bluuebunny/crossref_metadata_2025 huggingface dataset:
COMPARATIVE STUDY OF AUTOMATIC PLANE FITTING REGISTRATION FOR MLS SPARSE POINT CLOUDS WITH DIFFERENT PLANE SEGMENTATION METHODS
Authors: Long Nguyen H. , Belton D. , Helmholz P.
Published: September 2017

Abstract. The least square plane fitting adjustment method has been widely used for registration of the mobile laser scanning (MLS) point clouds. The inputs for this process are the plane parameters and points of the corresponding planar features. These inputs can be manually and/or automatically extracted from the MLS point clouds. A number of papers have been proposed to automatically extract planar features. They use different criteria to extract planar features and their outputs are slightly different. This will lead to differences in plane parameters values and points of the corresponding features. This research studies and compares the results of the least square plane fitting adjustment process with different inputs obtained by using different segmentation methods (e.g. RANSAC, RDPCA, Cabo, RGPL) and the results from the point to plane approach – an ICP variant. The questions for this research are: (1) which is the more suitable method for registration of MLS sparse point clouds and (2) which is the best segmentation method to obtain the inputs for the plane based MLS point clouds registration? Experiments were conducted with two real MLS point clouds captured by the MDL – Dynascan S250 system. The results show that ICP is less accurate than the least square plane fitting adjustment. It also shows that the accuracy of the plane based registration process is highly correlated with the mean errors of the extracted planar features and the plane parameters. The conclusion is that the RGPL method seems to be the best methods for planar surfaces extraction in MLS sparse point clouds for the registration process.
WATER SURFACE RECONSTRUCTION IN AIRBORNE LASER BATHYMETRY FROM REDUNDANT BED OBSERVATIONS
Authors: Mandlburger G. , Pfeifer N. , Soergel U.
Published: September 2017

Abstract. In airborne laser bathymetry knowledge of exact water level heights is a precondition for applying run-time and refraction correction of the raw laser beam travel path in the medium water. However, due to specular reflection especially at very smooth water surfaces often no echoes from the water surface itself are recorded (drop outs). In this paper, we first discuss the feasibility of reconstructing the water surface from redundant observations of the water bottom in theory. Furthermore, we provide a first practical approach for solving this problem, suitable for static and locally planar water surfaces. It minimizes the bottom surface deviations of point clouds from individual flight strips after refraction correction. Both theoretical estimations and practical results confirm the potential of the presented method to reconstruct water level heights in dm precision. Achieving good results requires enough morphological details in the scene and that the water bottom topography is captured from different directions.
AUTOMATIC BUILDING ABSTRACTION FROM AERIAL PHOTOGRAMMETRY
Authors: Ley A. , Hänsch R. , Hellwich O.
Published: September 2017

Abstract. Multi-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3D city modelling usually requires a different representation of the 3D scene than these point clouds. This paper applies a fully-automatic pipeline to generate a simplified mesh from a given dense point cloud. The mesh provides a certain level of abstraction as it only consists of relatively large planar and textured surfaces. Thus, it is possible to remove noise, outlier, as well as clutter, while maintaining a high level of accuracy.
IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND
DENSE IMAGE MATCHING
Authors: Mandlburger G. , Wenzel K. , Spitzer A. , Haala N. , Glira P. , Pfeifer N.
Published: September 2017

Abstract. Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the RIEGL LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i) systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii) systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii) improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.
PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR
ENVIRONMENTS BASED ON SPARSE OBSERVATIONS
Authors: Dehbi Y. , Loch-Dehbi S. , Plümer L.
Published: September 2017

Abstract. This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
A CONCEPTUAL FRAMEWORK FOR INDOOR MAPPING BY USING GRAMMARS
Authors: Hu X. , Fan H. , Zipf A. , Shang J. , Gu F.
Published: September 2017

Abstract. Maps are the foundation of indoor location-based services. Many automatic indoor mapping approaches have been proposed, but they rely highly on sensor data, such as point clouds and users’ location traces. To address this issue, this paper presents a conceptual framework to represent the layout principle of research buildings by using grammars. This framework can benefit the indoor mapping process by improving the accuracy of generated maps and by dramatically reducing the volume of the sensor data required by traditional reconstruction approaches. In addition, we try to present more details of partial core modules of the framework. An example using the proposed framework is given to show the generation process of a semantic map. This framework is part of an ongoing research for the development of an approach for reconstructing semantic maps.
DETECTION OF SINGLE TREE STEMS IN FORESTED AREAS FROM HIGH DENSITY
ALS POINT CLOUDS USING 3D SHAPE DESCRIPTORS
Authors: Amiri N. , Polewski P. , Yao W. , Krzystek P. , Skidmore A. K.
Published: September 2017

