bluuebunny/crossref_metadata_2025 huggingface dataset:
AUTOMATIC CLASSIFICATION OF TREES FROM LASER SCANNING POINT CLOUDS
Authors: Sirmacek B. , Lindenbergh R.
Published: August 2015

Abstract. Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into ’tree’ and ’non-tree’ classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the ’tree’ or ’non-tree’ class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.
KALMAN FILTER BASED RAILWAY TRACKING FROM MOBILE LIDAR DATA
Authors: Jwa Y. , Sonh G.
Published: August 2015

Abstract. This study introduces a new method to reconstruct 3D model of railway tracks from a railway corridor scene captured by mobile LiDAR data. The proposed approach starts to approximate the orientation of railway track trajectory from LiDAR point clouds and extract a strip, which direction is orthogonal to the trajectory of railway track. Within the strip, a track region and its track points are detected based on the Bayesian decision process. Once the main track region is localized, rail head points are segmented based on the region growing approach from the detected track points and then initial track models are reconstructed using a third-degree polynomial function. Based on the initial modelling result, a potential track region with varying lengths is dynamically predicted and the model parameters are updated in the Kalman Filter framework. The key aspect is that the proposed approach is able to enhance the efficiency of the railway tracking process by reducing the complexity for detecting track points and reconstructing track models based on the use of the track model previously reconstructed. An evaluation of the proposed method is performed over an urban railway corridor area containing multiple railway track pairs.
A MAN-PORTABLE, IMU-FREE MOBILE MAPPING SYSTEM
Authors: Nüchter A. , Borrmann D. , Koch P. , Kühn M. , May S.
Published: August 2015

Abstract. Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.
TOWARDS A GENERIC METHOD FOR BUILDING-PARCEL VECTOR DATA ADJUSTMENT BY LEAST SQUARES
Authors: Méneroux Y. , Brasebin M.
Published: August 2015

Abstract. Being able to merge high quality and complete building models with parcel data is of a paramount importance for any application dealing with urban planning. However since parcel boundaries often stand for the legal reference frame, the whole correction will be exclusively done on building features. Then a major task is to identify spatial relationships and properties that buildings should keep through the conflation process. The purpose of this paper is to describe a method based on least squares approach to ensure that buildings fit consistently into parcels while abiding by a set of standard constraints that may concern most of urban applications. An important asset of our model is that it can be easily extended to comply with more specific constraints. In addition, results analysis also demonstrates that it provides significantly better output than a basic algorithm relying on an individual correction of features, especially regarding conservation of metrics and topological relationships between buildings. In the future, we would like to include more specific constraints to retrieve the actual positions of buildings relatively to parcel borders and we plan to assess the contribution of our algorithm on the quality of urban application outputs.
GEOSPATIAL DATA QUALITY OF THE SERVIR CORS NETWORK
Authors: Santos J. , Teodoro R. , Mira N. , Mendes V. B.
Published: August 2015

Abstract. The SERVIR Continuous Operation Reference Stations (CORS) network was implemented in 2006 to facilitate land surveying with Global Navigation Satellite Systems (GNSS) positioning techniques. Nowadays, the network covers all Portuguese mainland. The SERVIR data is provided to many users, such as surveyors, universities (for education and research purposes) and companies that deal with geographic information. By middle 2012, there was a significant change in the network accessing paradigm, the most important of all being the increase in the responsibility of managing the network to guarantee a permanent availability and the highest quality of the geospatial data. In addition, the software that is used to manage the network and to compute the differential corrections was replaced by a new software package. These facts were decisive to perform the quality control of the SERVIR network and evaluate positional accuracy. In order to perform such quality control, a significant number of geodetic monuments spread throughout the country were chosen. Some of these monuments are located in the worst location regarding the network geometry in order to evaluate the accuracy of positions for the worst case scenarios. Data collection was carried out using different GNSS positioning modes and were compared against the benchmark positions that were determined using data acquired in static mode in 3-hour sessions. We conclude the geospatial data calculated and provided to the users community by the network is, within the surveying purposes, accurate, precise and fits the needs of those users.
DATA QUALITY ASSESSMENT FOR MARITIME SITUATION AWARENESS
Authors: Iphar C. , Napoli A. , Ray C.
Published: August 2015

Abstract. The Automatic Identification System (AIS) initially designed to ensure maritime security through continuous position reports has been progressively used for many extended objectives. In particular it supports a global monitoring of the maritime domain for various purposes like safety and security but also traffic management, logistics or protection of strategic areas, etc. In this monitoring, data errors, misuse, irregular behaviours at sea, malfeasance mechanisms and bad navigation practices have inevitably emerged either by inattentiveness or voluntary actions in order to circumvent, alter or exploit such a system in the interests of offenders. This paper introduces the AIS system and presents vulnerabilities and data quality assessment for decision making in maritime situational awareness cases. The principles of a novel methodological approach for modelling, analysing and detecting these data errors and falsification are introduced.
MEASURES AND INDICATORS OF VGI QUALITY: AN OVERVIEW
Authors: Antoniou V. , Skopeliti A.
Published: August 2015

