bluuebunny/crossref_metadata_2025 huggingface dataset:
DENSE 3D POINT CLOUD GENERATION FROM UAV IMAGES FROM IMAGE MATCHING AND GLOBAL OPTIMAZATION
Authors: Rhee S. , Kim T.
Published: August 2016

3D spatial information from unmanned aerial vehicles (UAV) images is usually provided in the form of 3D point clouds. For various UAV applications, it is important to generate dense 3D point clouds automatically from over the entire extent of UAV images. In this paper, we aim to apply image matching for generation of local point clouds over a pair or group of images and global optimization to combine local point clouds over the whole region of interest. We tried to apply two types of image matching, an object space-based matching technique and an image space-based matching technique, and to compare the performance of the two techniques. The object space-based matching used here sets a list of candidate height values for a fixed horizontal position in the object space. For each height, its corresponding image point is calculated and similarity is measured by grey-level correlation. The image space-based matching used here is a modified relaxation matching. We devised a global optimization scheme for finding optimal pairs (or groups) to apply image matching, defining local match region in image- or object- space, and merging local point clouds into a global one. For optimal pair selection, tiepoints among images were extracted and stereo coverage network was defined by forming a maximum spanning tree using the tiepoints. From experiments, we confirmed that through image matching and global optimization, 3D point clouds were generated successfully. However, results also revealed some limitations. In case of image-based matching results, we observed some blanks in 3D point clouds. In case of object space-based matching results, we observed more blunders than image-based matching ones and noisy local height variations. We suspect these might be due to inaccurate orientation parameters. The work in this paper is still ongoing. We will further test our approach with more precise orientation parameters.
ACCURACY ASSESSMENT OF COASTAL TOPOGRAPHY DERIVED FROM UAV IMAGES
Authors: Long N. , Millescamps B. , Pouget F. , Dumon A. , Lachaussée N. , Bertin X.
Published: August 2016

To monitor coastal environments, Unmanned Aerial Vehicle (UAV) is a low-cost and easy to use solution to enable data acquisition with high temporal frequency and spatial resolution. Compared to Light Detection And Ranging (LiDAR) or Terrestrial Laser Scanning (TLS), this solution produces Digital Surface Model (DSM) with a similar accuracy. To evaluate the DSM accuracy on a coastal environment, a campaign was carried out with a flying wing (eBee) combined with a digital camera. Using the Photoscan software and the photogrammetry process (Structure From Motion algorithm), a DSM and an orthomosaic were produced. Compared to GNSS surveys, the DSM accuracy is estimated. Two parameters are tested: the influence of the methodology (number and distribution of Ground Control Points, GCPs) and the influence of spatial image resolution (4.6 cm vs 2 cm). The results show that this solution is able to reproduce the topography of a coastal area with a high vertical accuracy (< 10 cm). The georeferencing of the DSM require a homogeneous distribution and a large number of GCPs. The accuracy is correlated with the number of GCPs (use 19 GCPs instead of 10 allows to reduce the difference of 4 cm); the required accuracy should be dependant of the research problematic. Last, in this particular environment, the presence of very small water surfaces on the sand bank does not allow to improve the accuracy when the spatial resolution of images is decreased.
ACCURACY COMPARISON OF VHR SYSTEMATIC-ORTHO SATELLITE IMAGERIES AGAINST VHR ORTHORECTIFIED IMAGERIES USING GCP
Authors: Widyaningrum E. , Fajari M. , Octariady J.
Published: August 2016

The Very High Resolution (VHR) satellite imageries such us Pleiades, WorldView-2, GeoEye-1 used for precise mapping purpose must be corrected from any distortion to achieve the expected accuracy. Orthorectification is performed to eliminate geometric errors of the VHR satellite imageries. Orthorectification requires main input data such as Digital Elevation Model (DEM) and Ground Control Point (GCP). The VHR systematic-ortho imageries were generated using SRTM 30m DEM without using any GCP data. The accuracy value differences of VHR systematic-ortho imageries and VHR orthorectified imageries using GCP currently is not exactly defined. This study aimed to identified the accuracy comparison of VHR systematic-ortho imageries against orthorectified imageries using GCP. Orthorectified imageries using GCP created by using Rigorous model. Accuracy evaluation is calculated by using several independent check points.
DEM EXTRACTION FROM WORLDVIEW-3 STEREO-IMAGES AND ACCURACY EVALUATION
Authors: Hu F. , Gao X. M. , Li G.Y. , Li M.
Published: August 2016

