bluuebunny/crossref_metadata_2025 huggingface dataset:
AERIAL IMAGES FROM AN UAV SYSTEM: 3D MODELING AND TREE SPECIES CLASSIFICATION IN A PARK AREA
Authors: Gini R. , Passoni D. , Pinto L. , Sona G.
Published: August 2012

Abstract. The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.
SENSOR CORRECTION AND RADIOMETRIC CALIBRATION OF A 6-BAND MULTISPECTRAL IMAGING SENSOR FOR UAV REMOTE SENSING
Authors: Kelcey J. , Lucieer A.
Published: August 2012

Abstract. The increased availability of unmanned aerial vehicles (UAVs) has resulted in their frequent adoption for a growing range of remote sensing tasks which include precision agriculture, vegetation surveying and fine-scale topographic mapping. The development and utilisation of UAV platforms requires broad technical skills covering the three major facets of remote sensing: data acquisition, data post-processing, and image analysis. In this study, UAV image data acquired by a miniature 6-band multispectral imaging sensor was corrected and calibrated using practical image-based data post-processing techniques. Data correction techniques included dark offset subtraction to reduce sensor noise, flat-field derived per-pixel look-up-tables to correct vignetting, and implementation of the Brown- Conrady model to correct lens distortion. Radiometric calibration was conducted with an image-based empirical line model using pseudo-invariant features (PIFs). Sensor corrections and radiometric calibration improve the quality of the data, aiding quantitative analysis and generating consistency with other calibrated datasets.
STUDY ON CONSTRUCTION OF 3D BUILDING BASED ON UAV IMAGES
Authors: Xie F. , Lin Z. , Gui D. , Lin H.
Published: August 2012

Abstract. Based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D)city modeling, a method of fast 3D building modeling using the images from UAV carrying four-combined camera is studied. Firstly, by contrasting and analyzing the mosaic structures of the existing four-combined cameras, a new type of four-combined camera with special design of overlap images is designed, which improves the self-calibration function to achieve the high precision imaging by automatically eliminating the error of machinery deformation and the time lag with every exposure, and further reduce the weight of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of building surfaces and the texture extraction. Finally, two tests that are aerial photography with large scale mapping of 1:1000 and 3D building construction in Shandong University of Science and Technology and aerial photography with large scale mapping of 1:500 and 3D building construction in Henan University of Urban Construction, provide authentication model for construction of 3D building based on combined wide-angle camera images from UAV system. It is demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D building production, and the technology solution in this paper offers a new, fast and technical plan for the 3D expression of the city landscape, fine modeling and visualization.
AUTOMATIC AND GENERIC MOSAICING OF MULTISENSOR IMAGES: AN APPLICATION TO PLEIADES HR
Authors: Bignalet-Cazalet F. , Baillarin S. , Panem C.
Published: August 2012

Abstract. In the early phase of the Pleiades program, the CNES (the French Space Agency) specified and developed a fully automatic mosaicing processing unit, in order to generate satellite image mosaics under operational conditions. This tool can automatically put each input image in a common geometry, homogenize the radiometry, and generate orthomosaics using stitching lines. As the image quality commissioning phase of Pleiades1A is on-going, this mosaicing process is being tested for the first time under operational conditions. The French newly launched high resolution satellite can acquire adjacent images for French Civil and Defense User Ground Segments. This paper presents the very firsts results of mosaicing Pleiades1A images. Beyond Pleiades’ use, our mosaicing tool can process a significant variety of images, including other satellites and airborne acquisitions, using automatically-taken or external ground control points, offering time-based image superposition, and more. This paper also presents the design of the mosaicing tool and describes the processing workflow and the additional capabilities and applications.
PLEIADES SYSTEM ARCHITECTURE AND MAIN PERFORMANCES
Authors: Gleyzes M. A. , Perret L. , Kubik P.
Published: August 2012