Abstract. The evaluation of VGI quality has been a very interesting and popular issue amongst academics and researchers. Various metrics and indicators have been proposed for evaluating VGI quality elements. Various efforts have focused on the use of well-established methodologies for the evaluation of VGI quality elements against authoritative data. In this paper, a number of research papers have been reviewed and summarized in a detailed report on measures for each spatial data quality element. Emphasis is given on the methodology followed and the data used in order to assess and evaluate the quality of the VGI datasets. However, as the use of authoritative data is not always possible many researchers have turned their focus on the analysis of new quality indicators that can function as proxies for the understanding of VGI quality. In this paper, the difficulties in using authoritative datasets are briefly presented and new proposed quality indicators are discussed, as recorded through the literature review. We classify theses new indicators in four main categories that relate with: i) data, ii) demographics, iii) socio-economic situation and iv) contributors. This paper presents a dense, yet comprehensive overview of the research on this field and provides the basis for the ongoing academic effort to create a practical quality evaluation method through the use of appropriate quality indicators.
UNCERTAINTIES OF COMPLETENESS MEASURES IN OPENSTREETMAP – A CASE STUDY FOR BUILDINGS IN A MEDIUM-SIZED GERMAN CITY
Authors: Törnros T. , Dorn H. , Hahmann S. , Zipf A.
Published: August 2015

Abstract. The completeness of buildings in OpenStreetMap (OSM) is estimated for a medium-sized German city and its surroundings by comparing the OSM data with data from an official building cadastre. As completeness measures we apply two unit-based methods that are frequently applied in similar studies. It is found that the estimation of OSM building completeness strongly differ between the methods. A count ratio (number of OSM buildings / number of reference buildings) tends to underestimate the actual building completeness and an area ratio (total OSM building area / total reference building area) instead tends to overestimate the completeness within the study area. It is argued that a simple pre-processing of the building footprint polygons leads to a more accurate completeness estimation when applying the count ratio. It is also suggested to more carefully examine the areas that have been mapped in OSM but not in the reference data set (false positives). In the present study region, these values are mainly due to simplified OSM polygons and they contribute to an overestimation of the OSM building completeness when applying the area ratio.
RECONSTRUCTION OF SCAFFOLDING COMPONENTS FROM PHOTOGRAMMETRIC POINT CLOUDS OF A CONSTRUCTION SITE
Authors: Xu Y. , He J. , Tuttas S. , Stilla U.
Published: August 2015

Abstract. This paper presents a data-driven workflow for the detection of scaffolding components from point clouds. The points belonging to the scaffolding components are identified and separated from the main building structures and two basic elements, namely the toeboard and the tube, are reconstructed. The workflow has four main processing steps. Firstly, the raw point clouds are preprocessed by statistical filtering and voxel girding. In the second step, the planar surfaces of the building surface and scaffoldings are extracted via RANSAC and then grouped by their parallelity and distance to separate the building façade. In the third step, the 3D shape descriptor FPFH and random forest classification algorithm are applied to classify the point data of building façades into classes belonging to different elements. Finally, by the use of linear fitting algorithm and matching using SHOT shape descriptor, the tubes and toeboards are reconstructed with their geometric parameters. It is shown that the points belonging to these objects are identified and then reconstructed with cylinder and cuboid models. The final results show that over 60% of the tubes and nearly 90% of the toeboards are reconstructed in the investigated façade, and more than 40% of the reconstructed objects are well rebuilt.
GLOBAL AND LOCAL SPARSE SUBSPACE OPTIMIZATION FOR MOTION SEGMENTATION
Authors: Ying Yang M. , Feng S. , Ackermann H. , Rosenhahn B.
Published: August 2015

Abstract. In this paper, we propose a new framework for segmenting feature-based moving objects under affine subspace model. Since the feature trajectories in practice are high-dimensional and contain a lot of noise, we firstly apply the sparse PCA to represent the original trajectories with a low-dimensional global subspace, which consists of the orthogonal sparse principal vectors. Subsequently, the local subspace separation will be achieved via automatically searching the sparse representation of the nearest neighbors for each projected data. In order to refine the local subspace estimation result, we propose an error estimation to encourage the projected data that span a same local subspace to be clustered together. In the end, the segmentation of different motions is achieved through the spectral clustering on an affinity matrix, which is constructed with both the error estimation and sparse neighbors optimization. We test our method extensively and compare it with state-of-the-art methods on the Hopkins 155 dataset. The results show that our method is comparable with the other motion segmentation methods, and in many cases exceed them in terms of precision and computation time.
VISUALISATION OF COMPLEX 3D CITY MODELS ON MOBILE WEBBROWSERS USING CLOUD-BASED IMAGE PROVISIONING
Authors: Christen M. , Nebiker S.
Published: August 2015