This paper validates the potentials of Worldview-3 satellite images in large scale topographic mapping, by choosing Worldview-3 along-track stereo-images of Yi Mountain area in Shandong province China for DEM extraction and accuracy evaluation. Firstly, eighteen accurate and evenly-distributed GPS points are collected in field and used as GCPs/check points, the image points of which are accurately measured, and also tie points are extracted from image matching; then, the RFM-based block adjustment to compensate the systematic error in image orientation is carried out and the geo-positioning accuracy is calculated and analysed; next, for the two stereo-pairs of the block, DSMs are separately constructed and mosaicked as an entirety, and also the corresponding DEM is subsequently generated; finally, compared with the selected check points from high-precision airborne LiDAR point cloud covering the same test area, the accuracy of the generated DEM with 2-meter grid spacing is evaluated by the maximum (max.), minimum (min.), mean and standard deviation (std.) values of elevation biases. It is demonstrated that, for Worldview-3 stereo-images used in our research, the planimetric accuracy without GCPs is about 2.16 m (mean error) and 0.55 (std. error), which is superior to the nominal value, while the vertical accuracy is about -1.61 m (mean error) and 0.49 m (std. error); with a small amount of GCPs located in the center and four corners of the test area, the systematic error can be well compensated. The std. value of elevation biases between the generated DEM and the 7256 LiDAR check points are about 0.62 m. If considering the potential uncertainties in the image point measurement, stereo matching and also elevation editing, the accuracy of generating DEM from Worldview-3 stereo-images should be more desirable. Judging from the results, Worldview-3 has the potential for 1:5000 or even larger scale mapping application.
Radiometric Cross-calibration of KOMPSAT-3A with Landsat-8
Authors: Shin D. Y. , Ahn H. Y. , Lee S. G. , Choi C. U. , Kim J. S.
Published: August 2016

In this study, Cross calibration was conducted at the Libya 4 PICS site on 2015 using Landsat-8 and KOMPSAT-3A. Ideally a cross calibration should be calculated for each individual scene pair because on any given date the TOA spectral profile is influenced by sun and satellite view geometry and the atmospheric conditions. However, using the near-simultaneous images minimizes this effect because the sensors are viewing the same atmosphere. For the cross calibration, the calibration coefficient was calculated by comparing the at sensor spectral radiance for the same location calculated using the Landsat-8 calibration parameters in metadata and the DN of KOMPSAT-3A for the regions of interest (ROI). Cross calibration can be conducted because the satellite sensors used for overpass have a similar bandwidth. However, not all satellites have the same color filter transmittance and sensor reactivity, even though the purpose is to observe the visible bands. Therefore, the differences in the RSR should be corrected. For the cross-calibration, a calibration coefficient was calculated using the TOA radiance and KOMPSAT-3 DN of the Landsat-8 OLI overpassed at the Libya 4 Site, As a result, the accuracy of the calibration coefficient at the site was assumed to be ± 1.0%. In terms of the results, the radiometric calibration coefficients suggested here are thought to be useful for maintaining the optical quality of the KOMPSAT-3A.
GEOSPATIAL ANALYSIS USING REMOTE SENSING IMAGES: CASE STUDIES OF ZONGULDAK TEST FIELD
Authors: Bayık Çağlar , Topan Hüseyin , Özendi Mustafa , Oruç Murat , Cam Ali , Abdikan Saygın
Published: August 2016

