data based on the cartographic standards. Due to the manufacture and management of DLGM data that are independent from software and platform, its data can be used in many fields. Network application is one of them. This paper is to use DLGM in the network applications. First it reveals the connotation and characteristics of DLGM then analyses the model that DLGM organizes, manages DLG and map symbol data. After that, combined with SVG standards, we put forward DLGM’s SVG encoding method without any information loss. Finally we provide a web map system based on local area network by using 1：10000 DLGM data of a certain area. Based on this study, we conclude that DLGM can be used in the network environment providing high quality DLG and cartographic data for WebGIS.
TOWARDS THEMATIC WEB SERVICES FOR GENERIC DATA VISUALIZATION AND ANALYSIS
Authors: Horanont T. , Basa M. , Shibasaki R.
Published: October 2012

Abstract. Spatial analysis packages and thematic mapping are available in a number of traditional desktop GIS. However, visualizing thematic maps through the Internet is still limited to fix contents and restrict changes of the input data. The users with limited GIS knowledge or people who do not own digital map data are normally having difficulties to create output thematic maps from generic data. In this study, we developed thematic mapping services that can be applied to non-spatial data format served through powerful map services solutions. Novice users who have no GIS software experience or have no digital base map can simply input a plain text file with location identifier field such as place name or gazetteer to generate thematic maps online. We implemented a prototype by using web service standards recommended by the Open Geospatial Consortium (OGC) such as Web Map Service (WMS), Web Feature Service (WFS) and Styled Layer Descriptor (SLD) to provide a principle for communication and allow users to visualize spatial information as thematic maps. The system dedicates a great deal of effort to the initial study of geospatial analysis and visualization for novice users including those with no past experience using Geographic Information Systems.
A GEOSPATIAL WEB SERVICES COMPOSITION FRAMEWORK SUPPORTING REAL-TIME STATUS MONITORING
Authors: You L. , Gui Z. , Guo W. , Shen S. , Wu H.
Published: October 2012

Abstract. Geospatial web services composition becomes one of the main solutions for complex computing in the GIS realm with the development of information interoperability and advanced IT technologies. Standard geospatial web services only have two simple statuses: success or failure. However the procedures for geospatial information processing and analysis always feature intensive data, complex computation, and long processing times. Thus, standard geospatial web services composition only provides basic functions and cannot fully satisfy geospatial information processing and analysis needs. The problems with standard geospatial web services are numerous, including difficulties in controlling and monitoring geospatial web services, composition optimization, and error tracking. The execution status of geospatial web services composition must be monitored becoming the basis for further optimization of the geospatial web services composition model. This paper proposes a framework for geospatial web service composition that supports real-time status monitoring. This framework effectively integrates geospatial web services with status interfaces and dynamic monitoring technology. Experiments show that this framework can effectively monitor execution information, reminding users of bottleneck information thus providing the foundation for further improvements in the model's execution efficiency.
THE USE OF SATELLITE IMAGERY TO GUIDE FIELD PLOT SAMPLING SCHEME FOR BIOMASS ESTIMATION IN GHANAIAN FOREST
Authors: Sah B. P. , Hämäläinen J. M. , Sah A. K. , Honji K. , Foli E. G. , Awudi C.
Published: October 2012

Abstract. Accurate and reliable estimation of biomass in tropical forest has been a challenging task because a large proportion of forests are difficult to access or inaccessible. So, for effective implementation of REDD+ and fair benefit sharing, the proper designing of field plot sampling schemes plays a significant role in achieving robust biomass estimation. The existing forest inventory protocols using various field plot sampling schemes, including FAO's regular grid concept of sampling for land cover inventory at national level, are time and human resource intensive. Wall to wall LiDAR scanning is, however, a better approach to assess biomass with high precision and spatial resolution even though this approach suffers from high costs. Considering the above, in this study a sampling design based on a LiDAR strips sampling scheme has been devised for Ghanaian forests to support field plot sampling. Using Top-of-Atmosphere (TOA) reflectance value of satellite data, Land Use classification was carried out in accordance with IPCC definitions and the resulting classes were further stratified, incorporating existing GIS data of ecological zones in the study area. Employing this result, LiDAR sampling strips were allocated using systematic sampling techniques. The resulting LiDAR strips represented all forest categories, as well as other Land Use classes, with their distribution adequately representing the areal share of each category. In this way, out of at total area of 15,153km2 of the study area, LiDAR scanning was required for only 770 km2 (sampling intensity being 5.1%). We conclude that this systematic LiDAR sampling design is likely to adequately cover variation in above-ground biomass densities and serve as sufficient a-priori data, together with the Land Use classification produced, for designing efficient field plot sampling over the seven ecological zones.
THE USE OF LIDAR AND VOLUNTEERED GEOGRAPHIC INFORMATION TO MAP FLOOD EXTENTS AND INUNDATION
Authors: McDougall K. , Temple-Watts P.
Published: October 2012