Abstract. Rendering large city models with high polygon count and a vast amount of textures at interactive frame rates is a rather difficult to impossible task as it highly depends on the client hardware, which is often insufficient, even if out-of-core rendering techniques and level of detail approaches are used. Rendering complex city models on mobile devices is even more challenging. An approach of rendering and caching very large city models in the cloud using ray-tracing based image provisioning is introduced. This allows rendering large scenes efficiently, including on mobile devices. With this approach, it is possible to render cities with nearly unlimited number of polygons and textures.
SEMI-AUTOMATED DETECTION OF SURFACE DEGRADATION ON BRIDGES BASED ON A LEVEL SET METHOD
Authors: Masiero A. , Guarnieri A. , Pirotti F. , Vettore A.
Published: August 2015

Abstract. Due to the effect of climate factors, natural phenomena and human usage, buildings and infrastructures are subject of progressive degradation. The deterioration of these structures has to be monitored in order to avoid hazards for human beings and for the natural environment in their neighborhood. Hence, on the one hand, monitoring such infrastructures is of primarily importance. On the other hand, unfortunately, nowadays this monitoring effort is mostly done by expert and skilled personnel, which follow the overall data acquisition, analysis and result reporting process, making the whole monitoring procedure quite expensive for the public (and private, as well) agencies. This paper proposes the use of a partially user–assisted procedure in order to reduce the monitoring cost and to make the obtained result less subjective as well. The developed method relies on the use of images acquired with standard cameras by even inexperienced personnel. The deterioration on the infrastructure surface is detected by image segmentation based on a level sets method. The results of the semi-automated analysis procedure are remapped on a 3D model of the infrastructure obtained by means of a terrestrial laser scanning acquisition. The proposed method has been successfully tested on a portion of a road bridge in Perarolo di Cadore (BL), Italy.
INTEGRATED ESTIMATION OF SEISMIC PHYSICAL VULNERABILITY OF TEHRAN USING RULE BASED GRANULAR COMPUTING
Authors: Sheikhian H. , Delavar M. R. , Stein A.
Published: August 2015

Abstract. Tehran, the capital of Iran, is surrounded by the North Tehran fault, the Mosha fault and the Rey fault. This exposes the city to possibly huge earthquakes followed by dramatic human loss and physical damage, in particular as it contains a large number of non-standard constructions and aged buildings. Estimation of the likely consequences of an earthquake facilitates mitigation of these losses. Mitigation of the earthquake fatalities may be achieved by promoting awareness of earthquake vulnerability and implementation of seismic vulnerability reduction measures. In this research, granular computing using generality and absolute support for rule extraction is applied. It uses coverage and entropy for rule prioritization. These rules are combined to form a granule tree that shows the order and relation of the extracted rules. In this way the seismic physical vulnerability is assessed, integrating the effects of the three major known faults. Effective parameters considered in the physical seismic vulnerability assessment are slope, seismic intensity, height and age of the buildings. Experts were asked to predict seismic vulnerability for 100 randomly selected samples among more than 3000 statistical units in Tehran. The integrated experts’ point of views serve as input into granular computing. Non-redundant covering rules preserve the consistency in the model, which resulted in 84% accuracy in the seismic vulnerability assessment based on the validation of the predicted test data against expected vulnerability degree. The study concluded that granular computing is a useful method to assess the effects of earthquakes in an earthquake prone area.
DEVELOPMENT OF A CARTOGRAPHIC STRATEGY AND GEOSPATIAL SERVICES FOR DISASTER EARLY WARNING AND MITIGATION IN THE ECOWAS SUBREGION
Authors: Gueye L. A. , Keita M. S. , Akinyede J. O. , Kufoniyi O. , Erin G.
Published: August 2015