Abstract. France, under the leadership of the French Space Agency (CNES), has set up a cooperative program with Austria, Belgium, Spain, Sweden, in order to develop a space Earth Observation system called PLEIADES. PLEIADES is a dual system, this means that it is intended to fulfill an extended panel of both civilian and Defense user’s needs.. This paper reports the status of the satellite after its launch and the in orbit commissioning, the PLEIADES satellite first model has been launched at the end of year 2011, the second model will be launched about 12 months later. It describes the main mission characteristics and performances status. It exposes how the system, satellite and ground segment have been designed in order to be compliant with a dual exploitation between civilian and defense partners. The system is based on the use of a set of newly European developed technologies to feature the satellite. In order to maximize the agility of the satellite, weight and inertia have been reduced using a compact hexagonal shape for the satellite bus. The optical mission consists in Earth optical observation composed of 0.7 m nadir resolution for the panchromatic band and 2.8 m nadir resolution for the four multi-spectral bands. The image swath is about 20 km. PLEIADES delivers optical high resolution products consisting in a Panchromatic image, into which is merged a four multispectral bands image, orthorectified on a Digital Terrain Model (DTM). Thanks to the huge satellite agility obtained with control momentum gyros as actuators, the optical system delivers as well instantaneous stereo images, under different stereoscopic conditions and mosaic images, issued from along the track thus enlarging the field of view. The ground segment is composed of a dual ground center located in CNES Toulouse premises in charge of preparing the dual mission command plan and of the real time contacts with the satellite through a control center. The dual ground center interfaces with several mission centers : one center is built for each Defense partner (France, Spain …), one center is set up for the Civilian Operator. Each mission center is in charge of managing the programming requests, then, receiving the mission telemetry, processing the data to feed a catalog and an archive, to generate the system products and distribute them to the final user. System reactivity has been optimized with a chronology based on three mission planning activations per day. The mission plan is uploaded to the satellite just before flyby over East Asia , Europe and North America. In addition a Direct Tasking mode is available for commercial Image Receiving Stations.
PLEIADES-HR INNOVATIVE TECHNIQUES FOR GEOMETRIC IMAGE QUALITY COMMISSIONING
Authors: Greslou D. , de Lussy F. , Delvit J. M. , Dechoz C. , Amberg V.
Published: August 2012

Abstract. Since the beginning of 2012, the first Pleiades-HR satellite of the program conducted by the French National Space Agency, CNES, delivers 20 km wide color scenes with a 70 cm ground sampling distance. A second satellite should be launched in 2013 which will achieve an almost world-wide coverage with a revisit interval of 24h. The assessment of the image quality and the calibration operation have been performed by CNES Image Quality team during the 6 month commissioning phase that followed the satellite launch. The geometric commissioning activities consist in improve the geometric quality of the images in order to meet very demanding specifications as localization accuracy, local coherence, dynamic stability, length alteration … This goal has been achieved through the implementation of new methods of calibration and performance assessment. Some of these methods are based on the exploitation of very specific satellite acquisitions that have been achieved thanks to the amazing agility of the Pleiades satellite. Thus, many stars acquisitions and very slow earth pictures have been processed to characterize dynamic phenomena. Similarly, “along-cross track” pairs have been exploited to improve the accuracy of the focal plane description. This paper deals with these new methods. It describes their accuracy and their operational interests.
PLEIADES ABSOLUTE CALIBRATION : INFLIGHT CALIBRATION SITES AND METHODOLOGY
Authors: Lachérade S. , Fourest S. , Gamet P. , Lebègue L.
Published: August 2012

Abstract. In-flight calibration of space sensors once in orbit is a decisive step to be able to fulfil the mission objectives. This article presents the methods of the in-flight absolute calibration processed during the commissioning phase. Four In-flight calibration methods are used: absolute calibration, cross-calibration with reference sensors such as PARASOL or MERIS, multi-temporal monitoring and inter-bands calibration. These algorithms are based on acquisitions over natural targets such as African deserts, Antarctic sites, La Crau (Automatic calibration station) and Oceans (Calibration over molecular scattering) or also new extra-terrestrial sites such as the Moon and selected stars. After an overview of the instrument and a description of the calibration sites, it is pointed out how each method is able to address one or several aspects of the calibration. We focus on how these methods complete each other in their operational use, and how they help building a coherent set of information that addresses all aspects of in-orbit calibration. Finally, we present the perspectives that the high level of agility of PLEIADES offers for the improvement of its calibration and a better characterization of the calibration sites.
PLEIADES-HR IMAGE QUALITY COMMISSIONING
Authors: Lebègue L. , Greslou D. , de Lussy F. , Fourest S. , Blanchet G , Latry C. , Lachérade L. , Delvit J. M. , Kubik P. , Déchoz C. , Amberg V. , Porez-Nadal F.
Published: August 2012

