bluuebunny/crossref_metadata_2025 huggingface dataset:
TOWARD AUTOMATED FAÇADE TEXTURE GENERATION FOR 3D PHOTOREALISTIC CITY MODELLING WITH SMARTPHONES OR TABLET PCS
Authors: Wang S.
Published: August 2012

Abstract. An automated model-image fitting algorithm is proposed in this paper for generating façade texture image from pictures taken by smartphones or tablet PCs. The façade texture generation requires tremendous labour work and thus, has been the bottleneck of 3D photo-realistic city modelling. With advanced developments of the micro electro mechanical system (MEMS), camera, global positioning system (GPS), and gyroscope (G-sensors) can all be integrated into a smartphone or a table PC. These sensors bring the possibility of direct-georeferencing for the pictures taken by smartphones or tablet PCs. Since the accuracy of these sensors cannot compared to the surveying instruments, the image position and orientation derived from these sensors are not capable of photogrammetric measurements. This paper adopted the least-squares model-image fitting (LSMIF) algorithm to iteratively improve the image's exterior orientation. The image position from GPS and the image orientation from gyroscope are treated as the initial values. By fitting the projection of the wireframe model to the extracted edge pixels on image, the image exterior orientation elements are solved when the optimal fitting achieved. With the exact exterior orientation elements, the wireframe model of the building can be correctly projected on the image and, therefore, the façade texture image can be extracted from the picture.
AUTOMATIC EXTRACTION OF BUILDING ROOFS FROM PICTOMETRY'S ORTHOGONAL AND OBLIQUE IMAGES
Authors: Wang Y.
Published: August 2012

Abstract. Automatic extraction of buildings from digital images aims at detection of buildings from digital images and reconstruction of roof structure automatically. At Pictometry, more than 30 million images are captured every year and how to extract the useful information of objects on the ground from the existing image library for various applications is a big challenge we face now. In this paper, an automatic approach for extraction of building roof from digital orthogonal and oblique imagery is proposed. The proposed method uses image processing technique to derive the accurate 3D structure of building roof for accurate roof measurement, 3D modeling, computation of building footprints, etc. It consists of three major steps, i.e. extraction of roof corner and ridge points from the images, automatic matching of roof corner and ridge points between orthogonal and oblique images and grouping of the matched roof points to create roof facets. In this study, the modified Moravec operator is used to extract feature points from digital images. To find roof points which cannot be extracted by the point extractor, edge information is also extracted. Due to the nature of roof points, especially corner points and the difference between orthogonal and oblique images, a feature-based image matching technique is used to derive 3D information of roof corner and ridge points, instead of area-based matching. To match roof points correctly, edges associated with a corner or ridge point and their properties are used. After 3D roof points are generated, roof points belonging to the same roof facet are grouped together by using their spatial relations. Once points belonging to the same facet are found, a surface is fitted to the points and outliers can be removed during this process.
PRIMITIVE-BASED 3D BUILDING RECONSTRUCTION METHOD TESTED BY REFERENCE AIRBORNE DATA
Authors: Zhang W. , Chen Y. , Yan K. , Yan G. , Zhou G.
Published: August 2012

Abstract. Airborne LiDAR data and optical imagery are two datasets used for 3D building reconstruction. By study of the complementarities of these two datasets, we proposed a primitive-based 3D building reconstruction method, which can use LiDAR data and optical imagery at the same time. The proposed method comprises following steps: (1) recognize primitives from LiDAR point cloud and roughly measure primitives’ parameters as initial values, and (2) select primitives' features on the imagery, and (3) optimize primitives' parameters by the constraints of LiDAR point cloud and imagery, and (4) represent 3D building model by these optimized primitives. Compared with other model-based or CSG-based methods, the proposed method has some advantages. It is simpler, because it only uses the most straightforward features, i.e. planes of LiDAR point cloud and points of optical imagery. And it can tightly integrate LiDAR point cloud and optical imagery, that is to say, all primitives' parameters are optimized with all constraints in one step. Recently, an ISPRS Test Project on Urban Classification and 3D Building Reconstruction was launched, two datasets both with airborne LiDAR data and images are provided. The proposed method was applied to Area 3 of Dataset 1 Vaihingen, in which there are some buildings with plane roofs or gable roofs. The organizer of this test project evaluated the submitted reconstructed 3D model using reference data. The result shows the feasibility of the proposed 3D building reconstruction method.
PERSISTENT OBJECT TRACKING WITH RANDOMIZED FORESTS
Authors: Klinger T. , Muhle D.
Published: August 2012