Abstract. The West Africa Sub-region has been crisis and disaster ridden in recent times with enormous challenges for disaster mitigation. The crisis/disasters range from conflicts fuelled by political upheaval to epidemics that take their tolls on the population of some countries in the sub-region. The crisis and disaster events have overwhelming magnitudes and are highly dynamic, requiring a well-articulated plan for immediate response in order to mitigate their effects. A study carried out by the Early Warning Directorate (EWD) of the Economic Commission of West African States (ECOWAS) highlighted the risks and vulnerabilities of the region despite the considerable progress made in development and peace consolidation in some parts of the region. The study identified apparent institutional and infrastructural deficiencies, such as the lack of up-to-date geospatial data and information, and inadequate platforms for data gathering and data sharing among the relevant national agencies, which have made much of the region particularly vulnerable to the emerging threats. It is against the foregoing that the development of a Cartographic Strategy and Geospatial Services for EWD and the ECOWAS is being proposed. In addition to the resolution of the crucial need of reliable geospatial data capacity of member states, this initiative will spearhead the realisation of a Geospatial Data Infrastructure for ECOWAS Commission, through the appropriate policy formulation and implementation. Through the proper implementation of the Cartographic Strategy and Geospatial Services, ECOWAS will have the capacity to provide geospatial analysis and mapping support focusing on areas related to conflict prevention and resolution, regional planning for food security, early warning of viral diseases and epidemics, disaster preparedness, mitigation and response, infrastructural development and refugee resettlement, and a host of other vital projects/programmes for promoting ECOWAS regional integration agenda. This paper discusses the outcome of the preliminary studies and activities carried out by an Expert Group commissioned by the EWD to develop a Cartographic Strategy and propose a framework for its implementation. These include the assessment of the status of mapping and Geographic Information System uptake in member states, the formulation of policy and the realisation of a work plan for its successful implementation in the region.
HEIGHT ACCURACY BASED ON DIFFERENT RTK GPS METHOD FOR ULTRALIGHT AIRCRAFT IMAGES
Authors: Tahar K. N.
Published: August 2015

Abstract. Height accuracy is one of the important elements in surveying work especially for control point’s establishment which requires an accurate measurement. There are many methods can be used to acquire height value such as tacheometry, leveling and Global Positioning System (GPS). This study has investigated the effect on height accuracy based on different observations which are single based and network based GPS methods. The GPS network is acquired from the local network namely Iskandar network. This network has been setup to provide real-time correction data to rover GPS station while the single network is based on the known GPS station. Nine ground control points were established evenly at the study area. Each ground control points were observed about two and ten minutes. It was found that, the height accuracy give the different result for each observation.
TREATMENT OF GEODETIC SURVEY DATA AS FUZZY VECTORS
Authors: Navratil G. , Heer E. , Hahn J.
Published: August 2015

Abstract. Geodetic survey data are typically analysed using the assumption that measurement errors can be modelled as noise. The least squares method models noise with the normal distribution and is based on the assumption that it selects measurements with the highest probability value (Ghilani, 2010, p. 179f). There are environment situations where no clear maximum for a measurement can be detected. This can happen, for example, if surveys take place in foggy conditions causing diffusion of light signals. This presents a problem for automated systems because the standard assumption of the least squares method does not hold. A measurement system trying to return a crisp value will produce an arbitrary value that lies within the area of maximum value. However repeating the measurement is unlikely to create a value following a normal distribution, which happens if measurement errors can be modelled as noise. In this article we describe a laboratory experiment that reproduces conditions similar to a foggy situation and present measurement data gathered from this setup. Furthermore we propose methods based on fuzzy set theory to evaluate the data from our measurement.
INFLUENCE OF THE PRECISION OF LIDAR DATA IN SURFACE WATER RUNOFF ESTIMATION FOR ROAD MAINTENANCE
Authors: González-Jorge H. , Díaz-Vilariño L. , Lagüela S. , Martínez-Sánchez J. , Arias P.
Published: August 2015

Abstract. Roads affect the natural surface and subsurface drainage pattern of a hill or a watershed. Road drainage systems are designed with the objective of reducing the energy generated by the flowing water and the presence of excess water or moisture within the road. A poorly designed drainage may affect to road maintenance causing cut or fill failures, road surface erosion and degrading the engineering properties of the materials with which it was constructed. Surface drainage pattern can be evaluated from Digital Elevation Models typically calculated from point clouds acquired with aerial LiDAR platforms. However, these systems provide low resolution point clouds especially in cases where slopes with steep grades exist. In this work, Mobile LiDAR systems (aerial and terrestrial) are combined for surveying roads and their surroundings in order to provide complete point cloud. As the precision of the point clouds obtained from these mobile systems is influenced by GNSS outages, Gaussian noise with different standard deviation values is introduced in the point cloud in order to determine its influence in the evaluation of water runoff direction. Results depict an increase in the differences of flow direction with the decrease of cell size of the raster dataset and with the increase of Gaussian noise. The last relation fits to a second-order polynomial Differences in flow direction up to 42º are achieved for a cell size of 0.5 m with a standard deviation of 0.15 m.
COASTAL DIGITAL SURFACE MODEL ON LOW CONTRAST IMAGES
Authors: Rosu A.-M. , Assenbaum M. , De la Torre Y. , Pierrot-Deseilligny M.
Published: August 2015

