bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-term observations of black carbon mass concentrations at Fukue Island,
western Japan, during 2009–2015: constraining wet removal rates and
emission strengths from East Asia
Authors: Kanaya Yugo , Pan Xiaole , Miyakawa Takuma , Komazaki Yuichi , Taketani Fumikazu , Uno Itsushi , Kondo Yutaka
Published: August 2016

Abstract. Long-term (2009–2015) observations of atmospheric black carbon (BC) mass concentrations were performed using a continuous soot-monitoring system (COSMOS) at Fukue Island, western Japan, to provide information on wet removal rate constraints and the emission strengths of important source regions in East Asia (China and others). The annual average mass concentration was 0.36 µg m−3, with distinct seasonality; high concentrations were recorded during autumn, winter, and spring and were caused by Asian continental outflows, which reached Fukue Island in 6–46 h. The observed data were categorized into two classes, i.e., with and without a wet removal effect, using the accumulated precipitation along a backward trajectory (APT) for the last 3 days as an index. Statistical analysis of the observed ΔBC ∕ ΔCO ratios was performed to obtain information on the emission ratios (from data with zero APT only) and wet removal rates (including data with nonzero APTs). The estimated emission ratios (5.2–6.9 ng m−3 ppb−1) varied over the six air mass origin areas; the higher ratios for south-central East China (30–35° N) than for north-central East China (35–40° N) indicated the relative importance of domestic emissions and/or biomass burning sectors. The significantly higher BC ∕ CO emission ratios adopted in the bottom-up Regional Emission inventory in Asia (REAS) version 2 (8.3–23 ng m−3 ppb−1) over central East China and Korea needed to be reduced at least by factors of 1.3 and 2.8 for central East China and Korea, respectively, but the ratio for Japan was reasonable. The wintertime enhancement of the BC emission from China, predicted by REAS2, was verified for air masses from south-central East China but not for those from north-central East China. Wet removal of BC was clearly identified as a decrease in the ΔBC ∕ ΔCO ratio against APT. The transport efficiency (TE), defined as the ratio of the ΔBC ∕ ΔCO ratio with precipitation to that without precipitation, was fitted reasonably well by a stretched exponential decay curve against APT; a single set of fitting parameters was sufficient to represent the results for air masses originating from different areas. An accumulated precipitation of 25.5 ± 6.1 mm reduced the TE to 1∕e. BC-containing particles traveling to Fukue must have already been converted from hydrophobic to hydrophilic particles, because the behavior of TE against APT was similar to that of PM2.5, the major components of which are hydrophilic. Wet loss of BC greatly influenced interannual variations in the ΔBC ∕ ΔCO ratios and BC mass concentrations. This long-term data set will provide a benchmark for testing chemical transport/climate model simulations covering East Asia.
The constraint of CO2 measurements made onboard passenger aircraft on surface-atmosphere fluxes: the impact of transport model errors in vertical mixing
Authors: Verma Shreeya , Marshall Julia , Gerbig Christoph , Roedenbeck Christian , Totsche Kai Uwe
Published: August 2016

Abstract. Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network with those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height as compared to the ground- based network. This highlights the benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-Service Aircraft for a Global Observing System) project in future, in constraining the regional carbon budget. Our results show that the regions tropical Africa and temperate Eurasia, that are under constrained by the existing surface based network, will benefit the most from these measurements, the reduction of posterior flux uncertainty being about 7 to 10 %.
Coherence among the Northern Hemisphere land, cryosphere, and ocean
responses to natural variability and anthropogenic forcing during the
satellite era
Authors: Gonsamo Alemu , Chen Jing M. , Shindell Drew T. , Asner Gregory P.
Published: August 2016

Abstract. A lack of long-term measurements across Earth's biological and physical systems has made observation-based detection and attribution of climate change impacts to anthropogenic forcing and natural variability difficult. Here we explore coherence among land, cryosphere and ocean responses to recent climate change using 3 decades (1980–2012) of observational satellite and field data throughout the Northern Hemisphere. Our results show coherent interannual variability among snow cover, spring phenology, solar radiation, Scandinavian Pattern, and North Atlantic Oscillation. The interannual variability of the atmospheric peak-to-trough CO2 amplitude is mostly impacted by temperature-mediated effects of El Niño/Southern Oscillation (ENSO) and Pacific/North American Pattern (PNA), whereas CO2 concentration is affected by Polar Pattern control on sea ice extent dynamics. This is assuming the trend in anthropogenic CO2 emission remains constant, or the interannual changes in the trends are negligible. Our analysis suggests that sea ice decline-related CO2 release may outweigh increased CO2 uptake through longer growing seasons and higher temperatures. The direct effects of variation in solar radiation and leading teleconnections, at least in part via their impacts on temperature, dominate the interannual variability of land, cryosphere and ocean indicators. Our results reveal a coherent long-term changes in multiple physical and biological systems that are consistent with anthropogenic forcing of Earth's climate and inconsistent with natural drivers.
DOM quality in a peatland and forest headwater stream: seasonal
and event characteristics
Authors: Broder Tanja , Knorr Klaus-Holger , Biester Harald
Published: August 2016