Abstract. Airborne Laser Scanning (ALS) is a widespread method for forest mapping and management purposes. While common ALS techniques provide valuable information about the forest canopy and intermediate layers, the point density near the ground may be poor due to dense overstory conditions. The current study highlights a new method for detecting stems of single trees in 3D point clouds obtained from high density ALS with a density of 300 points/m2. Compared to standard ALS data, due to lower flight height (150–200 m) this elevated point density leads to more laser reflections from tree stems. In this work, we propose a three-tiered method which works on the point, segment and object levels. First, for each point we calculate the likelihood that it belongs to a tree stem, derived from the radiometric and geometric features of its neighboring points. In the next step, we construct short stem segments based on high-probability stem points, and classify the segments by considering the distribution of points around them as well as their spatial orientation, which encodes the prior knowledge that trees are mainly vertically aligned due to gravity. Finally, we apply hierarchical clustering on the positively classified segments to obtain point sets corresponding to single stems, and perform ℓ1-based orthogonal distance regression to robustly fit lines through each stem point set. The ℓ1-based method is less sensitive to outliers compared to the least square approaches. From the fitted lines, the planimetric tree positions can then be derived. Experiments were performed on two plots from the Hochficht forest in Oberösterreich region located in Austria.We marked a total of 196 reference stems in the point clouds of both plots by visual interpretation. The evaluation of the automatically detected stems showed a classification precision of 0.86 and 0.85, respectively for Plot 1 and 2, with recall values of 0.7 and 0.67.
LINE SEGMENTATION OF 2D LASER SCANNER POINT CLOUDS FOR INDOOR SLAM
BASED ON A RANGE OF RESIDUALS
Authors: Peter M. , Jafri S. R. U. N. , Vosselman G.
Published: September 2017

Abstract. Indoor mobile laser scanning (IMLS) based on the Simultaneous Localization and Mapping (SLAM) principle proves to be the preferred method to acquire data of indoor environments at a large scale. In previous work, we proposed a backpack IMLS system containing three 2D laser scanners and an according SLAM approach. The feature-based SLAM approach solves all six degrees of freedom simultaneously and builds on the association of lines to planes. Because of the iterative character of the SLAM process, the quality and reliability of the segmentation of linear segments in the scanlines plays a crucial role in the quality of the derived poses and consequently the point clouds. The orientations of the lines resulting from the segmentation can be influenced negatively by narrow objects which are nearly coplanar with walls (like e.g. doors) which will cause the line to be tilted if those objects are not detected as separate segments. State-of-the-art methods from the robotics domain like Iterative End Point Fit and Line Tracking were found to not handle such situations well. Thus, we describe a novel segmentation method based on the comparison of a range of residuals to a range of thresholds. For the definition of the thresholds we employ the fact that the expected value for the average of residuals of n points with respect to the line is σ / √n. Our method, as shown by the experiments and the comparison to other methods, is able to deliver more accurate results than the two approaches it was tested against.
INDOOR POSITIONING BY VISUAL-INERTIAL ODOMETRY
Authors: Ramezani M. , Acharya D. , Gu F. , Khoshelham K.
Published: September 2017

Abstract. Indoor positioning is a fundamental requirement of many indoor location-based services and applications. In this paper, we explore the potential of low-cost and widely available visual and inertial sensors for indoor positioning. We describe the Visual-Inertial Odometry (VIO) approach and propose a measurement model for omnidirectional visual-inertial odometry (OVIO). The results of experiments in two simulated indoor environments show that the OVIO approach outperforms VIO and achieves a positioning accuracy of 1.1 % of the trajectory length.
BIM-BASED INDOOR PATH PLANNING CONSIDERING OBSTACLES
Authors: Xu M. , Wei S. , Zlatanova S. , Zhang R.
Published: September 2017

Abstract. At present, 87 % of people’s activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people’s daily life are more and more complex, many obstacles influence humans’ moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.
ERROR ESTIMATION AND UNAMBIGUOUS RECONSTRUCTION FOR CHINESE
FIRST DUAL-CHANNEL SPACEBORNE SAR IMAGING
Authors: Jin T. , Qiu X. , Hu D. , Ding C.
Published: September 2017