Abstract. Coastal sandy environments are extremely dynamic and require regular monitoring that can easily be achieved by using an unmanned aerial system (UAS) including a drone and a photo camera. The acquired images have low contrast and homogeneous texture. Using these images and with very few, if any, ground control points (GCPs), it is difficult to obtain a digital surface model (DSM) by classical correlation and automatic interest points determination approach. A possible response to this problem is to work with enhanced, contrast filtered images. To achieve this, we use and tune the free open-source software MicMac.
UAV APPLICATION IN COASTAL ENVIRONMENT, EXAMPLE OF THE OLERON ISLAND FOR DUNES AND DIKES SURVEY
Authors: Guillot B. , Pouget F.
Published: August 2015

Abstract. The recent evolutions in civil UAV ease of use led the University of La Rochelle to conduct an UAV program around its own potential costal application. An application program involving La Rochelle University and the District of Oleron Island began in January 2015 and lasted through July of 2015. The aims were to choose 9 study areas and survey them during the winter season. The studies concerned surveying the dikes and coastal sand dunes of Oleron Island. During each flight, an action sport camera fixed on the UAV’s brushless gimbal took a series of 150 pictures. After processing the photographs and using a 3D reconstruction plugin via Photoscan, we were able to export high-resolution ortho-imagery, DSM and 3D models. After applying GIS treatment to these images, volumetric evolutions between flights were revealed through a DDVM (Difference of Digital volumetric Model), in order to study sand movements on coastal sand dunes.
SYSTEM CONSIDERATIONS AND CHALLENDES IN 3D MAPPING AND MODELING USING LOW-COST UAV SYSTEMS
Authors: Lari Z. , El-Sheimy N.
Published: August 2015

Abstract. In the last few years, low-cost UAV systems have been acknowledged as an affordable technology for geospatial data acquisition that can meet the needs of a variety of traditional and non-traditional mapping applications. In spite of its proven potential, UAV-based mapping is still lacking in terms of what is needed for it to become an acceptable mapping tool. In other words, a well-designed system architecture that considers payload restrictions as well as the specifications of the utilized direct geo-referencing component and the imaging systems in light of the required mapping accuracy and intended application is still required. Moreover, efficient data processing workflows, which are capable of delivering the mapping products with the specified quality while considering the synergistic characteristics of the sensors onboard, the wide range of potential users who might lack deep knowledge in mapping activities, and time constraints of emerging applications, are still needed to be adopted. Therefore, the introduced challenges by having low-cost imaging and georeferencing sensors onboard UAVs with limited payload capability, the necessity of efficient data processing techniques for delivering required products for intended applications, and the diversity of potential users with insufficient mapping-related expertise needs to be fully investigated and addressed by UAV-based mapping research efforts. This paper addresses these challenges and reviews system considerations, adaptive processing techniques, and quality assurance/quality control procedures for achievement of accurate mapping products from these systems.
WIMUAS: DEVELOPING A TOOL TO REVIEW WILDLIFE DATA FROM VARIOUS UAS FLIGHT PLANS
Authors: Linchant J. , Lhoest S. , Quevauvillers S. , Semeki J. , Lejeune P. , Vermeulen C.
Published: August 2015

Abstract. To get around UAS limitations and propose a viable solution for wildlife monitoring, the development of new inventory methods is needed. However, most authors use the classic systematic transect method as data processing and statistics are easier. We thus created an application to process data from every type of flight plan and to help detect and compare observations on large datasets. WiMUAS is a small software compatible with the open-source QGIS© that allows the creation of visual maps compatible with geographical information systems based on telemetry data and payload parameters to estimate the covered area. The application also has a slider for animal detection that allows multiple observers to record and compare their results for accurate counts. We then tested it on data from a trial realized on savannah animal populations in Democratic Republic of Congo using the Falcon UAS. We created a new type of flight plan, a rosette-shaped design that can be covered in three flights,.and repeated it twice. More than 5000 images were collected during the six flights. Image projection gives an area of 12,4 km2 for the first trial and of 12,1 km2 for the second. The mean sampling rate for both test is 6,1 %. Observers spotted buffaloes, hippos, warthogs and various antelopes with different success over an average rate of 8 images reviewed per minute. Resulting densities observed by the three observers are similar for each test (coefficient of variation 6,9 and 8,6 % respectively) but mean densities vary a lot between the two trials (23,8 and 6,5 animals/km2 respectively).
YOU DESCRIBE IT, I WILL NAME IT: AN APPROACH TO ALLEVIATE THE EFFECT OF USERS’ SEMANTICS IN ASSIGNING TAGS TO FEATURES IN VGI
Authors: Hassany Pazoky S. , Karimipour F. , Hakimpour F.
Published: August 2015