Abstract. Peatlands and peaty riparian zones are major sources of DOM, but are poorly understood in terms of export dynamics and controls thereof. The quality of DOM affects function and behavior of DOM in aquatic ecosystems, but DOM quality can also help to track DOM sources and their export dynamics under specific hydrologic preconditions. The objective of this study was to elucidate controls on temporal variability in DOM concentration and quality in discharge from a bog and a forested peaty riparian zone, particularly considering drought and storm flow events. DOM quality was monitored using spectrofluorometric indices for aromaticity (SUVA254), apparent molecular size (SR) and precursor organic material (FI), as well as PARAFAC modeling of excitation emission matrices (EEMs). Indices for DOM quality exhibited major changes due to different hydrologic conditions, but patterns were also dependent on season. The forested site with mineral, peaty soils generally exhibited higher variability in concentrations and quality compared to the outflow of an ombrotrophic bog. During snowmelt and spring events surface-near protein-like DOM pools were exported. During drought a microbial DOM fraction originating from groundwater and deep peat layers was exported, characterized by high FI, high SR and increasing humic-like fluorophores C1% or C4%. During discharge events this deep sourced DOM pool was diluted by humic-rich surface-near DOM pools, which were more aromatic, also of microbial origin with high FI and SR, and an increase in humic-like fluorophores C2% and C3% at the forested site. The FI suggested export of DOM of strong microbial alteration particularly under discharge events with dry preconditions. This might be due to accelerated microbial activity in the peaty riparian zone of the forested site. Our study demonstrated that DOM export dynamics are not only a passive mixing of different hydrological sources, but assessing DOM quality can greatly improve our understanding of DOM sources and their response under different hydrological preconditions.
MODELLING STEEP SURFACES BY VARIOUS CONFIGURATIONS OF NADIR AND OBLIQUE PHOTOGRAMMETRY
Authors: Casella V. , Franzini M.
Published: August 2016

Among the parts of the territory requiring periodical and careful monitoring, many have steep surfaces: quarries, river basins, land-slides, dangerous mountainsides. Aerial photogrammetry based on lightweight unmanned aircraft systems (UAS) is rapidly becoming the tool of election to survey limited areas of land with a high level of detail. Aerial photogrammetry is traditionally based on vertical images and only recently the use of significantly inclined imagery has been considered. Oblique photogrammetry presents peculiar aspects and offers improved capabilities for steep surface reconstruction. Full comprehension of oblique photogrammetry still requires research efforts and the evaluation of diverse case studies. In the present paper, the focus is on the photogrammetric UAS-based survey of a part of a large sandpit. Various flight configurations are considered: ordinary linear strips, radial strips (as the scarp considered has a semi-circular shape) and curved ones; moreover, nadir looking and oblique image blocks were acquired. Around 300 control points were measured with a topographic total station. The various datasets considered are evaluated in terms of density of the extracted point cloud and in terms of the distance between the reconstructed surface and a number of check points.
UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR
Authors: Jozkow G. , Toth C. , Grejner-Brzezinska D.
Published: August 2016

Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various hardware and software solutions are investigated to increase the quality of UAS LiDAR point clouds. This work analyses several aspects of the UAS LiDAR point cloud generation performance based on UAS flights conducted with the Velodyne laser scanner and cameras. The attention was primarily paid to the trajectory reconstruction performance that is essential for accurate point cloud georeferencing. Since the navigation sensors, especially Inertial Measurement Units (IMUs), may not be of sufficient performance, the estimated camera poses could allow to increase the robustness of the estimated trajectory, and subsequently, the accuracy of the point cloud. The accuracy of the final UAS LiDAR point cloud was evaluated on the basis of the generated DSM, including comparison with point clouds obtained from dense image matching. The results showed the need for more investigation on MEMS IMU sensors used for UAS trajectory reconstruction. The accuracy of the UAS LiDAR point cloud, though lower than for point cloud obtained from images, may be still sufficient for certain mapping applications where the optical imagery is not useful.
KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION
Authors: Bai Yang , Tang Ping , Hu Changmiao
Published: August 2016