Inclined topographies are one of the most challenging problems for geospatial analysis of air-borne and space-borne imageries. However, flat areas are mostly misleading to exhibit the real performance. For this reason, researchers generally require a study area which includes mountainous topography and various land cover and land use types. Zonguldak and its vicinity is a very suitable test site for performance investigation of remote sensing systems due to the fact that it contains different land use types such as dense forest, river, sea, urban area; different structures such as open pit mining operations, thermal power plant; and its mountainous structure. In this paper, we reviewed more than 120 proceeding papers and journal articles about geospatial analysis that are performed on the test field of Zonguldak and its surroundings. Geospatial analysis performed with imageries include elimination of systematic geometric errors, 2/3D georeferencing accuracy assessment, DEM and DSM generation and validation, ortho-image production, evaluation of information content, image classification, automatic feature extraction and object recognition, pan-sharpening, land use and land cover change analysis and deformation monitoring. In these applications many optical satellite images are used i.e. ASTER, Bilsat-1, IKONOS, IRS-1C, KOMPSAT-1, KVR-1000, Landsat-3-5-7, Orbview-3, QuickBird, Pleiades, SPOT-5, TK-350, RADARSAT-1, WorldView-1-2; as well as radar data i.e. JERS-1, Envisat ASAR, TerraSAR-X, ALOS PALSAR and SRTM. These studies are performed by Departments of Geomatics Engineering at Bülent Ecevit University, at İstanbul Technical University, at Yıldız Technical University, and Institute of Photogrammetry and GeoInformation at Leibniz University Hannover. These studies are financially supported by TÜBİTAK (Turkey), the Universities, ESA, Airbus DS, ERSDAC (Japan) and Jülich Research Centre (Germany).
CMOS IMAGING SENSOR TECHNOLOGY FOR AERIAL MAPPING CAMERAS
Authors: Neumann Klaus , Welzenbach Martin , Timm Martin
Published: August 2016

In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera.

 In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs.

 Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.
CALIBRATION OF LOW COST RGB AND NIR UAV CAMERAS
Authors: Fryskowska A. , Kedzierski M. , Grochala A. , Braula A.
Published: August 2016

Non-metric digital cameras are being widely used for photogrammetric studies. The increase in resolution and quality of images obtained by non-metric cameras, allows to use it in low-cost UAV and terrestrial photogrammetry. Imagery acquired with non-metric cameras can be used in 3D modeling of objects or landscapes, reconstructing of historical sites, generating digital elevation models (DTM), orthophotos, or in the assessment of accidents.

 Non-metric digital camcorders are characterized by instability and ignorance of the interior orientation parameters. Therefore, the use of these devices requires prior calibration. Calibration research was conducted using non-metric camera, different calibration tests and various software.

 The first part of the paper contains a brief theoretical introduction including the basic definitions, like the construction of non-metric cameras or description of different optical distortions. The second part of the paper contains cameras calibration process, details of the calibration methods and models that have been used. Sony Nex 5 camera calibration has been done using software: Image Master Calib, Matlab - Camera Calibrator application and Agisoft Lens. For the study 2D test fields has been used. As a part of the research a comparative analysis of the results have been done.
TWO-STEP CAMERA CALIBRATION METHOD DEVELOPED FOR MICRO UAV'S
Authors: Gašparović M. , Gajski D.
Published: August 2016

The development of unmanned aerial vehicles (UAVs) and continuous price reduction of unmanned systems attracted us to this research. Professional measuring systems are dozens of times more expensive and often heavier than "amateur", non-metric UAVs. For this reason, we tested the DJI Phantom 2 Vision Plus UAV. Phantom’s smaller mass and velocity can develop less kinetic energy in relation to the professional measurement platforms, which makes it potentially less dangerous for use in populated areas. In this research, we wanted to investigate the ability of such non-metric UAV and find the procedures under which this kind of UAV may be used for the photogrammetric survey. It is important to emphasize that UAV is equipped with an ultra wide-angle camera with 14MP sensor. Calibration of such cameras is a complex process. In the research, a new two-step process is presented and developed, and the results are compared with standard one-step camera calibration procedure. Two-step process involves initially removed distortion on all images, and then uses these images in the phototriangulation with self-calibration. The paper presents statistical indicators which proved that the proposed two-step process is better and more accurate procedure for calibrating those types of cameras than standard one-step calibration. Also, we suggest two-step calibration process as the standard for ultra-wideangle cameras for unmanned aircraft.
RPAS ACCURACY TESTING FOR USING IT IN THE CADASTRE OF REAL ESTATES OF THE CZECH REPUBLIC
Authors: Housarová E. , Pavelka K. , Šedina J.
Published: August 2016