Abstract. PLEIADES is the highest resolution civilian earth observing system ever developed in Europe. This imagery program is conducted by the French National Space Agency, CNES. It operates since 2012 a first satellite PLEIADES-HR launched on 2011 December 17th, a second one should be launched by the end of the year. Each satellite is designed to provide optical 70 cm resolution coloured images to civilian and defence users. The Image Quality requirements were defined from users studies from the different spatial imaging applications, taking into account the trade-off between on-board technological complexity and ground processing capacity. The assessment of the image quality and the calibration operation have been performed by CNES Image Quality team during the 6 month commissioning phase that followed the satellite launch. These activities cover many topics gathered in two families : radiometric and geometric image quality. The new capabilities offered by PLEIADES-HR agility allowed to imagine new methods of image calibration and performance assessment. Starting from an overview of the satellite characteristics, this paper presents all the calibration operations that were conducted during the commissioning phase and also gives the main results for every image quality performance.
FUSING PASSIVE AND ACTIVE SENSED IMAGES TO GAIN INFRARED-TEXTURED 3D MODELS
Authors: Weinmann M. , Hoegner L. , Leitloff J. , Stilla U. , Hinz S. , Jutzi B.
Published: August 2012

Abstract. Obtaining a 3D description of man-made and natural environments is a basic task in Computer Vision, Photogrammetry and Remote Sensing. New active sensors provide the possibility of capturing range information by images with a single measurement. With this new technique, image-based active ranging is possible which allows for capturing dynamic scenes, e.g. with moving pedestrians or moving vehicles. The currently available range imaging devices usually operate within the close-infrared domain to capture range and furthermore active and passive intensity images. Depending on the application, a 3D description with additional spectral information such as thermal-infrared data can be helpful and offers new opportunities for the detection and interpretation of human subjects and interactions. Therefore, thermal-infrared data combined with range information is promising. In this paper, an approach for mapping thermal-infrared data on range data is proposed. First, a camera calibration is carried out for the range imaging system (PMD[vision] CamCube 2.0) and the thermal-infrared system (InfraTec VarioCAM hr). Subsequently, a registration of close-infrared and thermal infrared intensity images derived from different sensor devices is performed. In this context, wavelength independent properties are selected in order to derive point correspondences between the different spectral domains. Finally, the thermal infrared images are enhanced with information derived from data acquired with the range imaging device and the enhanced IR texture is projected onto the respective 3D point cloud data for gaining appropriate infrared-textured 3D models. The feasibility of the proposed methodology is demonstrated for an experimental setup which is well-suited for investigating these proposed possibilities. Hence, the presented work is a first step towards the development of methods for combined thermal-infrared and range representation.
A NEW EFFECTIVE WAY ON VEGETATION MORNITORING USING MULTI-SPECTRAL CANOPY LIDAR
Authors: Bo Z. , Wei G. , Shuo S. , Shalei S. , Yingying M.
Published: August 2012

Abstract. Airborne Laser Scanning (ALS) has been a well-established tool for the measurement of surface topography as well as for the estimation of biophysical canopy variables, such as tree height and vegetation density. By combining GPS and INS together, ALS could acquire surface information effectively in getting the mass production of DEM and DOM. However, up to now most approaches are built upon single-wavelength Lidar system, which could only provide structure information of the vegetation canopy, the intensity information was rarely used to monitor vegetation growing state as its limitation on spectral characteristics. On the other hand, positive multi/hyper-spectral imaging instruments highly rely on the effects of weather, shadow and the background noise etc. The attempts to fuse single-wavelength Lidar data with multi/hyper-spectral data also been effected this way. Thus, a concept for a multi-wavelength, active canopy Lidar has been tested in this paper. The proposed instrument takes measurement at two vegetation-sensitive bands separately at 556 nm and 780 nm, which, according to the correlation analysis between the wavelengths and biochemical content with plenty of ground ASD reflectance dataset, showed a high correlation coefficient on the chlorophyll concentration as well as nitrogen content. The instrumentation of the multi-wavelength canopy Lidar employs low power, solid and semiconductor laser diodes as its laser source and the receiver consists of two channels, one for 556 nm back-scatter signal and the other for 780 nm. The system calibration has also been done by using a standard white board. Multi-wavelength back-scatter signals were collected from a scene consists of stones, healthy broad-leaf trees and unhealthy trees that suffer from disease(part of its leaves were yellow). It is shown that the multi-wavelength canopy Lidar could not only capture the structure information, but also could pick up the spectral characteristics. A further test of three dimensional reconstruction and SVM based classification were also done and the results showed that the spatial resolution could be as high as 5 mm and the accuracy of classification on those three features (woody/un-woody, healthy/unhealthy) reached to 86%. Therefore, the multi-wavelength canopy Lidar shows its potential capability on vegetation monitoring in a new effective way.
SIMULTANEOUS ORIENTATION AND CALIBRATION OF IMAGES AND LASER POINT CLOUDS WITH STRAIGHT SEGMENTS
Authors: Angelats E. , Blázquez M. , Colomina I.
Published: August 2012