Abstract. Floods are one of the most destructive natural disasters that threaten communities and properties. In recent decades, flooding has claimed more lives, destroyed more houses and ruined more agricultural land than any other natural hazard. The accurate prediction of the areas of inundation from flooding is critical to saving lives and property, but relies heavily on accurate digital elevation and hydrologic models. The 2011 Brisbane floods provided a unique opportunity to capture high resolution digital aerial imagery as the floods neared their peak, allowing the capture of areas of inundation over the various city suburbs. This high quality imagery, together with accurate LiDAR data over the area and publically available volunteered geographic imagery through repositories such as Flickr, enabled the reconstruction of flood extents and the assessment of both area and depth of inundation for the assessment of damage. In this study, approximately 20 images of flood damaged properties were utilised to identify the peak of the flood. Accurate position and height values were determined through the use of RTK GPS and conventional survey methods. This information was then utilised in conjunction with river gauge information to generate a digital flood surface. The LiDAR generated DEM was then intersected with the flood surface to reconstruct the area of inundation. The model determined areas of inundation were then compared to the mapped flood extent from the high resolution digital imagery to assess the accuracy of the process. The paper concludes that accurate flood extent prediction or mapping is possible through this method, although its accuracy is dependent on the number and location of sampled points. The utilisation of LiDAR generated DEMs and DSMs can also provide an excellent mechanism to estimate depths of inundation and hence flood damage
AUTOMATED MOUNTING BIAS CALIBRATION FOR AIRBORNE LIDAR SYSTEM
Authors: Zhang J. , Jiang W. , Jiang S.
Published: October 2012

Abstract. Mounting bias is the major error source of Airborne LIDAR system. In this paper, an automated calibration method for estimating LIDAR system mounting parameters is introduced. LIDAR direct geo-referencing model is used to calculate systematic errors. Due to LIDAR footprints discretely sampled, the real corresponding laser points are hardly existence among different strips. The traditional corresponding point methodology does not seem to apply to LIDAR strip registration. We proposed a Virtual Corresponding Point Model to resolve the corresponding problem among discrete laser points. Each VCPM contains a corresponding point and three real laser footprints. Two rules are defined to calculate tie point coordinate from real laser footprints. The Scale Invariant Feature Transform (SIFT) is used to extract corresponding points in LIDAR strips, and the automatic flow of LIDAR system calibration based on VCPM is detailed described. The practical examples illustrate the feasibility and effectiveness of the proposed calibration method.
QTRAJECTORIES: IMPROVING THE QUALITY OF OBJECT TRACKING USING SELF-ORGANIZING CAMERA NETWORKS
Authors: Jaenen U. , Feuerhake U. , Klinger T. , Muhle D. , Haehner J. , Sester M. , Heipke C.
Published: October 2012

Abstract. Previous work in the research field of video surveillance intensively focused on separated aspects of object detection, data association, pattern recognition and system design. In contrast, we propose a holistic approach for object tracking in a self-organizing and distributed smart camera network. Each observation task is represented by a software-agent which improves the tracking performance by collaborative behavior. An object tracking agent detects persons in a video stream and associates them with a trajectory. The pattern recognition agent analyses these trajectories by detecting points of interest within the observation field. These are characterized by a non-deterministic behavior of the moving person. The trajectory points (enriched by the results of the pattern recognition agent) will be used by a configuration agent to align the cameras field of view. We show that this collaboration improves the performance of the observation system by increasing the amount of detected trajectory points by 22%.
FEATURE POSITIONING ON GOOGLE STREET VIEW PANORAMAS
Authors: Tsai V. J. D. , Chang C.-T.
Published: October 2012