Abstract. Our work addresses the problem of long-term visual people tracking in complex environments. Tracking a varying number of objects entails the problem of associating detected objects to tracked targets. To overcome the data association problem, we apply a Tracking-by-Detection strategy that uses Randomized Forests as a classifier together with a Kalman filter. Randomized Forests build a strong classifier for multi-class problems through aggregating simple decision trees. Due to their modular setup, Randomized Forests can be built incrementally, which makes them useful for unsupervised learning of object features in real-time. New training samples can be incorporated on the fly, while not drifting away from previously learnt features. To support further analysis of the automatically generated trajectories, we annotate them with quality metrics based on the association confidence. To build the metrics we analyse the confidence values that derive from the Randomized Forests and the similarity of detected and tracked objects. We evaluate the performance of the overall approach with respect to available reference data of people crossing the scene.
MAPPING MAJOR CROPPING PATTERNS IN SOUTHEAST ASIA FROM MODIS DATA USING WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORKS
Authors: Son N. T. , Chen C. F. , Cru C. R.
Published: August 2012

Abstract. Agriculture is one of the most important sectors in the economy of Southeast Asia countries, especially Thailand and Vietnam. These two countries have been the largest rice suppliers in the world and played a critical role in global food security. Yearly rice crop monitoring to provide policymakers with information on rice growing areas is thus important to timely devise plans to ensure food security. This study aimed to develop an approach for regional mapping of cropping patterns from time-series MODIS data. Data were processed through three steps: (1) noise filtering of time-series MODIS NDVI data with wavelet transform, (2) image classification of cropping patterns using artificial neural networks (ANNs), and (3) classification accuracy assessment using ground reference data. The results by a comparison between classification map and ground reference data indicated the overall accuracy of 80.3% and Kappa coefficient of 0.76.
USING STEREO VISION TO SUPPORT THE AUTOMATED ANALYSIS OF SURVEILLANCE VIDEOS
Authors: Menze M. , Muhle D.
Published: August 2012

Abstract. Video surveillance systems are no longer a collection of independent cameras, manually controlled by human operators. Instead, smart sensor networks are developed, able to fulfil certain tasks on their own and thus supporting security personnel by automated analyses. One well-known task is the derivation of people’s positions on a given ground plane from monocular video footage. An improved accuracy for the ground position as well as a more detailed representation of single salient people can be expected from a stereoscopic processing of overlapping views. Related work mostly relies on dedicated stereo devices or camera pairs with a small baseline. While this set-up is helpful for the essential step of image matching, the high accuracy potential of a wide baseline and the according good intersection geometry is not utilised. In this paper we present a stereoscopic approach, working on overlapping views of standard pan-tilt-zoom cameras which can easily be generated for arbitrary points of interest by an appropriate reconfiguration of parts of a sensor network. Experiments are conducted on realistic surveillance footage to show the potential of the suggested approach and to investigate the influence of different baselines on the quality of the derived surface model. Promising estimations of people’s position and height are retrieved. Although standard matching approaches show helpful results, future work will incorporate temporal dependencies available from image sequences in order to reduce computational effort and improve the derived level of detail.
FEATURE-BASED DIGITAL WATERMARKING FOR REMOTE SENSING IMAGES
Authors: Hsu P.-H. , Chen C.-C.
Published: August 2012

Abstract. With the rapid development of information and communication technology, people can acquire and distribute many kinds of digital data more conveniently than before. The consequence is that the "copyright protection" which prevents digital data from been duplicated illegally should be paid much more attention. Digital watermarking is the process of embedding visible or invisible information into a digital signal which may be used to verify its authenticity or the identity of its owners. In the past, digital watermarking technology has been successfully applied to the "copyright protection" of multimedia data, however the researches and applications of applying digital watermarking to geo-information data are still very inadequate. In this study, a novel digital watermarking algorithm based on the scale-space feature points is applied to the remote sensing images, and the robustness of the embedded digital watermark and the impact on satellite image quality are evaluated and analysed. This kind of feature points are commonly invariant to Image rotation, scaling and translation, therefore they naturally fit into the requirement of geometrically robust image watermarking. The experiment results show almost all extracted watermarks have high values of normal correlation and can be recognized clearly after the processing of image compression, brightness adjustment and contrast adjustment. In addition, most of the extracted watermarks are identified after the geometric attacks. Furthermore, the unsupervised image classification is implemented on the watermarked images to evaluate the image quality reduction and the results show that classification accuracy is affected slightly after embedding watermarks into the satellite images.
MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION
Authors: Liu X. , Yu Q. , Zhang X. , Shang Y. , Zhu X. , Lei Z.
Published: August 2012