Abstract. Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.
ESTIMATION OF SHIE GLACIER SURFACE MOVEMENT USING OFFSET TRACKING TECHNIQUE WITH COSMO-SKYMED IMAGES
Authors: Wang Q. , Zhou W. , Fan J. , Yuan W. , Li H. , Sousa J. J. , Guo Z.
Published: September 2017

Abstract. Movement is one of the most important characteristics of glaciers which can cause serious natural disasters. For this reason, monitoring this massive blocks is a crucial task. Synthetic Aperture Radar (SAR) can operate all day in any weather conditions and the images acquired by SAR contain intensity and phase information, which are irreplaceable advantages in monitoring the surface movement of glaciers. Moreover, a variety of techniques like DInSAR and offset tracking, based on the information of SAR images, could be applied to measure the movement. Sangwang lake, a glacial lake in the Himalayas, has great potentially danger of outburst. Shie glacier is situated at the upstream of the Sangwang lake. Hence, it is significant to monitor Shie glacier surface movement to assess the risk of outburst. In this paper, 6 high resolution COSMO-SkyMed images spanning from August to December, 2016 are applied with offset tracking technique to estimate the surface movement of Shie glacier. The maximum velocity of Shie glacier surface movement is 51 cm/d, which was observed at the end of glacier tongue, and the velocity is correlated with the change of elevation. Moreover, the glacier surface movement in summer is faster than in winter and the velocity decreases as the local temperature decreases. Based on the above conclusions, the glacier may break off at the end of tongue in the near future. The movement results extracted in this paper also illustrate the advantages of high resolution SAR images in monitoring the surface movement of small glaciers.
THE ANALYSIS OF OBJECT-BASED CHANGE DETECTION IN MINING AREA:
A CASE STUDY WITH PINGSHUO COAL MINE
Authors: Zhang M. , Zhou W. , Li Y.
Published: September 2017

Abstract. Accurate information on mining land use and land cover change are crucial for monitoring and environmental change studies. In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected to monitor changes combined with object-based classification and change vector analysis method, we also used R in highresolution remote sensing image for mining land classification, and found the feasibility and the flexibility of open source software. The results show that (1) the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of the change region map were 86.67 % and 89.44 %. It’s obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land; (2) the vegetation area changed from 46 % to 40 % accounted for the proportion of the total area from 2012 to 2015, and most of them were transformed into the arable land. The sum of arable land and vegetation area increased from 51 % to 70 %; meanwhile, build-up land has a certain degree of increase, part of the water area was transformed into arable land, but the extent of the two changes is not obvious. The result illustrated the transformation of reclaimed mining area, at the same time, there is still some land convert to mining land, and it shows the mine is still operating, mining land use and land cover are the dynamic procedure.
EXPLORATION OF URBAN SPATIAL PLANNING EVALUATION BASED ON HUMANLAND
HARMONY
Authors: Hu X. S. , Ma Q. R. , Liang W. Q. , Wang C. X. , Xiong X. Q. , Han X. H.
Published: September 2017

Abstract. This study puts forward a new concept, "population urbanization level forecast - driving factor analysis - urban spatial planning analysis" for achieving efficient and intensive development of urbanization considering human-land harmony. We analyzed big data for national economic and social development, studied the development trends of population urbanization and its influencing factors using the grey system model in Chengmai county of Hainan province, China. In turn, we calculated the population of Chengmai coming years based on the forecasting urbanization rate and the corresponding amount of urban construction land, and evaluated the urban spatial planning with GIS spatial analysis method in the study area. The result shows that the proposed concept is feasible for evaluation of urban spatial planning, and is meaningful for guiding the rational distribution of urban space, controlling the scale of development, improving the quality of urbanization and thus promoting highly-efficient and intensive use of limited land resource.
SPATIOTEMPORAL VISUALIZATION OF TSUNAMI WAVES USING KML ON GOOGLE EARTH
Authors: Mohammadi H. , Delavar M. R. , Sharifi M. A. , Pirooz M. D.
Published: September 2017