The multivariate alteration detection (MAD) algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA) which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA). The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1) data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.
RPC STEREO PROCESSOR (RSP) – A SOFTWARE PACKAGE FOR DIGITAL SURFACE MODEL AND ORTHOPHOTO GENERATION FROM SATELLITE STEREO IMAGERY
Authors: Qin R.
Published: August 2016

Large-scale Digital Surface Models (DSM) are very useful for many geoscience and urban applications. Recently developed dense image matching methods have popularized the use of image-based very high resolution DSM. Many commercial/public tools that implement matching methods are available for perspective images, but there are rare handy tools for satellite stereo images. In this paper, a software package, RPC (rational polynomial coefficient) stereo processor (RSP), is introduced for this purpose. RSP implements a full pipeline of DSM and orthophoto generation based on RPC modelled satellite imagery (level 1+), including level 2 rectification, geo-referencing, point cloud generation, pan-sharpen, DSM resampling and ortho-rectification. A modified hierarchical semi-global matching method is used as the current matching strategy. Due to its high memory efficiency and optimized implementation, RSP can be used in normal PC to produce large format DSM and orthophotos. This tool was developed for internal use, and may be acquired by researchers for academic and non-commercial purpose to promote the 3D remote sensing applications.
A NEW CONTROL POINTS BASED GEOMETRIC CORRECTION ALGORITHM FOR AIRBORNE PUSH BROOM SCANNER IMAGES WITHOUT ON-BOARD DATA
Authors: Strakhov P. , Badasen E. , Shurygin B. , Kondranin T.
Published: August 2016

Push broom scanners, such as video spectrometers (also called hyperspectral sensors), are widely used in the present. Usage of scanned images requires accurate geometric correction, which becomes complicated when imaging platform is airborne. This work contains detailed description of a new algorithm developed for processing of such images. The algorithm requires only user provided control points and is able to correct distortions caused by yaw, flight speed and height changes. It was tested on two series of airborne images and yielded RMS error values on the order of 7 meters (3-6 source image pixels) as compared to 13 meters for polynomial-based correction.
GAZE AND FEET AS ADDITIONAL INPUT MODALITIES FOR INTERACTING WITH GEOSPATIAL INTERFACES
Authors: Çöltekin A. , Hempel J. , Brychtova A. , Giannopoulos I. , Stellmach S. , Dachselt R.
Published: August 2016

Geographic Information Systems (GIS) are complex software environments and we often work with multiple tasks and multiple displays when we work with GIS. However, user input is still limited to mouse and keyboard in most workplace settings. In this project, we demonstrate how the use of gaze and feet as additional input modalities can overcome time-consuming and annoying mode switches between frequently performed tasks. In an iterative design process, we developed gaze- and foot-based methods for zooming and panning of map visualizations. We first collected appropriate gestures in a preliminary user study with a small group of experts, and designed two interaction concepts based on their input. After the implementation, we evaluated the two concepts comparatively in another user study to identify strengths and shortcomings in both. We found that continuous foot input combined with implicit gaze input is promising for supportive tasks.
TOWARDS THE DEVELOPMENT OF A TAXONOMY FOR VISUALISATION OF STREAMED GEOSPATIAL DATA
Authors: Sibolla B. H. , Van Zyl T. , Coetzee S.
Published: August 2016

Geospatial data has very specific characteristics that need to be carefully captured in its visualisation, in order for the user and the viewer to gain knowledge from it. The science of visualisation has gained much traction over the last decade as a response to various visualisation challenges. During the development of an open source based, dynamic two-dimensional visualisation library, that caters for geospatial streaming data, it was found necessary to conduct a review of existing geospatial visualisation taxonomies. The review was done in order to inform the design phase of the library development, such that either an existing taxonomy can be adopted or extended to fit the needs at hand. The major challenge in this case is to develop dynamic two dimensional visualisations that enable human interaction in order to assist the user to understand the data streams that are continuously being updated. This paper reviews the existing geospatial data visualisation taxonomies that have been developed over the years. Based on the review, an adopted taxonomy for visualisation of geospatial streaming data is presented. Example applications of this taxonomy are also provided. The adopted taxonomy will then be used to develop the information model for the visualisation library in a further study.
GEOGRAPHIC DATA AS PERSONAL DATA IN FOUR EU MEMBER STATES
Authors: de Jong A. J. , van Loenen B. , Zevenbergen J. A.
Published: August 2016