Abstract. Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP) and Local Weighted Amplitude (LWA), are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM) is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the Local Frequency Response Vectors (LFRV), Phase Congruence (PC), and Four Directional-Derivative-Energy Image (FDDEI), especially when there is a low signal-to-noise ratio (SNR). As few assumptions are made, our proposed method can foreseeably be used in a wide variety of image-matching applications.
SPECTRAL REGRESSION DISCRIMINANT ANALYSIS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Authors: Pan Y. , Wu J. , Huang H. , Liu J.
Published: August 2012

Abstract. Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.
ITERATIVE DETERMINATION OF CAMERA POSE FROM LINE FEATURES
Authors: Zhang X. , Sun X. , Yuan Y. , Zhu Z. , Yu Q.
Published: August 2012

Abstract. we present an accurate and efficient solution for pose estimation from line features. By introducing coplanarity errors, we formulate the objective functions in terms of distances in the 3D scene space, and use different optimization strategies to find the best rotation and translation. Experiments show that the algorithm has strong robustness to noise and outliers, and that it can attain very accurate results efficiently.
ULTRAMAP V3 – A REVOLUTION IN AERIAL PHOTOGRAMMETRY
Authors: Reitinger B. , Sormann M. , Zebedin L. , Schachinger B. , Hoefler M. , Tomasi R. , Lamperter M. , Gruber B. , Schiester G. , Kobald M. , Unger M. , Klaus A. , Bernoegger S. , Karner K. , Wiechert A. , Ponticelli M. , Gruber M.
Published: August 2012

Abstract. In the last years, Microsoft has driven innovation in the aerial photogrammetry community. Besides the market leading camera technology, UltraMap has grown to an outstanding photogrammetric workflow system which enables users to effectively work with large digital aerial image blocks in a highly automated way. Best example is the project-based color balancing approach which automatically balances images to a homogeneous block. UltraMap V3 continues innovation, and offers a revolution in terms of ortho processing. A fully automated dense matching module strives for high precision digital surface models (DSMs) which are calculated either on CPUs or on GPUs using a distributed processing framework. By applying constrained filtering algorithms, a digital terrain model can be derived which in turn can be used for fully automated traditional ortho texturing. By having the knowledge about the underlying geometry, seamlines can be generated automatically by applying cost functions in order to minimize visual disturbing artifacts. By exploiting the generated DSM information, a DSMOrtho is created using the balanced input images. Again, seamlines are detected automatically resulting in an automatically balanced ortho mosaic. Interactive block-based radiometric adjustments lead to a high quality ortho product based on UltraCam imagery. UltraMap v3 is the first fully integrated and interactive solution for supporting UltraCam images at best in order to deliver DSM and ortho imagery.
IMPLEMENTATION OF THE DISTRIBUTED PARALLEL PROGRAM FOR GEOID HEIGHTS COMPUTATION USING MPI AND OPENMP
Authors: Lee S. , Kim J. , Jung Y. , Choi J. , Choi C.
Published: August 2012

Abstract. Much research have been carried out using optimization algorithms for developing high-performance program, under the parallel computing environment with the evolution of the computer hardware technology such as dual-core processor and so on. Then, the studies by the parallel computing in geodesy and surveying fields are not so many. The present study aims to reduce running time for the geoid heights computation and carrying out least-squares collocation to improve its accuracy using distributed parallel technology. A distributed parallel program was developed in which a multi-core CPU-based PC cluster was adopted using MPI and OpenMP library. Geoid heights were calculated by the spherical harmonic analysis using the earth geopotential model of the National Geospatial-Intelligence Agency(2008). The geoid heights around the Korean Peninsula were calculated and tested in diskless-based PC cluster environment. As results, for the computing geoid heights by a earth geopotential model, the distributed parallel program was confirmed more effective to reduce the computational time compared to the sequential program.
DEVELOPMENT OF A SERVICE ORIENTED ARCHITECTURE BASED GEOGRAPHIC INFORMATION SYSTEM IN EARTH SCIENCES
Authors: Toz G. , Dogru A.
Published: August 2012

Abstract. The studies of recent crustal movements are based on analyses of repeated geodetic measurements, and their combination with results of geophysical and geological investigations. It is obvious that a single data producer can not produce useful datasets and information without integrating data from others because one scientist’s results become another’s data. So, the problem to be solved naturally has an interdisciplinary character. However, Earth scientists traditionally work on one aspect of the problem and they have a tradition of sharing of data but they are willing to share it if asked. Because of this, the resources are being wasted in duplicative efforts. However, the goal is for data to evolve it into information, and then into knowledge as quickly and effectively as possible. In order to do this, calculations and analysis need to bring to the desktops of researchers, decision-makers, and educators. The aim of this study is to develop a service-oriented architecture (SOA) based Geographic Information System (GIS) that enables linking and sharing multidisciplinary Earth science data, tools, and software and to provide a wide range of users access to the system and in this way to build an easy-to-use interactive access to data and analysis environment to study earthquakes in Turkey.
DATA UPDATING METHODS FOR SPATIAL DATA INFRASTRUCTURE THAT MAINTAIN INFRASTRUCTURE QUALITY AND ENABLE ITS SUSTAINABLE OPERATION
Authors: Murakami S. , Takemoto T. , Ito Y.
Published: August 2012