Abstract. Disaster risk is a function of hazard and vulnerability. Risk is defined as the expected losses, including lives, personal injuries, property damages, and economic disruptions, due to a particular hazard for a given area and time period. Risk assessment is one of the key elements of a natural disaster management strategy as it allows for better disaster mitigation and preparation. It provides input for informed decision making, and increases risk awareness among decision makers and other stakeholders. Virtual globes such as Google Earth can be used as a visualization tool. Proper spatiotemporal graphical representations of the concerned risk significantly reduces the amount of effort to visualize the impact of the risk and improves the efficiency of the decision-making process to mitigate the impact of the risk. The spatiotemporal visualization of tsunami waves for disaster management process is an attractive topic in geosciences to assist investigation of areas at tsunami risk. In this paper, a method for coupling virtual globes with tsunami wave arrival time models is presented. In this process we have shown 2D+Time of tsunami waves for propagation and inundation of tsunami waves, both coastal line deformation, and the flooded areas. In addition, the worst case scenario of tsunami on Chabahar port derived from tsunami modelling is also presented using KML on google earth.
ASSESSMENT OF LIGHT POLLUTION IMPACT ON PROTECTED AREAS IN CHINA
Authors: Jiang W. , He G. , Ni Y.
Published: September 2017

Abstract. The Protected Areas (PAs) with natural, ecological and cultural value play important role in biological processes, biodiversity and ecosystem service. During the past years of rapid urban expansion in China, the spatial range and intensity of light pollution unprecedented increase. Historically, optical remote sensing and field survey data had been used to reveal that human activities impacted on PAs for individual areas and few papers documented the issue of light pollution impact on PAs at national scale. Here, time series night-time light satellite images of Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) were selected to assess the light pollution impacted on PAs in China. The method we proposed can be effectively applied to assess the impact of light pollution on PAs and the percent of dark PAs decreased by 35.38 % from 1992 to 2012 at nationwide. The trend of light pollution of most PAs in stable, however, light pollution of the local area is increase significantly, especially in northern Xinjiang, Gansu, Xizang, Yunnan, Jiangsu and Shandong. Considering the current status of light pollution encroach into PAs, two strategies of appropriate buffer zone and wide measured for light pollution are also recommend.
LABELING RESIDENTIAL COMMUNITY CHARACTERISTICS FROM COLLECTIVE ACTIVITY PATTERNS USING TAXI TRIP DATA
Authors: Zhou Y. , Fang Z.
Published: September 2017

Abstract. There existing a significant social and spatial differentiation in the residential communities in urban city. People live in different places have different socioeconomic background, resulting in various geographically activity patterns. This paper aims to label the characteristics of residential communities in a city using collective activity patterns derived from taxi trip data. Specifically, we first present a method to allocate the O/D (Origin/Destination) points of taxi trips to the land use parcels where the activities taken place in. Then several indices are employed to describe the collective activity patterns, including both activity intensity, travel distance, travel time, and activity space of residents by taking account of the geographical distribution of all O/Ds of the taxi trip related to that residential community. Followed by that, an agglomerative hierarchical clustering algorithm is introduced to cluster the residential communities with similar activity patterns. In the case study of Wuhan, the residential communities are clearly divided into eight clusters, which could be labelled as ordinary communities, privileged communities, old isolated communities, suburban communities, and so on. In this paper, we provide a new perspective to label the land use under same type from people’s mobility patterns with the support of big trajectory data.
SURFACE DEFORMATION MONITORING IN PERMAFROST REGIONS OF TIBETAN PLATEAU BASED ON ALOS PALSAR DATA
Authors: Chen L. M. , Qiao G. , Lu P.
Published: September 2017

Abstract. The permafrost region of Qinghai-Tibet Plateau is widely distributed with the freeze/thaw processes that cause surface structural damage. The differential interferometry synthetic aperture radar (DInSAR) can detect large scale surface deformation with high precision, thus can be used to monitor the freeze/thaw processes of frozen soil area. In this paper, the surface deformation pattern of Qinghai-Tibet railway was analyzed by using the PALSAR 1.0 raw data of the ALOS satellite (L band) and 90m resolution SRTM DEM data, with the help of two-pass DInSAR method in GAMMA software, and the differential interferograms and deformation maps were obtained accordingly. Besides, the influence of temperature, topography and other factors on deformation of frozen soil were also studied. The following conclusions were obtained: there is a negative correlation between deformation and temperature, and there is a delay between the deformation change and that of temperature; deformation and elevation are positively correlated; the permafrost deformation is also affected by solar radiation that could form variable amplitude variation.
WATER LEVEL CHANGES OF NAM-CO LAKE BASED ON SATELLITE ALTIMETRY
DATA SERIES
Authors: Wu Y. J. , Qiao G. , Li H. W.
Published: September 2017