Abstract. This paper presents a method based on the use of straight lines as tie features for simultaneous orientation and calibration of Frame Camera (FC) and Airborne Laser Scanner (ALS) images. For the orientation and calibration of FC images, various methods have been investigated in the past. From those, FC Integrated Sensor Orientation (ISO) has established as the most accurate and robust one. More recently, ISO block adjustment techniques have been successfully applied to ALS orientation and calibration. As of today, for the combined ALS and FC image data sets there are no well-defined procedures as compared to the other two scenarios. Our proposed method essentially reduces to the use of straight line segments as tie features between FC and ALS images. The concept is similar and compatible to the use of tie points in FC ISO and of planar surfaces in ALS ISO thus allowing for the simultaneous orientation and calibration of ALS and FC images that involve, point, line and planar surface tie features. In the paper we describe and derive the two observation equations that relate (1) FC image point measurements to straight lines and (2) distance-parallelism measures between straight lines and planes. The concept and models are validated with a small FC and ALS block with real data. The preliminary results indicate the potential of the approach and confirm its feasibility.
CONTROLLING VIRTUAL CLOUDS AND MAKING IT RAIN PARTICLE SYSTEMS IN REAL SPACES USING SITUATED AUGMENTED SIMULATION AND PORTABLE VIRTUAL ENVIRONMENTS
Authors: Hedley N. , Lonergan C. D.
Published: August 2012

Abstract. The research described in this paper reports on the design, rationale, development and implementation of a set of new geospatial interfaces that combine multi-touch interaction, portable virtual environments, 'geosimulation gaming', and mobile augmented reality. The result is a set of new ways for us to combine the capabilities of geospatial virtual environments, augmented realitiy and geosimulation. These new hybrid interfaces deliver new geospatial information experiences – new ways of connecting spatial data, simulations, and abstract concepts to real spaces. Their potential to enhance environmental perception and learning must be explored.
EVALUATING THREE INTERFACE TECHNOLOGIES IN ASSISTING PEDESTRIANS' SPATIAL KNOWLEDGE ACQUISITION
Authors: Huang H. , Schmidt M. , Gartner G.
Published: August 2012

Abstract. Recent years have seen raising interests in mobile pedestrian navigation systems. Different interface technologies can be used to communicate/convey route directions to pedestrians, such as mobile maps, voices, and augmented reality (AR). Many field experiments have been conducted to study the effectiveness of different interface technologies in guiding pedestrians to their destinations. In contrast to other field studies, this article aims at investigating the influence of different interface technologies on spatial knowledge acquisition (spatial learning). With sufficient spatial knowledge about an environment, people can still find their way when navigation systems fail (e.g. out of battery). The goal of this article is to empirically evaluate three GPS-based navigation prototypes (implementing mobile map-based, AR-based, and voice-based guidance respectively) in supporting spatial knowledge acquisition. The field test showed that in terms of spatial knowledge acquisition, the three interface technologies led to comparable poor results, which were also not significantly different from each other. This article concludes with some implications for designing mobile pedestrian navigation systems.
BUILDING ANALYSIS FOR URBAN ENERGY PLANNING USING KEY INDICATORS ON VIRTUAL 3D CITY MODELS – THE ENERGY ATLAS OF BERLIN
Authors: Krüger A. , Kolbe T. H.
Published: August 2012

Abstract. In the context of increasing greenhouse gas emission and global demographic change with the simultaneous trend to urbanization, it is a big challenge for cities around the world to perform modifications in energy supply chain and building characteristics resulting in reduced energy consumption and carbon dioxide mitigation. Sound knowledge of energy resource demand and supply including its spatial distribution within urban areas is of great importance for planning strategies addressing greater energy efficiency. The understanding of the city as a complex energy system affects several areas of the urban living, e.g. energy supply, urban texture, human lifestyle, and climate protection. With the growing availability of 3D city models around the world based on the standard language and format CityGML, energy system modelling, analysis and simulation can be incorporated into these models. Both domains will profit from that interaction by bringing together official and accurate building models including building geometries, semantics and locations forming a realistic image of the urban structure with systemic energy simulation models. A holistic view on the impacts of energy planning scenarios can be modelled and analyzed including side effects on urban texture and human lifestyle. This paper focuses on the identification, classification, and integration of energy-related key indicators of buildings and neighbourhoods within 3D building models. Consequent application of 3D city models conforming to CityGML serves the purpose of deriving indicators for this topic. These will be set into the context of urban energy planning within the Energy Atlas Berlin. The generation of indicator objects covering the indicator values and related processing information will be presented on the sample scenario estimation of heating energy consumption in buildings and neighbourhoods. In their entirety the key indicators will form an adequate image of the local energy situation for decision making. An approach for extending the CityGML standard for the explicit storage of these indicators in relation to the according city object will be given by using the concept of CityGML Application Domain Extension (ADE). The aim of this approach is to initiate a discussion process for the specification of a standardized data model extension concerning energy assessment into 3D CityGML models, which facilitates the application of the Energy Atlas decision support concepts within other city models conforming to this standard.
A RESEARCH ON SPATIAL TOPOLOGICAL ASSOCIATION RULES MINING
Authors: Chen J. , Liu S. , Zhang P. , Sha Z.
Published: August 2012