Abstract. The Japanese government, local governments and businesses are working closely together to establish spatial data infrastructures in accordance with the Basic Act on the Advancement of Utilizing Geospatial Information (NSDI Act established in August 2007). Spatial data infrastructures are urgently required not only to accelerate computerization of the public administration, but also to help restoration and reconstruction of the areas struck by the East Japan Great Earthquake and future disaster prevention and reduction. For construction of a spatial data infrastructure, various guidelines have been formulated. But after an infrastructure is constructed, there is a problem of maintaining it. In one case, an organization updates its spatial data only once every several years because of budget problems. Departments and sections update the data on their own without careful consideration. That upsets the quality control of the entire data system and the system loses integrity, which is crucial to a spatial data infrastructure. To ensure quality, ideally, it is desirable to update data of the entire area every year. But, that is virtually impossible, considering the recent budget crunch. The method we suggest is to update spatial data items of higher importance only in order to maintain quality, not updating all the items across the board. We have explored a method of partially updating the data of these two geographical features while ensuring the accuracy of locations. Using this method, data on roads and buildings that greatly change with time can be updated almost in real time or at least within a year. The method will help increase the availability of a spatial data infrastructure. We have conducted an experiment on the spatial data infrastructure of a municipality using those data. As a result, we have found that it is possible to update data of both features almost in real time.
RIGOROUS PHOTOGRAMMETRIC PROCESSING OF CHANG'E-1 AND CHANG'E-2 STEREO IMAGERY FOR LUNAR TOPOGRAPHIC MAPPING
Authors: Di K. , Liu Y. , Liu B. , Peng M.
Published: August 2012

Abstract. Chang'E-1(CE-1) and Chang'E-2(CE-2) are the two lunar orbiters of China's lunar exploration program. Topographic mapping using CE-1 and CE-2 images is of great importance for scientific research as well as for preparation of landing and surface operation of Chang'E-3 lunar rover. In this research, we developed rigorous sensor models of CE-1 and CE-2 CCD cameras based on push-broom imaging principle with interior and exterior orientation parameters. Based on the rigorous sensor model, the 3D coordinate of a ground point in lunar body-fixed (LBF) coordinate system can be calculated by space intersection from the image coordinates of con-jugate points in stereo images, and the image coordinates can be calculated from 3D coordinates by back-projection. Due to uncer-tainties of the orbit and the camera, the back-projected image points are different from the measured points. In order to reduce these inconsistencies and improve precision, we proposed two methods to refine the rigorous sensor model: 1) refining EOPs by correcting the attitude angle bias, 2) refining the interior orientation model by calibration of the relative position of the two linear CCD arrays. Experimental results show that the mean back-projection residuals of CE-1 images are reduced to better than 1/100 pixel by method 1 and the mean back-projection residuals of CE-2 images are reduced from over 20 pixels to 0.02 pixel by method 2. Consequently, high precision DEM (Digital Elevation Model) and DOM (Digital Ortho Map) are automatically generated.
UPGRADING TO POSTGIS 2.0 IN THE BRAZILIAN FEDERAL POLICE FORENSICS GIS
Authors: Miranda D. , Russo D. , Alves R. A. L.
Published: August 2012

Abstract. Inteligeo, the Geospatial database of the Brazilian Federal Police Forensics Department, contains more than 800 layers and almost 7 million features. It was initially stored in a PostgreSQL database using the PostGIS 1.5 spatial extension. Most of the data in the system was obtained due to police intelligence field work and lacks standardization and metadata. Sometimes the data itself contains inaccuracies and topological errors. In some cases these errors are easily correctable but PostGIS 1.5 does not have tools to make these basic corrections automatically. Another common day-to-day task is calculating areas, distances and lengths. Since the standard spatial reference system is in geographical coordinates it was necessary to find a suitable projection for the area to obtain the measurements in metric units. PostGIS 1.5 does not have a tool to automatically choose an adequate projection. Looking into the newest PostGIS (subversion revision 7993 at the time), we realized that new functionality helped to solve several everyday problems and opened some possibilities regarding raster data. Among the most prominent features are: the geography support that enables distance and area calculations on the ellipsoid, the support for raster data and basic topological errors correction. As of October 2011, PostGIS 2.0 had not been released and was still under heavy development but already featured several improvements which motivated our early adoption. Early tests did not detect any major issue and demonstrated that PostGIS 2.0 was basically backwards compatible with PostGIS 1.5. Some minor bugs where reported by the federal police and quickly corrected by the developers. This work describes the installation requirements, the migration process, the caveats and back up procedures adopted by the federal police in our production database which is online since august 2011. PostGis 2.0 has been released in April 3rd 2012. This work is provided in the hope that it may be useful to anyone considering making the same transition.
AN INTEGRATED SPATIAL INDEXING OF HUGE POINT IMAGE MODEL
Authors: Wang Y. , Guo M.
Published: August 2012