The EU Directive 95/46/EC on the protection of individuals with regard to the processing of personal data and on the free movement of such data aims at harmonising data protection legislation in the European Union. This should promote the free flow of products and services within the EU. This research found a wide variety of interpretations of the application of data protection legislation to geographic data. The variety was found among the different EU Member States, the different stakeholders and the different types of geographic data. In the Netherlands, the Data Protection Authority (DPA) states that panoramic images of streets are considered personal data. While Dutch case law judges that the data protection legislation does not apply if certain features are blurred and no link to an address is provided. The topographic datasets studied in the case studies do not contain personal data, according to the Dutch DPA, while the German DPA and the Belgian DPA judge that topographic maps of a large scale can contain personal data, and impose conditions on the processing of topographic maps. The UK DPA does consider this data outside of the scope of legal definition of personal data. The patchwork of differences in data protection legislation can be harmonised by using a traffic light model. This model focuses on the context in which the processing of the data takes place and has four categories of data: (1) sensitive personal data, (2) personal data, (3), data that can possibly lead to identification, and (4) non-personal data. For some geographic data, for example factual data that does not reveal sensitive information about a person, can be categorised in the third category giving room to opening up data under the INSPIRE Directive.
VOLUMINATOR 2.0 – SPEEDING UP THE APPROXIMATION OF THE VOLUME OF DEFECTIVE 3D BUILDING MODELS
Authors: Sindram M. , Machl T. , Steuer H. , Pültz M. , Kolbe T. H.
Published: August 2016

Semantic 3D city models are increasingly used as a data source in planning and analyzing processes of cities. They represent a virtual copy of the reality and are a common information base and source of information for examining urban questions. A significant advantage of virtual city models is that important indicators such as the volume of buildings, topological relationships between objects and other geometric as well as thematic information can be derived. Knowledge about the exact building volume is an essential base for estimating the building energy demand. In order to determine the volume of buildings with conventional algorithms and tools, the buildings may not contain any topological and geometrical errors. The reality, however, shows that city models very often contain errors such as missing surfaces, duplicated faces and misclosures. To overcome these errors (Steuer et al., 2015) have presented a robust method for approximating the volume of building models. For this purpose, a bounding box of the building is divided into a regular grid of voxels and it is determined which voxels are inside the building. The regular arrangement of the voxels leads to a high number of topological tests and prevents the application of this method using very high resolutions. In this paper we present an extension of the algorithm using an octree approach limiting the subdivision of space to regions around surfaces of the building models and to regions where, in the case of defective models, the topological tests are inconclusive. We show that the computation time can be significantly reduced, while preserving the robustness against geometrical and topological errors.
AUTOMATIC CONSTRUCTION OF HIERARCHICAL ROAD NETWORKS
Authors: Yang Weiping
Published: August 2016

This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.
IDENTIFYING THE LOCAL SURFACE URBAN HEAT ISLAND THROUGH THE MORPHOLOGY OF THE LAND SURFACE TEMPERATURE
Authors: Wang Jiong , Zhan Qingming , Xiao Yinghui
Published: August 2016

Current characterization of the Land Surface Temperature (LST) at city scale insufficiently supports efficient mitigations and adaptations of the Surface Urban Heat Island (SUHI) at local scale. This research intends to delineate the LST variation at local scale where mitigations and adaptations are more feasible. At the local scale, the research helps to identify the local SUHI (LSUHI) at different levels. The concept complies with the planning and design conventions that urban problems are treated with respect to hierarchies or priorities. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. The continuous and smooth latent LST is first recovered from the raw images. The Multi-Scale Shape Index (MSSI) is then applied to the latent LST to extract morphological indicators. The local scale variation of the LST is quantified by the indicators such that the LSUHI can be identified morphologically. The results are promising. It can potentially be extended to investigate the temporal dynamics of the LST and LSUHI. This research serves to the application of remote sensing, pattern analysis, urban microclimate study, and urban planning at least at 2 levels: (1) it extends the understanding of the SUHI to the local scale, and (2) the characterization at local scale facilitates problem identification and support mitigations and adaptations more efficiently.
EVENT DETECTION USING MOBILE PHONE MASS GPS DATA AND THEIR RELIAVILITY VERIFICATION BY DMSP/OLS NIGHT LIGHT IMAGE
Authors: Yuki Akiyama , Satoshi Ueyama , Ryosuke Shibasaki , Adachi Ryuichiro
Published: August 2016