In the last few years, interest in the collection of data using remotely piloted aircraft systems (RPAS) has sharply risen. RPAS technology has a very wide area of use; one of its main advantages is its accuracy, timeliness of data, frequency of collecting data and low operating costs. RPAS can be used for the mapping of small, dangerous and inaccessible areas in contrast with ordinary aerial photogrammetry. In the cadastre of real estates of the Czech Republic, it is possible to map out areas by using aerial photogrammetry, so it has been done in the past. However, this is a relatively expensive and complex technology, and therefore we are looking for new alternatives. An alternative would be to use RPAS technology for data acquisition. The testing of the possibility of using RPAS for the cadastre of real estates of the Czech Republic is the subject of this paper. When evaluating results we compared point coordinates measured by geodetic method, GNSS technology and RPAS technology.
ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY
Authors: Kosmatin Fras M. , Kerin A. , Mesarič M. , Peterman V. , Grigillo D.
Published: August 2016

Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.
MULTI-TEMPORAL CROP SURFACE MODELS COMBINED WITH THE RGB VEGETATION INDEX FROM UAV-BASED IMAGES FOR FORAGE MONITORING IN GRASSLAND
Authors: Possoch M. , Bieker S. , Hoffmeister D. , Bolten A. , Schellberg J. , Bareth G.
Published: August 2016

Remote sensing of crop biomass is important in regard to precision agriculture, which aims to improve nutrient use efficiency and to develop better stress and disease management. In this study, multi-temporal crop surface models (CSMs) were generated from UAV-based dense imaging in order to derive plant height distribution and to determine forage mass. The low-cost UAV-based RGB imaging was carried out in a grassland experiment at the University of Bonn, Germany, in summer 2015. The test site comprised three consecutive growths including six different nitrogen fertilizer levels and three replicates, in sum 324 plots with a size of 1.5×1.5 m. Each growth consisted of six harvesting dates. RGB-images and biomass samples were taken at twelve dates nearly biweekly within two growths between June and September 2015. Images were taken with a DJI Phantom 2 in combination of a 2D Zenmuse gimbal and a GoPro Hero 3 (black edition). Overlapping images were captured in 13 to 16 m and overview images in approximately 60 m height at 2 frames per second. The RGB vegetation index (RGBVI) was calculated as the normalized difference of the squared green reflectance and the product of blue and red reflectance from the non-calibrated images. The post processing was done with Agisoft PhotoScan Professional (SfM-based) and Esri ArcGIS. 14 ground control points (GCPs) were located in the field, distinguished by 30 cm × 30 cm markers and measured with a RTK-GPS (HiPer Pro Topcon) with 0.01 m horizontal and vertical precision. The errors of the spatial resolution in x-, y-, z-direction were in a scale of 3-4 cm. From each survey, also one distortion corrected image was georeferenced by the same GCPs and used for the RGBVI calculation. The results have been used to analyse and evaluate the relationship between estimated plant height derived with this low-cost UAV-system and forage mass. Results indicate that the plant height seems to be a suitable indicator for forage mass. There is a robust correlation of crop height related with dry matter (R² = 0.6). The RGBVI seems not to be a suitable indicator for forage mass in grassland, although the results provided a medium correlation by combining plant height and RGBVI to dry matter (R² = 0.5).
TECHNICAL ASPECTS FOR THE CREATION OF A MULTI-DIMENSIONAL LAND INFORMATION SYSTEM
Authors: Ioannidis Charalabos , Potsiou Chryssy , Soile Sofia , Verykokou Styliani , Mourafetis George , Doulamis Nikolaos
Published: August 2016