Abstract. As an important factor of VGI quality, this paper focuses on uncertainty arisen in assigning tags to features by VGI users. The VGI portals ask their users to assign (or tag) one or more data types to features, from a set of pre-defined types, whose meanings may be vague for the user, or distinctions between some of them are not clear, i.e. depend on the users’ semantics. This research believes such uncertainties are the results of perceptual issues arising in serial communication between the system and the user. We categorize the problem, and then utilize semantic modelling to reduce such uncertainties. A hierarchy of feature types is produced. At each step, users are asked a simple question with clear distinct answers, which gradually directs the user to the right type. We will describe the approach and present the initial results for the hierarchy produced for major linear features of OpenStreetMap.
DEDICATED PAYLOADS FOR LOWALTITUDE REMOTE SENSING IN NATURAL ENVIRONMENTS
Authors: Beaudoin L. , Avanthey L. , Gademer A. , Roux M. , Rudant J.-P.
Published: August 2015

Abstract. The recent years have shown a growing interest in low-altitude remote sensing for the study of natural areas. But natural environments lead to many constraints on acquisition sensors, which add to operational and carriers constraints. This article is a feedback on the design of two of these sensors.
SEMI-BLIND SOURCE SEPARATION FOR ESTIMATION OF CLAY CONTENT OVER SEMI-VEGETATED AREAS, FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE DATA
Authors: Ouerghemmi W. , Gomez C. , Nacer S. , Lagacherie P.
Published: August 2015

Abstract. The applicability of Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery for soil property mapping decreases when surfaces are partially covered by vegetation. The objective of this research was to develop and evaluate a methodology based on the “double-extraction” technique, for clay content estimation over semi-vegetated surfaces using VNIR/SWIR hyperspectral airborne data. The “double-extraction” technique initially proposed by Ouerghemmi et al. (2011) consists of 1) an extraction of a soil reflectance spectrum ssoil from semi-vegetated spectra using a Blind Source Separation technique, and 2) an extraction of clay content from the soil reflectance spectrum ssoil, using a multivariate regression method. In this paper, the Source Separation approach is Semi-Blind thanks to the integration of field knowledge in Source Separation model. And the multivariate regression method is a partial least squares regression (PLSR) model. This study employed VNIR/SWIR HyMap airborne data acquired in a French Mediterranean region over an area of 24 km2. Our results showed that our methodology based on the “double-extraction” technique is accurate for clay content estimation when applied to pixels under a specific Cellulose Absorption Index threshold. Finally the clay content can be estimated over around 70% of the semi-vegetated pixels of our study area, which may offer an extension of soil properties mapping, at the moment restricted to bare soils.
MAPPING OF FOLIAR CONTENT USING RADIATIVE TRANSFER MODELING AND VIS-NIR HYPERSPECTRAL CLOSE-RANGE REMOTE-SENSING
Authors: Jay S. , Bendoula R. , Hadoux X. , Gorretta N.
Published: August 2015

Abstract. Most methods for retrieving foliar content from hyperspectral data are well adapted either to remote-sensing scale, for which each spectral measurement has a spatial resolution ranging from a few dozen centimeters to a few hundred meters, or to leaf scale, for which an integrating sphere is required to collect the spectral data. In this study, we present a method for estimating leaf optical properties from hyperspectral images having a spatial resolution of a few millimeters or centimeters. In presence of a single light source assumed to be directional, it is shown that leaf hyperspectral measurements can be related to the directional hemispherical reflectance simulated by the PROSPECT radiative transfer model using two other parameters. The first one is a multiplicative term that is related to local leaf angle and illumination zenith angle. The second parameter is an additive specular-related term that models BRDF effects. Our model was tested on visible and near infrared hyperspectral images of leaves of various species, that were acquired under laboratory conditions. Introducing these two additional parameters into the inversion scheme leads to improved estimation results of PROSPECT parameters when compared to original PROSPECT. In particular, the RMSE for local chlorophyll content estimation was reduced by 21% (resp. 32%) when tested on leaves placed in horizontal (resp. sloping) position. Furthermore, inverting this model provides interesting information on local leaf angle, which is a crucial parameter in classical remote-sensing.
3D WEB VISUALIZATION OF ENVIRONMENTAL INFORMATION – INTEGRATION OF HETEROGENEOUS DATA SOURCES WHEN PROVIDING NAVIGATION AND INTERACTION
Authors: Herman L. , Řezník T.
Published: August 2015

Abstract. 3D information is essential for a number of applications used daily in various domains such as crisis management, energy management, urban planning, and cultural heritage, as well as pollution and noise mapping, etc. This paper is devoted to the issue of 3D modelling from the levels of buildings to cities. The theoretical sections comprise an analysis of cartographic principles for the 3D visualization of spatial data as well as a review of technologies and data formats used in the visualization of 3D models. Emphasis was placed on the verification of available web technologies; for example, X3DOM library was chosen for the implementation of a proof-of-concept web application. The created web application displays a 3D model of the city district of Nový Lískovec in Brno, the Czech Republic. The developed 3D visualization shows a terrain model, 3D buildings, noise pollution, and other related information. Attention was paid to the areas important for handling heterogeneous input data, the design of interactive functionality, and navigation assistants. The advantages, limitations, and future development of the proposed concept are discussed in the conclusions.
ASSESSMENT OF THE VOLUNTEERED GEOGRAPHIC INFORMATION FEEDBACK SYSTEM FOR THE DUTCH TOPOGRAPHICAL KEY REGISTER
Authors: Grus M. , te Winkel D.
Published: August 2015