Abstract. In order to manage point image model easier and build the point cloud model on the basis of the need and improve the query efficiency, a 2D&3D integrated spatial index of large point image model is proposed in this paper. Point image is managed by 2D quad tree and 3D MBB. Point image model constituted by point image are indexed by 3D-R tree. Finally the organized hierarchical model and other attribute data are stored in commercial database. The storage, management and visualization of large point image model are verified on the ordinary PCs. The experiment data are derived from the representative ancient buildings in Forbidden City. Experimental results show that the algorithm is able to manage more than 10G-level data and one billion valid points with satisfactory rendering efficiency.
SATELLITE PERSPECTIVES ON HIGHLAND – LOWLAND HUMAN INTERACTION IN ANCIENT SYRIA
Authors: Lönnqvist M. , Törmä M. , Lönnqvist K. , Nuñez M.
Published: August 2012

Abstract. Nowadays we can travel by GoogleEarth 3D to Syria (http://www.worldcountries.info/GoogleEarth/GoogleEarth-Syria.php) and zoom in on the desert landscape of the mountainous region of Jebel Bishri between the Euphrates river and the Syrian Desert. This is the area, where the Finnish archaeological survey and mapping project SYGIS worked in 2000-2010 studying the relationship of humans with their environment from ancient times to the present. What kind of landscape views and visions did the ancients have and how did they utilize them? The present paper focuses on seeking answers for these questions by combining satellite data sources, such as imagery and radar data, with location information of archaeological remains collected on the ground. Landsat as well as QuickBird imagery have been fused with SRTM mission and ASTER DEM data in creating 3D landscape models and fly-over simulations. The oasis of El Kowm on the western piedmont of the mountain seems to have served as a base camp for early huntergatherers and pastoral nomads dwelling seasonally in the region of Jebel Bishri. According to the archaeological finds, the interaction between the lowland and the mountain people already started during the Palaeolithic era but was continued by pastoral nomads of the region from the Neolithic period onwards. The Upper Palaeolithic period meant a clear change in cognitive thinking and obviously in understanding the properties of landscape, visibility and perceiving sceneries in 3D. Mobility of hunter-gatherers and pastoral nomads is based on subsistence economy, but mobility also enhances visions and prospects of phenomena appearing in the horizon.
DIGITAL ELEVATION MODELS AND DERIVED PRODUCTS FROM LROC NAC STEREO OBSERVATIONS
Authors: Burns K. N. , Speyerer E. J. , Robinson M. S. , Tran T. , Rosiek M. R. , Archinal B. A. , Howington-Kraus E. ,   the LROC Science Team
Published: August 2012

Abstract. One of the primary objectives of the Lunar Reconnaissance Orbiter Camera (LROC) is to acquire stereo observations with the Narrow Angle Camera (NAC) to enable production of high resolution digital elevation models (DEMs). This work describes the processes and techniques used in reducing the NAC stereo observations to DEMs through a combination of USGS integrated Software for Imagers and Spectrometers (ISIS) and SOCET SET® from BAE Systems by a team at Arizona State University (ASU). LROC Science Operations Center personnel have thus far reduced 130 stereo observations to DEMs of more than 130 stereo pairs for 11 Constellation Program (CxP) sites and 53 other regions of scientific interest. The NAC DEM spatial sampling is typically 2 meters, and the vertical precision is 1–2 meters. Such high resolution provides the three-dimensional view of the lunar surface required for site selection, hazard avoidance and planning traverses that minimize resource consumption. In addition to exploration analysis, geologists can measure parameters such as elevation, slope, and volume to place constraints on composition and geologic history. The NAC DEMs are released and archived through NASA’s Planetary Data System.
HAITI EARTHQUAKE DAMAGE ASSESSMENT: REVIEW OF THE REMOTE SENSING ROLE
Authors: Boccardo P. , Tonolo F. G.
Published: August 2012