The complexity of modern urban environments and civil demands for fast, reliable and affordable decision-making requires not only a 3D Land Information System, which tends to replace traditional 2D LIS architectures, but also the need to address the time and scale parameters, that is, the 3D geometry of buildings in various time instances (4th dimension) at various levels of detail (LoDs - 5th dimension). This paper describes and proposes solutions for technical aspects that need to be addressed for the 5D modelling pipeline. Such solutions include the creation of a 3D model, the application of a selective modelling procedure between various time instances and at various LoDs, enriched with cadastral and other spatial data, and a procedural modelling approach for the representation of the inner parts of the buildings. The methodology is based on automatic change detection algorithms for spatial-temporal analysis of the changes that took place in subsequent time periods, using dense image matching and structure from motion algorithms. The selective modelling approach allows a detailed modelling only for the areas where spatial changes are detected. The procedural modelling techniques use programming languages for the textual semantic description of a building; they require the modeller to describe its part-to-whole relationships. Finally, a 5D viewer is developed, in order to tackle existing limitations that accompany the use of global systems, such as the Google Earth or the Google Maps, as visualization software. An application based on the proposed methodology in an urban area is presented and it provides satisfactory results.
DETERMINING SPATIO-TEMPORAL CADASTRAL DATA REQUIREMENT FOR INFRASTRUCTURE OF LADM FOR TURKEY
Authors: Alkan M. , Polat Z. A.
Published: August 2016

Nowadays, the nature of land title and cadastral (LTC) data in the Turkey is dynamic from a temporal perspective which depends on the LTC operations. Functional requirements with respect to the characteristics are investigated based upon interviews of professionals in public and private sectors. These are; Legal authorities, Land Registry and Cadastre offices, Highway departments, Foundations, Ministries of Budget, Transportation, Justice, Public Works and Settlement, Environment and Forestry, Agriculture and Rural Affairs, Culture and Internal Affairs, State Institute of Statistics (SIS), execution offices, tax offices, real estate offices, private sector, local governments and banks. On the other hand, spatio-temporal LTC data very important component for creating infrastructure of Land Administration Model (LADM). For this reason, spatio-temporal LTC data needs for LADM not only updated but also temporal. The investigations ended up with determine temporal analyses of LTC data, traditional LTC system and tracing temporal analyses in traditional LTC system. In the traditional system, the temporal analyses needed by all these users could not be performed in a rapid and reliable way. The reason for this is that the traditional LTC system is a manual archiving system. The aims and general contents of this paper: (1) define traditional LTC system of Turkey; (2) determining the need for spatio-temporal LTC data and analyses for core domain model for LADM. As a results of temporal and spatio-temporal analysis LTC data needs, new system design is important for the Turkish LADM model. Designing and realizing an efficient and functional Temporal Geographic Information Systems (TGIS) is inevitable for the Turkish LADM core infrastructure. Finally this paper outcome is creating infrastructure for design and develop LADM for Turkey.
HISTORICAL GIS DATA AND CHANGES IN URBAN MORPHOLOGICAL PARAMETERS FOR THE ANALYSIS OF URBAN HEAT ISLANDS IN HONG KONG
Authors: Peng F. , Wong M. S. , Nichol J. E. , Chan P. W.
Published: August 2016