Abstract. Since Topographical Key Register has become an open data the amount of users increased enormously. The highest grow was in the private users group. The increasing number of users and their growing demand for high actuality of the topographic data sets motivates the Dutch Kadaster to innovate and improve the Topographical Key Register (BRT). One of the initiatives was to provide a voluntary geographical information project aiming at providing a user-friendly feedback system adjusted to all kinds of user groups. The feedback system is a compulsory element of the Topographical Key Register in the Netherlands. The Dutch Kadaster is obliged to deliver a feedback system and the key-users are obliged to use it. The aim of the feedback system is to improve the quality and stimulate the usage of the data. The results of the pilot shows that the user-friendly and open to everyone feedback system contributes enormously to improve the quality of the topographic dataset.
IQPC 2015 Track: EVALUATION OF AUTOMATICALLY GENERATED 2D FOOTPRINTS FROM URBAN LIDAR DATA
Authors: Truong-Hong L. , Laefer D. , Bisheng Y. , Ronggang H. , Jianping L.
Published: August 2015

Abstract. Over the last decade, several automatic approaches have been proposed to extract and reconstruct 2D building footprints and 2D road profiles from ALS data, satellite images, and/or aerial imagery. Since these methods have to date been applied to various data sets and assessed through a variety of different quality indicators and ground truths, comparing the relative effectiveness of the techniques and identifying their strengths and short-comings has not been possible in a systematic way. This contest as part of IQPC15 was designed to determine pros and cons of submitted approaches in generating 2D footprint of a city region from ALS data. Specifically, participants were asked to submit 2D footprints (building outlines and road profiles) derived from ALS data from a highly dense dataset (approximately 225 points/m2) across a 1km2 of Dublin, Ireland’s city centre. The proposed evaluation strategies were designed to measure not only the capacity of each method to detect and reconstruct 2D buildings and roads but also the quality of the reconstructed building and road models in terms of shape similarity and positional accuracy.
OPERATIONAL APPLICATION OF THE LANDSAT TIMESERIES TO ADDRESS LARGE AREA LANDCOVER UNDERSTANDING
Authors: Scarth P. , Armston J. , Flood N. , Denham R. , Collett L. , Watson F. , Trevithick B. , Muir J. , Goodwin N. , Tindall D. , Phinn S.
Published: August 2015

Abstract. State Government agencies in northern and eastern Australia and the University of Queensland, Brisbane, have been collaborating through the Joint Remote Sensing Research Program (JRSRP). This has resulted in a significant acceleration in the development and successful operational application of remote sensing methods for the JRSRP members and the various state and national programs and policies which they support. The JRSRP provides an open and collaborative mechanism and governance structure to successfully bring together a unique combination of expertise in image processing, field data collection, and data integration approaches to deliver accurate, repeatable and robust methods for mapping and monitoring Australia’s unique ecosystems. Remote sensing provides spatially- and temporally-comprehensive information about land cover features at a range of scales and often for minimal cost compared to traditional mapping and monitoring approaches. This makes remote sensing a very useful operational mapping and monitoring tool for land managers, particularly in the vast rangelands of Australia. This paper outlines recent developments in remote sensing and modelling products that are being used operationally by JRSRP members to address large area landcover understanding.
AUTOMATED LARGE SCALE PARAMETER EXTRACTION OF ROAD-SIDE TREES SAMPLED BY A LASER MOBILE MAPPING SYSTEM
Authors: Lindenbergh R. C. , Berthold D. , Sirmacek B. , Herrero-Huerta M. , Wang J. , Ebersbach D.
Published: August 2015

Abstract. In urbanized Western Europe trees are considered an important component of the built-up environment. This also means that there is an increasing demand for tree inventories. Laser mobile mapping systems provide an efficient and accurate way to sample the 3D road surrounding including notable roadside trees. Indeed, at, say, 50 km/h such systems collect point clouds consisting of half a million points per 100m. Method exists that extract tree parameters from relatively small patches of such data, but a remaining challenge is to operationally extract roadside tree parameters at regional level. For this purpose a workflow is presented as follows: The input point clouds are consecutively downsampled, retiled, classified, segmented into individual trees and upsampled to enable automated extraction of tree location, tree height, canopy diameter and trunk diameter at breast height (DBH). The workflow is implemented to work on a laser mobile mapping data set sampling 100 km of road in Sachsen, Germany and is tested on a stretch of road of 7km long. Along this road, the method detected 315 trees that were considered well detected and 56 clusters of tree points were no individual trees could be identified. Using voxels, the data volume could be reduced by about 97 % in a default scenario. Processing the results of this scenario took ~2500 seconds, corresponding to about 10 km/h, which is getting close to but is still below the acquisition rate which is estimated at 50 km/h.
3D web visualization of huge CityGML models
Authors: Prandi F. , Devigili F. , Soave M. , Di Staso U. , De Amicis R.
Published: August 2015