Abstract. Spatial association rules mining is a process of acquiring information and knowledge from large databases. Due to the nature of geographic space and the complexity of spatial objects and relations, the classical association rule mining methods are not suitable for the spatial association rule mining. Classical association rule mining treats all input data as independent, while spatial association rules often show high autocorrelation among nearby objects. The contiguous, adjacent and neighboring relations between spatial objects are important topological relations. In this paper a new approach based on topological predictions to discover spatial association rules is presented. First, we develop a fast method to get the topological relationship of spatial data with its algebraic structure. Then the interested spatial objects are selected. To find the interested spatial objects, topological relations combining with distance were used. In this step, the frequent topological predications are gained. Next, the attribute datasets of the selected interested spatial objects are mined with Apriori algorithm. Last, get the spatial topological association rules. The presented approach has been implemented and tested by the data of GDP per capita, railroads and roads in China in the year of 2005 at county level. The results of the experiments show that the approach is effective and valid.
COST ANALYSIS OF SPATIAL DATA PRODUCTION AS PART OF BUSINESS INTELLIGENCE WITHIN THE MAPPING DEPARTMENT
Authors: Kisa A. , Erkek B. , Çolak S.
Published: August 2012

Abstract. Business intelligence is becoming an important strategic tool for business management. Companies have invested significant resources in applications for customer relationship management (CRM), supply chain management (SCM), enterprise resource planning (ERP), e-commerce, among others, which collect vast amounts of data. Today, these same companies are realizing that no matter how robust their application feature sets are, without an equally robust BI mechanism to make use of the collected data, these applications are ultimately coming up short. They do not provide actionable information to end users nor can they give a global understanding among all the organization’s information from the various databases for accounting, CRM, and so on. General Directorate of Land Registry and Cadastre (GDLRC) is the leader organizations in Turkey on the field of mapping-land registry-cadastre. GDLRC has executed spatial based projects on the way National Spatial Data Infrastructure especially from the beginnings of 2000s. such as; Continuously Operating GPS Reference Stations (TUSAGA-Aktif), Geo-Metadata Portal (HBB), Orthophoto-Base Map Production and web services, Completion of Initial Cadastre, Cadastral Renovation Project (TKMP), Land Registry and Cadastre Information System (TAKBIS), Turkish National Spatial Data Infrastructure Project (TNSDI), Ottoman Land Registry Archive Information System (TARBIS). Most of this project has been completed. Some software has been developed within the mentioned project, especially reporting for management level to take decision. In the year of 2010 a new law launched and forced to reorganization of General Directorate of Land Registry and Cadastre. The new structural changes effected to whole organization, management understanding, carrier understanding so on. Even in mapping department which is spatial data producer, now there is no technician, there is no section; there are new carrier as experts. Because of that, all procedures and performance critters are redefined, improvement of existing software are defined, cost analysis implemented as a part of business intelligence. This paper indicated some activities such as cost analysis and its reflection in Mapping Department as an example to share in the concept of reorganization.
CONSISTENCY MATCHING IN THE INTEGRATION OF CONTOUR AND RIVER DATA BY SPATIAL KNOWLEDGE
Authors: Ai T. , Yang M.
Published: August 2012

Abstract. As the representation of terrain surface and height information, the contour data has the strict constraint relationship with the distribution of river network. In spatial data integration and matching, the inconsistency usually occurs between the river network and contour generating “river climbing uphill”. This study presents a method to build the matching relationship and to correct the inconsistency between river network and contour data. Based on Delaunay triangulation, the terrain landform features are extracted and by bend analysis build the matching relations between river network and contour. According to different inconsistency situations, we offer two correction approaches depending on which data is precise, which includes the river network displacement referenced to the contour and the opposite.
ASSESSMENT OF THREE-DIMENSIONAL MODELS DERIVED FROM LIDAR AND TLS DATA
Authors: Landes T. , Grussenmeyer P. , Boulaassal H. , Mohamed M.
Published: August 2012