Rapid urban development between the 1960 and 2010 decades have changed the urban landscape and pattern in the Kowloon Peninsula of Hong Kong. This paper aims to study the changes of urban morphological parameters between the 1985 and 2010 and explore their influences on the urban heat island (UHI) effect. This study applied a mono-window algorithm to retrieve the land surface temperature (LST) using Landsat Thematic Mapper (TM) images from 1987 to 2009. In order to estimate the effects of local urban morphological parameters to LST, the global surface temperature anomaly was analysed. Historical 3D building model was developed based on aerial photogrammetry technique using aerial photographs from 1964 to 2010, in which the urban digital surface models (DSMs) including elevations of infrastructures and buildings have been generated. Then, urban morphological parameters (i.e. frontal area index (FAI), sky view factor (SVF)), vegetation fractional cover (VFC), global solar radiation (GSR), Normalized Difference Built-Up Index (NDBI), wind speed were derived. Finally, a linear regression method in Waikato Environment for Knowledge Analysis (WEKA) was used to build prediction model for revealing LST spatial patterns. Results show that the final apparent surface temperature have uncertainties less than 1 degree Celsius. The comparison between the simulated and actual spatial pattern of LST in 2009 showed that the correlation coefficient is 0.65, mean absolute error (MAE) is 1.24 degree Celsius, and root mean square error (RMSE) is 1.51 degree Celsius of 22,429 pixels.
COGNITIVE ASPECTS OF COLLABORATION IN 3D VIRTUAL ENVIRONMENTS
Authors: Juřík V. , Herman L. , Kubíček P. , Stachoň Z. , Šašinka Č.
Published: August 2016

Human-computer interaction has entered the 3D era. The most important models representing spatial information — maps — are transferred into 3D versions regarding the specific content to be displayed. Virtual worlds (VW) become promising area of interest because of possibility to dynamically modify content and multi-user cooperation when solving tasks regardless to physical presence. They can be used for sharing and elaborating information via virtual images or avatars. Attractiveness of VWs is emphasized also by possibility to measure operators’ actions and complex strategies. Collaboration in 3D environments is the crucial issue in many areas where the visualizations are important for the group cooperation. Within the specific 3D user interface the operators' ability to manipulate the displayed content is explored regarding such phenomena as situation awareness, cognitive workload and human error. For such purpose, the VWs offer a great number of tools for measuring the operators’ responses as recording virtual movement or spots of interest in the visual field. Study focuses on the methodological issues of measuring the usability of 3D VWs and comparing them with the existing principles of 2D maps. We explore operators’ strategies to reach and interpret information regarding the specific type of visualization and different level of immersion.
SIMULATING NAVIGATION WITH VIRTUAL 3D GEOVISUALIZATIONS – A FOCUS ON MEMORY RELATED FACTORS
Authors: Lokka I. , Çöltekin A.
Published: August 2016

The use of virtual environments (VE) for navigation-related studies, such as spatial cognition and path retrieval has been widely adopted in cognitive psychology and related fields. What motivates the use of VEs for such studies is that, as opposed to real-world, we can control for the confounding variables in simulated VEs. When simulating a geographic environment as a virtual world with the intention to train navigational memory in humans, an effective and efficient visual design is important to facilitate the amount of recall. However, it is not yet clear what amount of information should be included in such visual designs intended to facilitate remembering: there can be too little or too much of it. Besides the amount of information or level of detail, the types of visual features (‘elements’ in a visual scene) that should be included in the representations to create memorable scenes and paths must be defined. We analyzed the literature in cognitive psychology, geovisualization and information visualization, and identified the key factors for studying and evaluating geovisualization designs for their function to support and strengthen human navigational memory. The key factors we identified are: i) the individual abilities and age of the users, ii) the level of realism (LOR) included in the representations and iii) the context in which the navigation is performed, thus specific tasks within a case scenario. Here we present a concise literature review and our conceptual development for follow-up experiments.
ASSESSING URBAN DROUGHTS IN A SMART CITY FRAMEWORK
Authors: Obringer R. , Zhang X. , Mallick K. , Alemohammad S. H. , Niyogi D.
Published: August 2016