Abstract. Nowadays, rapid technological development into acquiring geo-spatial information; joined to the capabilities to process these data in a relative short period of time, allows the generation of detailed 3D textured city models that will become an essential part of the modern city information infrastructure (Spatial Data Infrastructure) and, can be used to integrate various data from different sources for public accessible visualisation and many other applications. One of the main bottlenecks, which at the moment limit the use of these datasets to few experts, is a lack on efficient visualization systems through the web and interoperable frameworks that allow standardising the access to the city models. The work presented in this paper tries to satisfy these two requirements developing a 3D web-based visualization system based on OGC standards and effective visualization concepts. The architectural framework, based on Services Oriented Architecture (SOA) concepts, provides the 3D city data to a web client designed to support the view process in a very effective way. The first part of the work is to design a framework compliant to the 3D Portrayal Service drafted by the of the Open Geospatial Consortium (OGC) 3D standardization working group. The latter is related to the development of an effective web client able to render in an efficient way the 3D city models.
IQPC 2015 TRACK: TREE SEPARATION AND CLASSIFICATION IN MOBILE MAPPING LIDAR DATA
Authors: Gorte B. , Oude Elberink S. , Sirmacek B. , Wang J.
Published: August 2015

Abstract. The European FP7 project IQmulus yearly organizes several processing contests, where submissions are requested for novel algorithms for point cloud and other big geodata processing. This paper describes the set-up and execution of a contest having the purpose to evaluate state-of-the-art algorithms for Mobile Mapping System point clouds, in order to detect and identify (individual) trees. By the nature of MMS these are trees in the vicinity of the road network (rather than in forests). Therefore, part of the challenge is distinguishing between trees and other objects, such as buildings, street furniture, cars etc. Three submitted segmentation and classification algorithms are thus evaluated.
CHANGE DETECTION AND LAND USE / LAND COVER DATABASE UPDATING USING IMAGE SEGMENTATION, GIS ANALYSIS AND VISUAL INTERPRETATION
Authors: Mas J.-F. , González R.
Published: August 2015

Abstract. This article presents a hybrid method that combines image segmentation, GIS analysis, and visual interpretation in order to detect discrepancies between an existing land use/cover map and satellite images, and assess land use/cover changes. It was applied to the elaboration of a multidate land use/cover database of the State of Michoacán, Mexico using SPOT and Landsat imagery. The method was first applied to improve the resolution of an existing 1:250,000 land use/cover map produced through the visual interpretation of 2007 SPOT images. A segmentation of the 2007 SPOT images was carried out to create spectrally homogeneous objects with a minimum area of two hectares. Through an overlay operation with the outdated map, each segment receives the “majority” category from the map. Furthermore, spectral indices of the SPOT image were calculated for each band and each segment; therefore, each segment was characterized from the images (spectral indices) and the map (class label). In order to detect uncertain areas which present discrepancy between spectral response and class label, a multivariate trimming, which consists in truncating a distribution from its least likely values, was applied. The segments that behave like outliers were detected and labeled as “uncertain” and a probable alternative category was determined by means of a digital classification using a decision tree classification algorithm. Then, the segments were visually inspected in the SPOT image and high resolution imagery to assign a final category. The same procedure was applied to update the map to 2014 using Landsat imagery. As a final step, an accuracy assessment was carried out using verification sites selected from a stratified random sampling and visually interpreted using high resolution imagery and ground truth.
CALIBRATING CELLULAR AUTOMATA OF LAND USE/COVER CHANGE MODELS USING A GENETIC ALGORITHM
Authors: Mas J. F. , Soares-Filho B. , Rodrigues H.
Published: August 2015

Abstract. Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computational LUCC models use a cellular automata to replicate the land use / cover patches. Generally, model evaluation is based on assessing the location of the simulated changes in comparison to the true locations but landscapes metrics can also be used to assess landscape structure. As model complexity increases, the need to improve calibration and assessment techniques also increases. In this study, we applied a genetic algorithm tool to optimize cellular automata’s parameters to simulate deforestation in a region of the Brazilian Amazon. We found that the genetic algorithm was able to calibrate the model to simulate more realistic landscape in term of connectivity. Results show also that more realistic simulated landscapes are often obtained at the expense of the location coincidence. However, when considering processes such as the fragmentation impacts on biodiversity, the simulation of more realistic landscape structure should be preferred to spatial coincidence performance.