Abstract. This paper suggests the use of specific methods for assessing the geometry of 3D building models, by considering models extracted automatically from terrestrial laser scanning (TLS) data and aerial laser scanning (ALS) data. Well known quality factors have been applied for assessing roofs and façades separately. A projection into 2D makes sense in this case, because currently, 3D models or point clouds of façades are often projected into 2D for generating 2D façade maps, as required in the building trades. For assessing roofs in 3D, error maps have been suggested especially for analysing the spatial distribution of plane adjustment errors which might affect the final reconstructed 3D model. For assessing 3D building vector models as one object, first experiments based on volumetric quality factors are presented. This approach is based on ratios inspired from quality factors that have already proven themselves in the literature for comparing surface areas. The volumes considered here are computed on vector models (faceted solids) and not voxels. Further investigations are necessary on the one hand, for testing the sensitivity of these factors. On the other hand, the approach must be completed by criteria allowing the detection of shape differences, independently of the building volume.
COMBINED GEOMETRIC/RADIOMETRIC POINT CLOUD MATCHING FOR SHEAR ANALYSIS
Authors: Gehrke S.
Published: August 2012

Abstract. In the recent past, dense image matching methods such as Semi-Global Matching (SGM) became popular for many applications. The SGM approach has been adapted to and implemented for Leica ADS line-scanner data by North West Geomatics (North West) in co-operation with Leica Geosystems; it is used in North West’s production workflow. One of the advantages of ADS imagery is the calibrated color information (RGB and near infrared), extending SGM-derived point clouds to dense “image point clouds” or, more general, information clouds (info clouds). With the goal of automating the quality control of ADS data, info clouds are utilized for Shear Analysis: Three-dimensional offsets of adjacent ADS image strips are determined from a pattern of info cloud pairs in strip overlaps by point cloud matching. The presented approach integrates geometry (height) and radiometry (intensity) information; matching is based on local point-to-plane distances for all points in a given cloud. The offset is derived in a least squares adjustment by applying it to each individual distance computation equation. Using intensities in addition to heights greatly benefits the offset computation, because intensity gradients tend to occur more frequently than height gradients. They can provide or complement the required information for the derivation of planimetric offset components. The paper details the combined geometric/radiometric point cloud matching approach and verifies the results against manual measurements.
ALTERNATIVE METHODOLOGIES FOR THE ESTIMATION OF LOCAL POINT DENSITY INDEX: MOVING TOWARDS ADAPTIVE LIDAR DATA PROCESSING
Authors: Lari Z. , Habib A.
Published: August 2012

Abstract. Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification). Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for precise LiDAR data processing.v
CLASSIFICATION OF AIRBORNE LASER SCANNING DATA IN WADDEN SEA AREAS USING CONDITIONAL RANDOM FIELDS
Authors: Schmidt A. , Rottensteiner F. , Sörgel U.
Published: August 2012

Abstract. In this paper we investigate the influence of contextual knowledge for the classification of airborne laser scanning data in Wadden Sea areas. For this propose we use Conditional Random Fields (CRF) for the classification of the point cloud into the classes water, mudflat, and mussel bed based on geometric and intensity features. We learn typical structures in a training step and combine local descriptors with context information in a CRF framework. It is shown that the point-based classification result, especially the completeness rate for water and mussel bed as well as the correction rate of water, can be significantly improved if contextual knowledge is integrated. We evaluate our approach on a test side of the German part of the Wadden Sea and compare the results with a Maximum Likelihood Classification.
ACCURACY ASSESSMENT OF BUILDING MODELS CREATED FROM LASER SCANNING DATA
Authors: Borkowski A. , Jóźków G.
Published: August 2012

Abstract. Recently, it can be observed a growing interest in 3D building or city models created from laser scanning data. These models are used in many areas of interest. In this work the accuracy assessment of 3D buildings models created from airborne and terrestrial laser scanning data was carried out. TLS data for modelling were acquired with average point spacing about 0.02 m. In order to model invisible from the ground building elements such as roofs, the LIDAR data was used with density of about 12 pts./m2. TLS and LIDAR data were acquired in the same coordinates system. For textures mapping a set of 10 Mpix digital images using SLR camera Canon 40D were taken. Modelling was performed using both commercial software Leica Cyclone, as well as original software and free software. The accuracy of models is affected by many factors, but the impact of all factors leading to errors of the final models were analysed together. The accuracy of models was assessed by comparing the coordinates of characteristic points of the models and the corresponding coordinates of these points measured on real buildings. The accuracy of points measured on the real building was not affected by model errors, therefore they can be treated as error-free reference points. On site reference measurements were performed using Leica TCR407Power reflectorless total station. Obtained inaccuracies of the reconstructed models were as follow: 0.12 m horizontal, 0.1 3m vertical, 0.18 m three-dimensional.
A NEW OBJECT BASED METHOD FOR AUTOMATED EXTRACTION OF URBAN OBJECTS FROM AIRBORNE SENSORS DATA
Authors: Moussa A. , El-Sheimy N.
Published: August 2012