In this study, we developed a method to detect sudden population concentration on a certain day and area, that is, an “Event,” all over Japan in 2012 using mass GPS data provided from mobile phone users. First, stay locations of all phone users were detected using existing methods. Second, areas and days where Events occurred were detected by aggregation of mass stay locations into 1-km-square grid polygons. Finally, the proposed method could detect Events with an especially large number of visitors in the year by removing the influences of Events that occurred continuously throughout the year. In addition, we demonstrated reasonable reliability of the proposed Event detection method by comparing the results of Event detection with light intensities obtained from the night light images from the DMSP/OLS night light images. Our method can detect not only positive events such as festivals but also negative events such as natural disasters and road accidents. These results are expected to support policy development of urban planning, disaster prevention, and transportation management.
TWO-GRAPH BUILDING INTERIOR REPRESENTATION FOR EMERGENCY RESPONSE APPLICATIONS
Authors: Boguslawski P. , Mahdjoubi L. , Zverovich V. , Fadli F.
Published: August 2016

Nowadays, in a rapidly developing urban environment with bigger and higher public buildings, disasters causing emergency situations and casualties are unavoidable. Preparedness and quick response are crucial issues saving human lives. Available information about an emergency scene, such as a building structure, helps for decision making and organizing rescue operations. Models supporting decision-making should be available in real, or near-real, time. Thus, good quality models that allow implementation of automated methods are highly desirable. This paper presents details of the recently developed method for automated generation of variable density navigable networks in a 3D indoor environment, including a full 3D topological model, which may be used not only for standard navigation but also for finding safe routes and simulating hazard and phenomena associated with disasters such as fire spread and heat transfer.
EVALUATING THE EFFECTS OF REDUCTIONS IN LiDAR DATA ON THE VISUAL AND STATISTICAL CHARACTERISTICS OF THE CREATED DIGITAL ELEVATION MODELS
Authors: Asal F. F.
Published: August 2016

With continuous developments in LiDAR technologies high point cloud densities have been attainable but accompanied by challenges for processing big volumes of data. Reductions in high point cloud densities are expected to lower data acquisition and data processing costs; however this could affect the characteristics of the generated Digital Elevation Models (DEMs). This research aimed to evaluate the effects of reductions in airborne LiDAR point cloud data densities on the visual and statistical characteristics of the generated DEMs. DEMs have been created from a dataset which constitutes last returns of raw LiDAR data that was acquired at bare lands for Gilmer County, USA between March and April 2004, where qualitative and quantitative testing analyses have been performed. Visual analysis has shown that the DEM can withstand a considerable degree of quality with reduced densities down to 0.128 pts/m2 (47 % of the data remaining), however degradations in the DEM visual characteristics appeared in coarser tones and rougher textures have occurred with more reductions. Additionally, the statistical analysis has indicated that the standard deviations of the DEM elevations have decreased by only 22 % of the total decrease with data density reductions down to 0.101 pts/m2 (37 % of the data remaining) while greater rate of decreasing in the standard deviations has occurred with more reductions referring to greater rate of surface smoothing and elevation approximating. Furthermore, the accuracy analysis testing has given that the DEM accuracy has degraded by only 4.83 % of the total degradations with data density reductions down to 0.128 pts/m2, however great deteriorations in the DEM accuracy have occurred with more data reductions. Finally, it is recommended that LiDAR data can withstand point density reductions down to 0.128 pts/m2 (about 50 % of the data) without big deteriorations in the visual and statistical characteristics of the generated DEMs.
PHOTOGRAMMETRIC ACCURACY AND MODELING OF ROLLING SHUTTER CAMERAS
Authors: Vautherin Jonas , Rutishauser Simon , Schneider-Zapp Klaus , Choi Hon Fai , Chovancova Venera , Glass Alexis , Strecha Christoph
Published: August 2016

Unmanned aerial vehicles (UAVs) are becoming increasingly popular in professional mapping for stockpile analysis, construction site monitoring, and many other applications. Due to their robustness and competitive pricing, consumer UAVs are used more and more for these applications, but they are usually equipped with rolling shutter cameras. This is a significant obstacle when it comes to extracting high accuracy measurements using available photogrammetry software packages. In this paper, we evaluate the impact of the rolling shutter cameras of typical consumer UAVs on the accuracy of a 3D reconstruction. Hereto, we use a beta-version of the Pix4Dmapper 2.1 software to compare traditional (non rolling shutter) camera models against a newly implemented rolling shutter model with respect to both the accuracy of geo-referenced validation points and to the quality of the motion estimation. Multiple datasets have been acquired using popular quadrocopters (DJI Phantom 2 Vision+, DJI Inspire 1 and 3DR Solo) following a grid flight plan. For comparison, we acquired a dataset using a professional mapping drone (senseFly eBee) equipped with a global shutter camera. The bundle block adjustment of each dataset shows a significant accuracy improvement on validation ground control points when applying the new rolling shutter camera model for flights at higher speed (8m=s). Competitive accuracies can be obtained by using the rolling shutter model, although global shutter cameras are still superior. Furthermore, we are able to show that the speed of the drone (and its direction) can be solely estimated from the rolling shutter effect of the camera.
CLASSIFICATION OF AIRBORNE LASER SCANNING DATA USING GEOMETRIC MULTI-SCALE FEATURES AND DIFFERENT NEIGHBOURHOOD TYPES
Authors: Blomley R. , Jutzi B. , Weinmann M.
Published: August 2016