Abstract. Nam-Co Lake is the largest saltwater lake in Tibet and less influenced by human activity. In order to study the change of water level of Nam-Co Lake over the past decades and the impacts of climate change on the region, this paper combined height measurements of ERS-1, ERS-2, ENVISAT, ICESat-2 and CryoSat-2. We found that the water level of Nam Co Lake experienced three periods of change, namely, slightly decreasing period (1992–1993), significantly increasing period (1995–2005), and stable period (2006–2015). The change is consistent with the change of meteorological factors in the Nam-Co Basin. The increase of glacier melt water and precipitation in the basin is considered to be the cause of the overall trend of water level.
ANALYSIS OF WAVEFORM RETRACKING METHODS IN ANTARCTIC ICE
SHEET BASED ON CRYOSAT-2 DATA
Authors: Xiao F. , Li F. , Zhang S. , Hao W. , Yuan L. , Zhu T. , Zhang Y. , Zhu C.
Published: September 2017

Abstract. Satellite altimetry plays an important role in many geoscientific and environmental studies of Antarctic ice sheet. The ranging accuracy is degenerated near coasts or over nonocean surfaces, due to waveform contamination. A postprocess technique, known as waveform retracking, can be used to retrack the corrupt waveform and in turn improve the ranging accuracy. In 2010, the CryoSat-2 satellite was launched with the Synthetic aperture Interferometric Radar ALtimeter (SIRAL) onboard. Satellite altimetry waveform retracking methods are discussed in the paper. Six retracking methods including the OCOG method, the threshold method with 10 %, 25 % and 50 % threshold level, the linear and exponential 5-β parametric methods are used to retrack CryoSat-2 waveform over the transect from Zhongshan Station to Dome A. The results show that the threshold retracker performs best with the consideration of waveform retracking success rate and RMS of retracking distance corrections. The linear 5-β parametric retracker gives best waveform retracking precision, but cannot make full use of the waveform data.
THE PENETRATION EFFECTS ON TANDEM-X ELEVATION USING THE GNSS AND LASER ALTIMETRY MEASUREMENTS IN ANTARCTICA
Authors: Zhao J. , Floricioiu D.
Published: September 2017

Abstract. Synthetic Aperture Radar (SAR) has been widely used in many different fields, such as geoscience, climate monitoring, security-related applications. However, over natural terrain the radar signal has the ability to penetrate the ground surface which can cause the bias in the elevation measurements. The aim of the paper is to assess the SAR signal penetration effect on the TanDEM-X absolute elevation over ice and snow covered areas and it presents the results concerning the X-band SAR signal penetration effect on dry snow areas and blue ice region. Additionally, the relationship between SAR signal penetration depth and backscattering coefficient is exploited and discussed. In this paper, two study sites, Schirmacher area and Recovery Ice Stream are selected and it is found that the general X-band SAR signal penetration depth is around 3–7 meter on dry snow area while no penetration depth is expected on the blue-ice region.
THE TRANSFORM BETWEEN GEOGRAPHIC COORDINATES AND LOCATION CODES OF APERTURE 4 HEXAGONAL GRID SYSTEM
Authors: Wang R. , Ben J. , Li Y. , Du L.
Published: September 2017

Abstract. Discrete global grid system is a new data model which supports the fusion processing of multi-source geospatial data. In discrete global grid systems, all cell operations can be completed by codes theoretically, but most of current spatial data are in the forms of geographic coordinates and projected coordinates. It is necessary to study the transform between geographic coordinates and grid codes, which will support data entering and getting out of the systems. This paper chooses the icosahedral hexagonal discrete global system as a base, and builds the mapping relationships between the sphere and the icosahedron. Then an encoding scheme of planar aperture 4 hexagonal grid system is designed and applied to the icosahedron. Basing on this, a new algorithm of transforms between geographic coordinates and grid codes is designed. Finally, experiments test the accuracy and efficiency of this algorithm. The efficiency of code addition of HLQT is about 5 times the efficiency of code addition of HQBS.
DOCUMENTATION OF HERITAGE STRUCTURES THROUGH GEO-CROWDSOURCING AND WEB-MAPPING
Authors: Dhonju H. K. , Xiao W. , Shakya B. , Mills J. P. , Sarhosis V.
Published: September 2017