Abstract. Haiti was hit by a devastating earthquake on 12 January 2010. The immediate response to the disaster was a real turning point concerning the availability, dissemination and licensing of a huge quantity of geospatial data. Timely triggering of the Earth Observation satellites, and absence of cloud cover, allowed to acquire very high-resolution optical satellite imagery (spatial resolution up to 0.5m) over the main affected areas within a few hours of the disaster, while the whole country coverage was completed in a very short time span. Furthermore in the following days aerial imagery, high resolution SAR radar imagery as well as thermal and LiDAR data were widely acquired. The paper will show how well established remote sensing techniques allowed to carry out earthquake damage assessment in a very short time, exploiting the synergic capabilities of geospatial tools and instruments such as EO satellites, Web mapping, GIS software and volunteer mapping. In a few days several map products based on the aforementioned analysis were delivered to end users: a review of the different types and purposes of this products will be provided and discussed. An assessment of the thematic accuracy of remotely sensed based products will be carried out on the basis of a review of the several available studies focused on this issue, including the main outcomes of a validation based on a comparison with in-situ data performed by the authors.
WEB MAPPING SERVICES IN A CROWDSOURCE ENVIRONMENT FOR DISASTER MANAGEMENT: STATE-OF-THE-ART AND FURTHER DEVELOPMENT
Authors: Boccardo P. , Pasquali P.
Published: August 2012

Abstract. The Haiti earthquake in 2010 has been considered a turning point in disaster response because of the support provided by collaborative communities such as OpenStreetMap, Ushahidi, CrisisMappers, Google MapMaker and others. Taking advantage of post-disaster satellite imagery these virtual communities were able to give an impressive contribution in mapping affected areas and in damage assessment. Nowadays the crowd sourcing, whether made of experts or not, can play an important role in preparedness and disaster response. In recent years the increase of web applications’ capabilities have enabled more efficient crowd sourcing of environmental data. The most successful integration of tools and data between organizations, institutions or even individuals, happens when the most open standards for interoperability are adopted, such as Web Mapping Services and Web Feature Services, defined by the Open Geospatial Consortium. In order to be widely accepted, the applications should be likely open source. It is unlikely that a single platform can fit every need or terms of use can be broadly accepted (e.g. data ownership). Therefore some organizations could prefer having more control on the application by downloading and running it as their own shared data repository and possibly as a hub for external contributors. Nevertheless, other users could prefer to access to a hosted site where they can simply upload and share their contributions. This paper will illustrate the GeoNode open source application and the principles behind the developing of a community. GeoNode is an example of how an application can be use as a global platform or as a distributed data node to promote the collaborative use of spatial data.
A NEW MULTI-RESOLUTION ALGORITHM TO STORE AND TRANSMIT COMPRESSED DTM
Authors: Biagi L. , Brovelli M. , Zamboni G.
Published: August 2012

Abstract. WebGIS and virtual globes allow DTMs distribution and three dimensional representations to the Web users' community. In these applications, the database storage size represents a critical point. DTMs are obtained by some sampling or interpolation on the raw observations and typically are stored and distributed by data based models, like for example regular grids. A new approach to store and transmit DTMs is presented. The idea is to use multi-resolution bilinear spline functions to interpolate the observations and to model the terrain. More in detail, the algorithm performs the following actions. 1) The spatial distribution of the observations is investigated. Where few data are available, few levels of splines are activated while more levels are activated where the raw observations are denser: each new level corresponds to an halving of the spline support with respect to the previous level. 2) After the selection of the spline functions to be activated, the relevant coefficients are estimated by interpolating the observations. The interpolation is computed by batch least squares. 3) Finally, the estimated coefficients of the splines are stored. The model guarantees a local resolution consistent with the data density and can be defined analytical, because the coefficients of a given function are stored instead of a set of heights. The approach is discussed and compared with the traditional techniques to interpolate, store and transmit DTMs, considering accuracy and storage requirements. It is also compared with another multi-resolution technique. The research has been funded by the INTERREG HELI-DEM (Helvetia Italy Digital Elevation Model) project.
CONSERVATION MONITORING OF A HERITAGE CEILING BY PHOTOMETRIC STEREO
Authors: MacDonald L. , Gibb I. , Robson S.
Published: August 2012

Abstract. Photographic survey techniques were employed to monitor the condition of the paintwork on the ceiling of the Queen's Staircase at Hampton Court Palace. Illumination was provided by a flash, mounted on an 8 metre telescopic mast, raised to approximately 60 cm below the ceiling, with images were taken from a fixed camera position on the floor of the landing at a range of 6.5 m. The photometric stereo method was applied to images from ten lamp positions, to calculate surface normals and a depth map. Cross-sections at the estimated surface resolution of 7.7 pixels/mm, achieved a depth (Z axis) resolution of approximately 100 microns.
DYNAMIC CONCRETE BEAM DEFORMATION MEASUREMNET WITH 3D RANGE CAMERAS
Authors: Qi X. , Lichti D.
Published: August 2012