In this paper, we address the classification of airborne laser scanning data. We present a novel methodology relying on the use of complementary types of geometric features extracted from multiple local neighbourhoods of different scale and type. To demonstrate the performance of our methodology, we present results of a detailed evaluation on a standard benchmark dataset and we show that the consideration of multi-scale, multi-type neighbourhoods as the basis for feature extraction leads to improved classification results in comparison to single-scale neighbourhoods as well as in comparison to multi-scale neighbourhoods of the same type.
AUTOMATIC EXTRACTION OF BUILDING ROOF PLANES FROM AIRBORNE LIDAR DATA APPLYING AN EXTENDED 3D RANDOMIZED HOUGH TRANSFORM
Authors: Maltezos Evangelos , Ioannidis Charalabos
Published: August 2016

This study aims to extract automatically building roof planes from airborne LIDAR data applying an extended 3D Randomized Hough Transform (RHT). The proposed methodology consists of three main steps, namely detection of building points, plane detection and refinement. For the detection of the building points, the vegetative areas are first segmented from the scene content and the bare earth is extracted afterwards. The automatic plane detection of each building is performed applying extensions of the RHT associated with additional constraint criteria during the random selection of the 3 points aiming at the optimum adaptation to the building rooftops as well as using a simple design of the accumulator that efficiently detects the prominent planes. The refinement of the plane detection is conducted based on the relationship between neighbouring planes, the locality of the point and the use of additional information. An indicative experimental comparison to verify the advantages of the extended RHT compared to the 3D Standard Hough Transform (SHT) is implemented as well as the sensitivity of the proposed extensions and accumulator design is examined in the view of quality and computational time compared to the default RHT. Further, a comparison between the extended RHT and the RANSAC is carried out. The plane detection results illustrate the potential of the proposed extended RHT in terms of robustness and efficiency for several applications.
FOOTPRINT MAP PARTITIONING USING AIRBORNE LASER SCANNING DATA
Authors: Xiong B. , Oude Elberink S. , Vosselman G.
Published: August 2016

Nowadays many cities and countries are creating their 3D building models for a better daily management and smarter decision making. The newly created 3D models are required to be consistent with existing 2D footprint maps. Thereby the 2D maps are usually combined with height data for the task of 3D reconstruction. Many buildings are often composed by parts that are discontinuous over height. Building parts can be reconstructed independently and combined into a complete building. Therefore, most of the state-of-the-art work on 3D building reconstruction first decomposes a footprint map into parts. However, those works usually change the footprint maps for easier partitioning and cannot detect building parts that are fully inside the footprint polygon. In order to solve those problems, we introduce two methodologies, one more dependent on height data, and the other one more dependent on footprints. We also experimentally evaluate the two methodologies and compare their advantages and disadvantages. The experiments use Airborne Laser Scanning (ALS) data and two vector maps, one with 1:10,000 scale and another one with 1:500 scale.
GPS-DENIED GEO-LOCALISATION USING VISUAL ODOMETRY
Authors: Gupta Ashish , Chang Huan , Yilmaz Alper
Published: August 2016

The primary method for geo-localization is based on GPS which has issues of localization accuracy, power consumption, and unavailability. This paper proposes a novel approach to geo-localization in a GPS-denied environment for a mobile platform. Our approach has two principal components: public domain transport network data available in GIS databases or OpenStreetMap; and a trajectory of a mobile platform. This trajectory is estimated using visual odometry and 3D view geometry. The transport map information is abstracted as a graph data structure, where various types of roads are modelled as graph edges and typically intersections are modelled as graph nodes. A search for the trajectory in real time in the graph yields the geo-location of the mobile platform. Our approach uses a simple visual sensor and it has a low memory and computational footprint. In this paper, we demonstrate our method for trajectory estimation and provide examples of geolocalization using public-domain map data. With the rapid proliferation of visual sensors as part of automated driving technology and continuous growth in public domain map data, our approach has the potential to completely augment, or even supplant, GPS based navigation since it functions in all environments.
CHANGE DETECTION VIA MORPHOLOGICAL COMPARATIVE FILTERS
Authors: Vizilter Y. V. , Rubis A. Y. , Zheltov S. Y. , Vygolov O. V.
Published: August 2016