Abstract. Location-based services (LBS) on web-based maps and images have come into real-time since Google launched its Street View imaging services in 2007. This research employs Google Maps API and Web Service, GAE for JAVA, AJAX, Proj4js, CSS and HTML in developing an internet platform for accessing the orientation parameters of Google Street View (GSV) panoramas in order to determine the three dimensional position of interest features that appear on two overlapping panoramas by geometric intersection. A pair of GSV panoramas was examined using known points located on the Library Building of National Chung Hsing University (NCHU) with the root-mean-squared errors of ±0.522m, ±1.230m, and ±5.779m for intersection and ±0.142m, ±1.558m, and ±5.733m for resection in X, Y, and h (elevation), respectively. Potential error sources in GSV positioning were analyzed and illustrated that the errors in Google provided GSV positional parameters dominate the errors in geometric intersection. The developed system is suitable for data collection in establishing LBS applications integrated with Google Maps and Google Earth in traffic sign and infrastructure inventory by adding automatic extraction and matching techniques for points of interest (POI) from GSV panoramas.
AUTOMATED MODELING OF 3D BUILDING ROOFS USING IMAGE AND LIDAR DATA
Authors: Demir N. , Baltsavias E.
Published: October 2012

Abstract. In this work, an automated approach for 3D building roof modelling is presented. The method consists of two main parts, namely roof detection and 3D geometric modelling. For the detection, a combined approach of four methods achieved the best results, using slope-based DSM filtering as well as classification of multispectral images, elevation data and vertical LiDAR point density. In the evaluation, the combination of the four methods yields 94% correct detection at an omission error of 12%. Roof modelling is done by plane detection with RANSAC, followed by geometric refinement and merging of neighbouring segments to clean up oversegmentation. Walls are then detected and excluded, and the roof shapes are vectorised with the alpha-shape method. The resulting polygons are refined using 3D straight edges reconstructed by automatic straight edge extraction and matching, as well as 3D corner points constructed by intersection of the 3D edges. The results are quantitatively assessed by comparing to ground truth manually extracted from high-quality images, using several metrics for both the correctness and completeness of the roof polygons and for their geometric accuracy. The median value of correctness of the roof polygons is calculated as 96%, while the median value of completeness is 88%.
EXTRACTION OF SPATIAL PARAMETERS FROM CLASSIFIED LIDAR DATA AND AERIAL PHOTOGRAPH FOR SOUND MODELING
Authors: Biswas S. , Lohani B.
Published: October 2012

Abstract. Prediction of outdoor sound levels in 3D space is important for noise management, soundscaping etc. Sound levels at outdoor can be predicted using sound propagation models which need terrain parameters. The existing practices of incorporating terrain parameters into models are often limited due to inadequate data or inability to determine accurate sound transmission paths through a terrain. This leads to poor accuracy in modelling. LIDAR data and Aerial Photograph (or Satellite Images) provide opportunity to incorporate high resolution data into sound models. To realize this, identification of building and other objects and their use for extraction of terrain parameters are fundamental. However, development of a suitable technique, to incorporate terrain parameters from classified LIDAR data and Aerial Photograph, for sound modelling is a challenge. Determination of terrain parameters along various transmission paths of sound from sound source to a receiver becomes very complex in an urban environment due to the presence of varied and complex urban features. This paper presents a technique to identify the principal paths through which sound transmits from source to receiver. Further, the identified principal paths are incorporated inside the sound model for sound prediction. Techniques based on plane cutting and line tracing are developed for determining principal paths and terrain parameters, which use various information, e.g., building corner and edges, triangulated ground, tree points and locations of source and receiver. The techniques developed are validated through a field experiment. Finally efficacy of the proposed technique is demonstrated by developing a noise map for a test site.
A COMPARISON OF ACCURACIES OF THE RPC MODELS: HOMO- AND HETERO-TYPE STEREO PAIRS OF GEOEYE AND WORLDVIEW IMAGES
Authors: Choi S. Y. , Kang J. M. , Shin D. S.
Published: October 2012