Abstract. Concrete beams are used to construct bridges and other structures. Due to the traffic overloading or the decaying state of structures, deformation of bridges or other structures occurs frequently. Therefore, the requirement to measure concrete beam deformation, as integral components of structures, is well recognized. Many imaging techniques such as digital cameras, laser scanners and range cameras have been proven to be accurate and cost-effective methods for large-area measurement of deformation under static loading conditions. However, for obtaining useful information about the behaviour of the beams or monitoring real-time bridge deformation, the ability to measurement deformation under dynamic loading conditions is also necessary. This paper presents a relatively low-cost and high accuracy imaging technique to measure the deformation of concrete beams in response to dynamic loading with range cameras. However, due to the range camera measurement principle, target movement could lead to motion artefacts that degrade range measurement accuracy. The results of simulated and real-data investigation into the motion artefacts show that the lower sampling frequency leads to the more significant motion artefact. The results from real data experiments have indicated that periodic deformation can be recovered with sub-millimetre accuracy when the 3 Hz and 4 mm amplitude target motion is sampled at a rate of least 20 Hz and with 31 MHz range camera modulation frequency. When the modulation frequency is 29 MHz, the best sampling frequency is 20 Hz to keep the error under sub-millimetre.
AUTOMATIC TEXTURE MAPPING OF ARCHITECTURAL AND ARCHAEOLOGICAL 3D MODELS
Authors: Kersten T. P. , Stallmann D.
Published: August 2012

Abstract. Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.
BENCHMARKING MOBILE LASER SCANNING SYSTEMS USING A PERMANENT TEST FIELD
Authors: Kaartinen H. , Kukko A. , Hyyppä J. , Jaakkola A.
Published: August 2012

Abstract. The objective of the study was to benchmark the geometric accuracy of mobile laser scanning (MLS) systems using a permanent test field under good coverage of GNSS. Mobile laser scanning, also called mobile terrestrial laser scanning, is currently a rapidly developing area in laser scanning where laser scanners, GNSS and IMU are mounted onboard a moving vehicle. MLS can be considered to fill the gap between airborne and terrestrial laser scanning. Data provided by MLS systems can be characterized with the following technical parameters: a) point density in the range of 100-1000 points per m2 at 10 m distance, b) distance measurement accuracy of 2-5 cm, and c) operational scanning range from 1 to 100 m. Several commercial, including e.g. Riegl, Optech and others, and some research mobile laser scanning systems surveyed the test field using predefined driving speed and directions. The acquired georeferenced point clouds were delivered for analyzing. The geometric accuracy of the point clouds was determined using the reference targets that could be identified and measured from the point cloud. Results show that in good GNSS conditions most systems can reach an accuracy of 2 cm both in plane and elevation. The accuracy of a low cost system, the price of which is less than tenth of the other systems, seems to be within a few centimetres at least in ground elevation determination. Inaccuracies in the relative orientation of the instruments lead to systematic errors and when several scanners are used, in multiple reproductions of the objects. Mobile laser scanning systems can collect high density point cloud data with high accuracy. A permanent test field suits well for verifying and comparing the performance of different mobile laser scanning systems. The accuracy of the relative orientation between the mapping instruments needs more attention. For example, if the object is seen double in the point cloud due to imperfect boresight calibration between two scanners, this will make especially the automatic modelling of the object much more challenging.
EMPIRICAL ACCURACY ASSESSMENT OF MMS LASER POINT CLOUDS
Authors: Mano K. , Ishii K. , Hirao M. , Tachibana K. , Yoshimura M. , Akca D. , Gruen A.
Published: August 2012

Abstract. This paper describes on the accuracy assessment for the Mobile Mapping System (MMS) point clouds and its practical experiments. In recent years 3D measurement technologies have advanced significantly. Especially, MMS has been becoming to be common as one of 3D measurement instruments. We have to consider the effective accuracy assessment method stands on the measurement mechanism of MMS point cloud. For these backgrounds, we propose the accuracy assessment by applying the Least Squares 3D (LS3D) surface matching method. Our accuracy assessment consists of “1)Data quality assessment, 2)Precision accuracy assessment, 3)Absolute accuracy assessment and 4)Relative accuracy assessment”. In order to examine our accuracy assessment, we had conducted an actual MMS run at Minato-Mirai, Yokohama, Japan. Through the practical experiments and actual evaluation, we confirmed that our proposed method is the effective for the MMS point cloud accuracy assessment. As future works, we have a plan to compare with terrestrial laser point clouds as the cross-sensor accuracy assessment.
GEOSPATIAL DATA INTEGRATION FOR ASSESSING LANDSLIDE HAZARD ON ENGINEERED SLOPES
Authors: Miller P. E. , Mills J. P. , Barr S. L. , Birkinshaw S. J.
Published: August 2012