In this paper we propose the new change detection technique based on morphological comparative filtering. This technique generalizes the morphological image analysis scheme proposed by Pytiev. A new class of comparative filters based on guided contrasting is developed. Comparative filtering based on diffusion morphology is implemented too. The change detection pipeline contains: comparative filtering on image pyramid, calculation of morphological difference map, binarization, extraction of change proposals and testing change proposals using local morphological correlation coefficient. Experimental results demonstrate the applicability of proposed approach.
SIMULTANEOUS DETECTION AND TRACKING OF PEDESTRIAN FROM PANORAMIC LASER SCANNING DATA
Authors: Xiao Wen , Vallet Bruno , Schindler Konrad , Paparoditis Nicolas
Published: August 2016

Pedestrian traffic flow estimation is essential for public place design and construction planning. Traditional data collection by human investigation is tedious, inefficient and expensive. Panoramic laser scanners, e.g. Velodyne HDL-64E, which scan surroundings repetitively at a high frequency, have been increasingly used for 3D object tracking. In this paper, a simultaneous detection and tracking (SDAT) method is proposed for precise and automatic pedestrian trajectory recovery. First, the dynamic environment is detected using two different methods, Nearest-point and Max-distance. Then, all the points on moving objects are transferred into a space-time (x, y, t) coordinate system. The pedestrian detection and tracking amounts to assign the points belonging to pedestrians into continuous trajectories in space-time. We formulate the point assignment task as an energy function which incorporates the point evidence, trajectory number, pedestrian shape and motion. A low energy trajectory will well explain the point observations, and have plausible trajectory trend and length. The method inherently filters out points from other moving objects and false detections. The energy function is solved by a two-step optimization process: tracklet detection in a short temporal window; and global tracklet association through the whole time span. Results demonstrate that the proposed method can automatically recover the pedestrians trajectories with accurate positions and low false detections and mismatches.
FACADE INTERPRETATION USING A MARKED POINT PROCESS
Authors: Wenzel Susanne , Förstner Wolfgang
Published: August 2016

Our objective is the interpretation of facade images in a top-down manner, using a Markov marked point process formulated as a Gibbs process. Given single rectified facade images, we aim at the accurate detection of relevant facade objects as windows and entrances, using prior knowledge about their possible configurations within facade images. We represent facade objects by a simplified rectangular object model and present an energy model, which evaluates the agreement of a proposed configuration with the given image and the statistics about typical configurations, which we learned from training data. We show promising results on different datasets and provide a qualitative evaluation, which demonstrates the capability of complete and accurate detection of facade objects.
JOINT SIMULTANEOUS RECONSTRUCTION OF REGULARIZED BUILDING SUPERSTRUCTURES FROM LOW-DENSITY LIDAR DATA USING ICP
Authors: Wichmann Andreas , Kada Martin
Published: August 2016

There are many applications for 3D city models, e.g., in visualizations, analysis, and simulations; each one requiring a certain level of detail to be effective. The overall trend goes towards including various kinds of anthropogenic and natural objects therein with ever increasing geometric and semantic details. A few years back, the featured 3D building models had only coarse roof geometry. But nowadays, they are expected to include detailed roof superstructures like dormers and chimneys. Several methods have been proposed for the automatic reconstruction of 3D building models from airborne based point clouds. However, they are usually unable to reliably recognize and reconstruct small roof superstructures as these objects are often represented by only few point measurements, especially in low-density point clouds. In this paper, we propose a recognition and reconstruction approach that overcomes this problem by identifying and simultaneously reconstructing regularized superstructures of similar shape. For this purpose, candidate areas for superstructures are detected by taking into account virtual sub-surface points that are assumed to lie on the main roof faces below the measured points. The areas with similar superstructures are detected, extracted, grouped together, and registered to one another with the Iterative Closest Point (ICP) algorithm. As an outcome, the joint point density of each detected group is increased, which helps to recognize the shape of the superstructure more reliably and in more detail. Finally, all instances of each group of superstructures are modeled at once and transformed back to their original position. Because superstructures are reconstructed in groups, symmetries, alignments, and regularities can be enforced in a straight-forward way. The validity of the approach is presented on a number of example buildings from the Vaihingen test data set.
ROOF RECONSTRUCTION FROM AIRBORNE LASER SCANNING DATA BASED ON IMAGE PROCESSING METHODS
Authors: Goebbels S. , Pohle-Fröhlich R.
Published: August 2016