Abstract. We investigated the accuracy in three dimensional geo-positioning derived by two homo-type stereo pairs and four hetero-type stereo pairs of high resolution satellite images using the vendor-provided rational polynomial coefficients (RPC) in this research. The results of 3D geo-positioning from six different stereo combinations were assessed with seventeen GPS points which were commonly well distributed in the scenes. Recently, satellite image vendors provide homo-type stereo pair images taken by the same sensor during a short time period. Stereo pair images have good geometry for achieving accurate ground coordinates. However it is difficult to acquire them at the request time because of the revisit time of the satellite and current weather conditions. Due to these reasons, a new methodology using hetero-type stereo pairs has been suggested to derive ground coordinates. High resolution satellite images include the rational function model in the form of RPC which represents the relationship between the image coordinates and object coordinates with rational polynomials. RPC makes it fast, accurate, and simple to calculate ground coordinates without any exterior orientation parameters of satellites. We constituted six different stereo pairs from four images of GeoEye-1 in-track stereo pair images and WorldView-2 in-track stereo pair images which were collected for the same region (17.5 km x 10.0 km) of the west coast in Korea. We collected GCPs by differential GPS surveying. The ground coordinates derived from six different pairs without and with some GCPs were compared to all GPS points respectively. The accuracy of ground coordinates from hetero-type stereo pairs is equivalent to the accuracy from homo-type stereo pairs. This research demonstrates that we can achieve comparatively accurate ground coordinates without GCPs using any stereo combinations of images containing proper RPCs, although we don't have in-track stereo pair images. Furthermore, some proper combinations of images with GCPs can improve the positioning accuracy.
A CLASS OF REGRESSION-CUM-RATIO ESTIMATORS IN TWO-PHASE SAMPLING FOR UTILIZING INFORMATION FROM HIGH RESOLUTION SATELLITE DATA
Authors: Handique B. K.
Published: October 2012

Abstract. Two-phase sampling design offers a variety of possibilities for effective use of auxiliary information such as those from high resolution remote sensing data. Continuous satellite data with large area coverage provide scope for deriving population values of the auxiliary variables, which can effectively be used for estimating the population parameters of the variable of interest. This study has been made to examine the possibilities of different forms of auxiliary information derived from remote sensing data in two-phase sampling design and suggest an appropriate estimator that will be of broad interest and applications. A new class of regression-cum-ratio estimators has been proposed for two-phase sampling using information on two auxiliary variables derived from high resolution satellite data. The bias and the mean square error (MSE) of the proposed estimators have been obtained up to first order approximation. Efficiency comparison of the proposed estimators has been made with some traditional estimators. The proposed estimator is found to be more efficient than the usual regression and ratio estimators. Numerical illustration has been carried out to examine the efficiency of the estimator in case of forest timber volume estimation utilizing tree crown diameter and tree height as auxiliary variables. It is shown that these estimators can be employed in a variety of conditions where there is strong correlation of satellite derived information with sample based ground measurements and when the cost of ground measurements is relatively high.
MEDIUM-FORMAT CAMERAS AND THEIR USE IN TOPOGRAPHIC MAPPING
Authors: Höhle J.
Published: October 2012

Abstract. Based on practical experiences with large-format aerial cameras the impact of new medium-format digital cameras on topographic mapping tasks is discussed. Two new medium-format cameras are investigated with respect to elevation accuracy, area coverage and image quality. The produced graphs and tables show the potential of these cameras for general mapping tasks. Special attention is given to the image quality of the selected cameras. Applications for the medium-format cameras are discussed. The necessary tools for selected applications are described. The impact of sensors for georeferencing, multi-spectral images, and new matching algo-rithms is also dealt with. Practical investigations are carried out for the production of digital elevation models. A comparison with large-format frame cameras is carried out. It is concluded that the medium-format cameras have a potential for mapping of smaller areas and will be used in future in true orthoimage production, corridor mapping, and updating of maps. Their small dimensions and low weight allow installation in small airplanes, helicopters, and high-end UAVs. The two investigated medium-format cameras are low-cost alternatives for standard mapping tasks and special applications. The detection of changes in topographic databases and DTMs can be carried out by means of those medium-format cameras which can image the same area in four bands of the visible and invisible spectrum of light. Medium-format cameras will play an important role in future mapping tasks.