Abstract. Road and rail networks are essential components of national infrastructures, underpinning the economy, and facilitating the mobility of goods and the human workforce. Earthwork slopes such as cuttings and embankments are primary components, and their reliability is of fundamental importance. However, instability and failure can occur, through processes such as landslides. Monitoring the condition of earthworks is a costly and continuous process for network operators, and currently, geospatial data is largely underutilised. The research presented here addresses this by combining airborne laser scanning and multispectral aerial imagery to develop a methodology for assessing landslide hazard. This is based on the extraction of key slope stability variables from the remotely sensed data. The methodology is implemented through numerical modelling, which is parameterised with the slope stability information, simulated climate conditions, and geotechnical properties. This allows determination of slope stability (expressed through the factor of safety) for a range of simulated scenarios. Regression analysis is then performed in order to develop a functional model relating slope stability to the input variables. The remotely sensed raster datasets are robustly re-sampled to two-dimensional cross-sections to facilitate meaningful interpretation of slope behaviour and mapping of landslide hazard. Results are stored in a geodatabase for spatial analysis within a GIS environment. For a test site located in England, UK, results have shown the utility of the approach in deriving practical hazard assessment information. Outcomes were compared to the network operator’s hazard grading data, and show general agreement. The utility of the slope information was also assessed with respect to auto-population of slope geometry, and found to deliver significant improvements over the network operator’s existing field-based approaches.
CONSTRUCTION OF A SYSTEM FOR DEFINING AREAS WHICH ARE NOT OBTAINED DATA FROM STEREO IMAGES
Authors: Yanagi H. , Chikatsu H.
Published: August 2012

Abstract. Recently, digital documentation and visualization of various cultural assets have been receiving attention. For example, a small Buddha with a height of approximately 4 cm is categorized as a cultural asset. Such a small object has to be documented. Generally, in order to perform 3D modeling of small objects from the viewpoint of digital very close range photogrammetry, multi view images are taken. However, it is important to confirm the occluded part and image quality after taking images. In order to confirm the defocusing of images and the areas which were not obtained data from stereo images, a system is proposed for confirming data with a macro lens and convenient 3D measurement software called 3DiVision. Finally, it is proposed that the data be supplemented in areas which are not obtained data.
EVALUATION AND DEVELOPMENT OF E-LEARNING TOOLS AND METHODS IN DIGITAL PHOTOGRAMMETRY AND REMOTE SENSING FOR NON EXPERTS FROM ACADEMIA AND INDUSTRY
Authors: Gülch E. , Al-Ghorani N. , Quedenfeldt B. , Braun J.
Published: August 2012

Abstract. There does already exist a wide variety of tutorials and on-line courses on Photogrammetry and Remote Sensing very often used in academia. Many of them are still rather static and tedious or target high-knowledge learners. E-learning is, however, increasingly applied by many organizations and companies for life-long learning (like e.g. the EduServ courses of EuroSDR), but also for training of resellers and in order to save the expenses and time of travelling. A new issue of this project when taking into account the ethnic mentality in some countries like Saudi Arabia where it is impossible to mix the females and males at any institution type or for instance to teach ladies by a male teacher face to face, many academic workshops have been done separately twice by foreign organizations to adapt this situation. This paper will focus on these issues and present experiences gathered from a Master Thesis on "E-learning in Digital Photogrammetry and Remote Sensing for Non Experts using Moodle" at HFT Stuttgart in co-operation with a software vendor and a reseller and experiences from a current European Tempus IV project GIDEC (Geographic information technology for sustainable development in Eastern neighouring countries). The aim of this research is to provide an overview on available methods and tools and classify and judge their feasibility for the above mentioned scenarios. A more detailed description is given on the development of e-learning applications for Digital Photogrammetry and Remote Sensing using the open source package Moodle as platform. A first item covers the experiences from setting up and handling of Moodle for non-experts. The major emphasis is then on developing and analyzing some few case studies for lectures, exercises, and software training in the fields of Digital Photogrammetry and Remote Sensing. Feedback from students and company staff will be evaluated and incorporated in an improved design and sample implementation. A further focus is on free software and tools to allow an easy integration of dedicated methods as audio and video flashes, quizzes for self evaluation, dynamic training, web-conference, etc. into the e-learning platform. The overall objective is to evaluate on how far it is currently possibly to allow the non-experts from academic and non academic sectors to get the initial experience and knowledge in Digital Photogrammetry and Remote Sensing in a modern, flexible and economic way. The time and the skills required for developing web-based materials will thus be investigated in more detail. Additionally, the quality of the developed e-learning application will be assessed based on a list of quality criteria developed.