The paper presents a new data-driven approach to generate CityGML building models from airborne laser scanning data. The approach is based on image processing methods applied to an interpolated height map and avoids shortcomings of established methods for plane detection like Hough transform or RANSAC algorithms on point clouds. The improvement originates in an interpolation algorithm that generates a height map from sparse point cloud data by preserving ridge lines and step edges of roofs. Roof planes then are detected by clustering the height map’s gradient angles, parameterizations of planes are estimated and used to filter out noise around ridge lines. On that basis, a raster representation of roof facets is generated. Then roof polygons are determined from region outlines, connected to a roof boundary graph, and simplified. Whereas the method is not limited to churches, the method’s performance is primarily tested for church roofs of the German city of Krefeld because of their complexity. To eliminate inaccuracies of spires, contours of towers are detected additionally, and spires are rendered as solids of revolution. In our experiments, the new data-driven method lead to significantly better building models than the previously applied model-driven approach.
MODERN METHODS OF BUNDLE ADJUSTMENT ON THE GPU
Authors: Hänsch R. , Drude I. , Hellwich O.
Published: August 2016

The task to compute 3D reconstructions from large amounts of data has become an active field of research within the last years. Based on an initial estimate provided by structure from motion, bundle adjustment seeks to find a solution that is optimal for all cameras and 3D points. The corresponding nonlinear optimization problem is usually solved by the Levenberg-Marquardt algorithm combined with conjugate gradient descent. While many adaptations and extensions to the classical bundle adjustment approach have been proposed, only few works consider the acceleration potentials of GPU systems. This paper elaborates the possibilities of time and space savings when fitting the implementation strategy to the terms and requirements of realizing a bundler on heterogeneous CPUGPU systems. Instead of focusing on the standard approach of Levenberg-Marquardt optimization alone, nonlinear conjugate gradient descent and alternating resection-intersection are studied as two alternatives. The experiments show that in particular alternating resection-intersection reaches low error rates very fast, but converges to larger error rates than Levenberg-Marquardt. PBA, as one of the current state-of-the-art bundlers, converges slower in 50 % of the test cases and needs 1.5-2 times more memory than the Levenberg- Marquardt implementation.
APPLICABILITY OF NEW APPROACHES OF SENSOR ORIENTATION TO MICRO AERIAL VEHICLES
Authors: Rehak M. , Skaloud J.
Published: August 2016

This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. There, accurate aerial control plays a major role in successful terrain reconstruction and artifact-free ortophoto generation. The presented experiments focus on new approaches of aerial control. We confirm practically that the relative aerial position and attitude control can improve accuracy in difficult mapping scenarios. Indeed, the relative orientation method represents an attractive alternative in the context of MAVs for two reasons. First, the procedure is somewhat simplified, e.g. the angular misalignment, so called boresight, between the camera and the inertial measurement unit (IMU) does not have to be determined and, second, the effect of possible systematic errors in satellite positioning (e.g. due to multipath and/or incorrect recovery of differential carrier-phase ambiguities) is mitigated. First, we present a typical mapping project over an agricultural field and second, we perform a corridor road mapping. We evaluate the proposed methods in scenarios with and without automated image observations. We investigate a recently proposed concept where adjustment is performed using image observations limited to ground control and check points, so called fast aerial triangulation (Fast AT). In this context we show that accurate aerial control (absolute or relative) together with a few image observations can deliver accurate results comparable to classical aerial triangulation with thousands of image measurements. This procedure in turns reduces the demands on processing time and the requirements on the existence of surface texture. Finally, we compare the above mentioned procedures with direct sensor orientation (DiSO) to show its potential for rapid mapping.
A NEW PARADIGM FOR MATCHING UAV- AND AERIAL IMAGES
Authors: Koch T. , Zhuo X. , Reinartz P. , Fraundorfer F.
Published: August 2016

This paper investigates the performance of SIFT-based image matching regarding large differences in image scaling and rotation, as this is usually the case when trying to match images captured from UAVs and airplanes. This task represents an essential step for image registration and 3d-reconstruction applications. Various real world examples presented in this paper show that SIFT, as well as A-SIFT perform poorly or even fail in this matching scenario. Even if the scale difference in the images is known and eliminated beforehand, the matching performance suffers from too few feature point detections, ambiguous feature point orientations and rejection of many correct matches when applying the ratio-test afterwards. Therefore, a new feature matching method is provided that overcomes these problems and offers thousands of matches by a novel feature point detection strategy, applying a one-to-many matching scheme and substitute the ratio-test by adding geometric constraints to achieve geometric correct matches at repetitive image regions. This method is designed for matching almost nadir-directed images with low scene depth, as this is typical in UAV and aerial image matching scenarios. We tested the proposed method on different real world image pairs. While standard SIFT failed for most of the datasets, plenty of geometrical correct matches could be found using our approach. Comparing the estimated fundamental matrices and homographies with ground-truth solutions, mean errors of few pixels can be achieved.