This study aims to integrate environmental data for drought monitoring to reduce uncertainty in urban drought characterization as part of the smart city framework. Currently, drought monitoring in urban areas is a challenge. This is due, in part, to a lack of knowledge on the subject of urban droughts and urban drought vulnerability. A critical part to assessing urban drought and implementing the necessary policies is determining drought conditions. Often the timing and severity of the drought can leave cities to enforce water restrictions, so accuracy of this determination has socioeconomic implications. To determine drought conditions, we need to know the water balance over the urban landscape, of which evapotranspiration (ET) is a key variable. However, ET data and models have high uncertainty when compared to other hydrological variables (i.e., precipitation). This is largely due to ill-defined empirical models for characterizing the urban surface resistance parameter (rs) that is used in ET calculations. We propose a method to estimate rs values using a combination of the Surface Temperature Initiated Closure (STIC) method that calculates regional evapotranspiration data and an inverted version of the Penman-Monteith equation. We use this approach across the region surrounding Indianapolis, IN (USA) from 2010-2014. We discuss the potential for this method to be integrated in to smart city framework to improve urban drought assessment.
STRUCTURED LIGHT BASED 3D SCANNING FOR SPECULAR SURFACE BY THE COMBINATION OF GRAY CODE AND PHASE SHIFTING
Authors: Zhang Yujia , Yilmaz Alper
Published: August 2016

Surface reconstruction using coded structured light is considered one of the most reliable techniques for high-quality 3D scanning. With a calibrated projector-camera stereo system, a light pattern is projected onto the scene and imaged by the camera. Correspondences between projected and recovered patterns are computed in the decoding process, which is used to generate 3D point cloud of the surface. However, the indirect illumination effects on the surface, such as subsurface scattering and interreflections, will raise the difficulties in reconstruction. In this paper, we apply maximum min-SW gray code to reduce the indirect illumination effects of the specular surface. We also analysis the errors when comparing the maximum min-SW gray code and the conventional gray code, which justifies that the maximum min-SW gray code has significant superiority to reduce the indirect illumination effects. To achieve sub-pixel accuracy, we project high frequency sinusoidal patterns onto the scene simultaneously. But for specular surface, the high frequency patterns are susceptible to decoding errors. Incorrect decoding of high frequency patterns will result in a loss of depth resolution. Our method to resolve this problem is combining the low frequency maximum min-SW gray code and the high frequency phase shifting code, which achieves dense 3D reconstruction for specular surface. Our contributions include: (i) A complete setup of the structured light based 3D scanning system; (ii) A novel combination technique of the maximum min-SW gray code and phase shifting code. First, phase shifting decoding with sub-pixel accuracy. Then, the maximum min-SW gray code is used to resolve the ambiguity resolution. According to the experimental results and data analysis, our structured light based 3D scanning system enables high quality dense reconstruction of scenes with a small number of images. Qualitative and quantitative comparisons are performed to extract the advantages of our new combined coding method.
THE IQMULUS URBAN SHOWCASE: AUTOMATIC TREE CLASSIFICATION AND IDENTIFICATION IN HUGE MOBILE MAPPING POINT CLOUDS
Authors: Böhm J. , Bredif M. , Gierlinger T. , Krämer M. , Lindenberg R. , Liu K. , Michel F. , Sirmacek B.
Published: August 2016

Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.
CHANGE DETECTION OF MOBILE LIDAR DATA USING CLOUD COMPUTING
Authors: Liu Kun , Boehm Jan , Alis Christian
Published: August 2016

Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.
MULTISPECTRAL AIRBORNE LASER SCANNING FOR AUTOMATED MAP UPDATING
Authors: Matikainen Leena , Hyyppä Juha , Litkey Paula
Published: August 2016

During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.
INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY
Authors: Frommholz D. , Linkiewicz M. , Poznanska A. M.
Published: August 2016

This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and conditionally grown, fused and filtered morphologically. The output polygons are vectorized and reintegrated into the previously reconstructed buildings by sparsely ray-tracing their vertices. Finally the enhanced 3D models get stored as textured geometry for visualization and semantically annotated ”LOD-2.5” CityGML objects for GIS applications.
3D Building Reconstruction Using Dense Photogrammetric Point Cloud
Authors: Malihi S. , Valadan Zoej M. J. , Hahn M. , Mokhtarzade M. , Arefi H.
Published: August 2016