Abstract. The classification of urban objects such as buildings, trees and roads from airborne sensors data is an essential step in numerous mapping and modelling applications. The automation of this step is greatly needed as the manual processing is costly and time consuming. The increasing availability of airborne sensors data such as aerial imagery and LIDAR data offers new opportunities to develop more robust approaches for automatic classification. These approaches should integrate these data sources that have different characteristics to exceed the accuracy achieved using any individual data source. The proposed approach presented in this paper fuses the aerial images data with single return LIDAR data to extract buildings and trees for an urban area. Object based analysis is adopted to segment the entire DSM data into objects based on height variation. These objects are preliminarily classified into buildings, trees, and ground. This primary classification is used to compute the height to ground for each object to help improve the accuracy of the second phase of classification. The overlapping perspective aerial images are used to build an ortho-photo to derive a vegetation index value for each object. The second phase of classification is performed based on the height to ground and the vegetation index of each object. The proposed approach has been tested using three areas in the centre of the city of Vaihingen provided by ISPRS test project on urban classification and 3D building reconstruction. These areas have historic buildings having rather complex shapes, few high-rising residential buildings that are surrounded by trees, and a purely residential area with small detached houses. The results of the proposed approach are presented based on a reference solution for evaluation purposes. The classification evaluation exhibits highly successful classification results of buildings class. The proposed approach follows the exact boundary of trees based on LIDAR data which provide above average classification results for the trees when compared to the assumed ideal circular shaped trees in the reference data.
INTENSITY AND RANGE IMAGE BASED FEATURES FOR OBJECT DETECTION IN MOBILE MAPPING DATA
Authors: Palmer R. , Borck M. , West G. , Tan T.
Published: August 2012

Abstract. Mobile mapping is used for asset management, change detection, surveying and dimensional analysis. There is a great desire to automate these processes given the very large amounts of data, especially when 3-D point cloud data is combined with co-registered imagery – termed "3-D images". One approach requires low-level feature extraction from the images and point cloud data followed by pattern recognition and machine learning techniques to recognise the various high level features (or objects) in the images. This paper covers low-level feature analysis and investigates a number of different feature extraction methods for their usefulness. The features of interest include those based on the "bag of words" concept in which many low-level features are used e.g. histograms of gradients, as well as those describing the saliency (how unusual a region of the image is). These mainly image based features have been adapted to deal with 3-D images. The performance of the various features are discussed for typical mobile mapping scenarios and recommendations made as to the best features to use.
QUALITY ANALYSIS ON RANSAC-BASED ROOF FACETS EXTRACTION FROM AIRBORNE LIDAR DATA
Authors: Yan J. , Jiang W. , Shan J.
Published: August 2012

Abstract. RANSAC algorithm is a robust method for model estimation. It is widely used in the extraction of geometry primitives and 3D model reconstruction. However, there has been relatively little comprehensive evaluation in RANSAC-based approach for plane extraction. In order to provide a reference for improving the quality on RANSAC-based approach for roof facets extraction or segmentation, this paper focuses on the quality analysis on classical RANSAC algorithm. Airborne LIDAR data from the test Area 1 and Area 2 in Vaihingen (German) is used. 33 buildings (4 buildings with flat roofs and 29 buildings with slope roofs) extracted from LIDAR data are taken as input for planes extraction. Based on the characteristics of detected planar surfaces, planes can fall into several categories: non-segmented planes, over-segmented planes, under-segmented planes and spurious planes. Then, several causes for these quality problems are discussed. Some experimental results and analyses show that, considering spatial-domain connectivity, most of the quality problems of classical RANSAC algorithm can be improved. However, there are still many issues requiring in-depth research. Finally, some methods are suggested to solve these problems.
FROM IMAGE CONTOURS TO PIXELS
Authors: Scarmana G.
Published: August 2012