Three dimensional models of urban areas play an important role in city planning, disaster management, city navigation and other applications. Reconstruction of 3D building models is still a challenging issue in 3D city modelling. Point clouds generated from multi view images of UAV is a novel source of spatial data, which is used in this research for building reconstruction. The process starts with the segmentation of point clouds of roofs and walls into planar groups. By generating related surfaces and using geometrical constraints plus considering symmetry, a 3d model of building is reconstructed. In a refinement step, dormers are extracted, and their models are reconstructed. The details of the 3d reconstructed model are in LoD3 level, with respect to modelling eaves, fractions of roof and dormers.
CRITICAL ASSESSMENT OF OBJECT SEGMENTATION IN AERIAL IMAGE USING GEO-HAUSDORFF DISTANCE
Authors: Sun H. , Ding Y. , Huang Y. , Wang G.
Published: August 2016

Aerial Image records the large-range earth objects with the ever-improving spatial and radiometric resolution. It becomes a powerful tool for earth observation, land-coverage survey, geographical census, etc., and helps delineating the boundary of different kinds of objects on the earth both manually and automatically. In light of the geo-spatial correspondence between the pixel locations of aerial image and the spatial coordinates of ground objects, there is an increasing need of super-pixel segmentation and high-accuracy positioning of objects in aerial image. Besides the commercial software package of eCognition and ENVI, many algorithms have also been developed in the literature to segment objects of aerial images. But how to evaluate the segmentation results remains a challenge, especially in the context of the geo-spatial correspondence. The Geo-Hausdorff Distance (GHD) is proposed to measure the geo-spatial distance between the results of various object segmentation that can be done with the manual ground truth or with the automatic algorithms.Based on the early-breaking and random-sampling design, the GHD calculates the geographical Hausdorff distance with nearly-linear complexity. Segmentation results of several state-of-the-art algorithms, including those of the commercial packages, are evaluated with a diverse set of aerial images. They have different signal-to-noise ratio around the object boundaries and are hard to trace correctly even for human operators. The GHD value is analyzed to comprehensively measure the suitability of different object segmentation methods for aerial images of different spatial resolution. By critically assessing the strengths and limitations of the existing algorithms, the paper provides valuable insight and guideline for extensive research in automating object detection and classification of aerial image in the nation-wide geographic census. It is also promising for the optimal design of operational specification of remote sensing interpretation under the constraints of limited resource.
INDOOR NAVIGATION FROM POINT CLOUDS: 3D MODELLING AND OBSTACLE DETECTION
Authors: Díaz-Vilariño L. , Boguslawski P. , Khoshelham K. , Lorenzo H. , Mahdjoubi L.
Published: August 2016

In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation.

 Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored.

 In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.
3D MODELLING AND INTERACTIVE WEB-BASED VISUALIZATION OF CULTURAL HERITAGE OBJECTS
Authors: Koeva M. N.
Published: August 2016

Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria – a country with thousands of years of history and cultural heritage dating back to ancient civilizations. \this motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage.

 In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study discusses the advantages and disadvantages of these three approaches and their integration in multiple domains, such as web-based 3D city modelling, tourism and architectural 3D visualization. It was concluded that image-based modelling and panoramic visualisation are simple, fast and effective techniques suitable for simultaneous virtual representation of many objects. However, additional measurements or CAD information will be beneficial for obtaining higher accuracy.
FROM POINT CLOUD TO BIM: A MODELLING CHALLENGE IN THE CULTURAL HERITAGE FIELD
Authors: Tommasi C. , Achille C. , Fassi F.
Published: August 2016

Speaking about modelling the Cultural Heritage, nowadays it is no longer enough to build the mute model of a monument, but it has to contain plenty of information inside it, especially when we refer to existing construction. For this reason, the aim of the research is to insert an historical building inside a BIM process, proposing in this way a working method that can build a reality based model and preserve the unicity of the elements. The question is: “What is the more useful mean in term of survey data management, level of detail, information and time savings?” To test the potentialities and the limits of this process we employed the most used software in the international market, taking as example some composed elements, made by regular and complex, but also modular parts. Once a final model is obtained, it is necessary to provide a test phase on the interoperability between the used software modules, in order to give a general picture of the state of art and to contribute to further studies on this subject.