Abstract. This paper relates to the reconstruction of digital images using their contour representations. The process involves determining the pixel intensity value which would exist at the intersections of a regular grid using the nodes of randomly spaced contour locations. The reconstruction of digital images from their contour maps may also be used as a tool for image compression. This reconstruction process may provide for more accurate results and improved visual details than existing compressed versions of the same image, while requiring similar memory space for storage and speed of transmission over digital links. For the class of images investigated in this work, the contour approach to image reconstruction and compression requires contour data to be filtered and eliminated from the reconstruction process. Statistical tests which validate the proposed process conclude this paper.
QUALITY ANALYSIS OF VEHICLE-BASED SEQUENCE IMAGES RELATIVE ORIENTATION BASED ON COMPUTER VISION
Authors: Yan L. , Xu Z.
Published: August 2012

Abstract. Analyzed the quality and its influence factors of relative orientation of vehicle-based sequence images by comparing with the result obtained from Position & Orientation System using Direct Geo-referencing. Studies have shown that, under normal circumstances, the image Relative Orientation based on Computer vision is more robust, and under special conditions, it is more practical for analyzing and increasing the quality of vision measurement. Besides these, the method can be borrowed by many surveying and mapping related fields, taking indoor robot mobile environment awareness and unmanned automobile for instance.
INVESTIGATING THE DYNAMICS OF WANDOO CROWN DECLINE WITH TIME SERIES LANDSAT IMAGERY
Authors: Zdunic K. , Behn G. , van Dongen R.
Published: August 2012

Abstract. In the forests of south west Western Australia dramatic declines in tree health have been observed in recent years. The species Eucalyptus wando has exhibited loss of crown foliage in increasing stages of severity; this condition is referred to as wandoo crown decline and can lead to death. Determining the extent and timing of these declines is difficult on the ground due to the large distribution of E. wandoo and the observation of tree declines at a range of locations and dates over the last 40 years. Understanding the distribution, severity and timing of these declines is essential to the identification of the causes of these impacts. Investigation of time series Landsat imagery can inform on locations of crown foliage loss and the time periods these losses occurred in. Applying a vegetation index to a 20 year sequence of imagery enabled periods of decline to be identified. Employment of trend analysis of four date time series demonstrated the dynamics of wandoo crown cover. Comparisons of periods of decline with the variations of cover density over the entire image sequence facilitated the identification of possible locations and timing of wandoo crown decline impacts. Changes in crown cover observed by the imagery analysis were compared to field surveys.
LOCATION DETERMINATION IN URBAN ENVIRONMENT FROM IMAGE SEQUENCES
Authors: Zhan Q. , Liang Y. , Xiao Y.
Published: August 2012

Abstract. Location Determination Problem (LDP) is a classic and interesting problem both for photogrammetry and computer vision community: Given an image depicting a set of landmarks with known locations, determine that point in space from which the image was obtained. In this paper we try to use image sequences to automatically solve LDP in local Euclidean space in which no georeference information is needed. Overlapping image sequences are preferable for matching images obtained in cities. We implement a method which can semi-automatically solve LDP in urban scenario with state-of-the-art 3D reconstruction system.
MORPHOLOGICAL HIT-OR-MISS TRANSFORM BASED APPROACH FOR BUILDING DAMAGE ESTIMATION FROM VHR AIRBORNE IMAGERY IN 2011 PACIFIC COAST OF TOHOKU EARTHQUAKE AND TSUNAMI
Authors: Parape C. D. K. , Chinthaka H. , Premachandra N. , Tamura M. , Sugiura M.
Published: August 2012

Abstract. The very high resolution (VHR) airborne images offer the opportunity to recognize features such as road, vegetation, buildings and other kind of infrastructures. The advantage of remote sensing and its applications made it possible to extract damaged, undamaged building and vulnerability assessment of wide urban areas due to a natural disaster. In this paper, we focus on an automatic building detection method which is helpful to optimizing, recognizing, rescuing, recovery and management tasks in the event of a disaster. Objective of this study is to develop techniques for tsunami damaged building extraction, based on very high resolution (VHR) airborne images acquired before and after the 2011 East coastline of Japan among Tohoku area and to carry out a damage assessment of building and vulnerable area mapping. This paper presents a methodology and results of evaluating damaged buildings detection algorithm using an object recognition task based on Mathematical Morphological (MM) operators for Very High Resolution (VHR) remotely sensed airborne images. The proposed approach involves several advanced morphological operators among which an adaptive hit-or-miss transform with varying size and shape of the structuring elements. VHR airborne images consisting of pre and post 2011 Pacific coast of Tohoku earthquake and Tsunami site of the Ishinomaki, Miyagi area in Japan were used. The extracted results of building were compared with ground truth data giving 76% and 88% in accuracy before and after the Tsunami event.