Abstract. Heritage documentation has become increasingly urgent due to both natural impacts and human influences. The documentation of countless heritage sites around the globe is a massive project that requires significant amounts of financial and labour resources. With the concepts of volunteered geographic information (VGI) and citizen science, heritage data such as digital photographs can be collected through online crowd participation. Whilst photographs are not strictly geographic data, they can be geo-tagged by the participants. They can also be automatically geo-referenced into a global coordinate system if collected via mobile phones which are now ubiquitous. With the assistance of web-mapping, an online geo-crowdsourcing platform has been developed to collect and display heritage structure photographs. Details of platform development are presented in this paper. The prototype is demonstrated with several heritage examples. Potential applications and advancements are discussed.
DETECTION OF PERSONS IN MLS POINT CLOUDS
Authors: Borgmann B. , Hebel M. , Arens M. , Stilla U.
Published: September 2017

Abstract. In this paper we present an approach for the detection of persons in point clouds gathered by mobile laser scanning (MLS) systems. The approach consists of a preprocessing and the actual detection. The main task of the preprocessing is to reduce the amount of data which has to be processed by the detection. To fulfill this task, the preprocessing consists of ground removal, segmentation and several filters. The detection is based on an implicit shape models (ISM) approach which is an extension to bag-of-words approaches. For this detection method, it is sufficient to work with a small amount of training data. Although in this paper we focus on the detection of persons, our approach is able to detect multiple classes of objects in point clouds. Using a parameterization of the approach which offers a good compromise between detection and runtime performance, we are able to achieve a precision of 0.68 and a recall of 0.76 while having a average runtime of 370 ms per single scan rotation of the rotating head of a typical MLS sensor.
MODELLING MEAN ALBEDO OF INDIVIDUAL ROOFS IN COMPLEX URBAN AREAS
USING SATELLITE IMAGES AND AIRBORNE LASER SCANNING POINT CLOUDS
Authors: Kalantar B. , Mansor S. , Khuzaimah Z. , Ibrahim Sameen M. , Pradhan B.
Published: September 2017

Abstract. Knowledge of surface albedo at individual roof scale is important for mitigating urban heat islands and understanding urban climate change. This study presents a method for quantifying surface albedo of individual roofs in a complex urban area using the integration of Landsat 8 and airborne LiDAR data. First, individual roofs were extracted from airborne LiDAR data and orthophotos using optimized segmentation and supervised object based image analysis (OBIA). Support vector machine (SVM) was used as a classifier in OBIA process for extracting individual roofs. The user-defined parameters required in SVM classifier were selected using v-fold cross validation method. After that, surface albedo was calculated for each individual roof from Landsat images. Finally, thematic maps of mean surface albedo of individual roofs were generated in GIS and the results were discussed. Results showed that the study area is covered by 35% of buildings varying in roofing material types and conditions. The calculated surface albedo of buildings ranged from 0.16 to 0.65 in the study area. More importantly, the results indicated that the types and conditions of roofing materials significantly effect on the mean value of surface albedo. Mean albedo of new concrete, old concrete, new steel, and old steel were found to be equal to 0.38, 0.26, 0.51, and 0.44 respectively. Replacing old roofing materials with new ones should highly prioritized.
AUTOMATIC PARKING OF SELF-DRIVING CAR BASED ON LIDAR
Authors: Lee B. , Wei Y. , Guo I. Y.
Published: September 2017

Abstract. To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on the basis of the vehicle’s dynamics and collision constraints. Besides, we used the fuzzy logic controller to control the brake and accelerator in order to realize the stably of speed. At last the experiments were conducted in an autonomous car, and the results show that the proposed automatic parking system is feasible and effective.
CLASSIFICATION OF MOBILE LASER SCANNING POINT CLOUDS FROM HEIGHT FEATURES
Authors: Zheng M. , Lemmens M. , van Oosterom P.
Published: September 2017

Abstract. The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (MLS) systems are often the preferred geo-data acquisition method for capturing such scenes. Because MLS systems are mounted on cars or vans they can acquire billions of points of road scenes within a few hours of survey. Manual processing of point clouds is labour intensive and thus time consuming and expensive. Hence, the need for rapid and automated methods for 3D mapping of dense point clouds is growing exponentially. The last five years the research on automated 3D mapping of MLS data has tremendously intensified. In this paper, we present our work on automated classification of MLS point clouds. In the present stage of the research we exploited three features – two height components and one reflectance value, and achieved an overall accuracy of 73 %, which is really encouraging for further refining our approach.
AUTOMATIC RECOGNITION OF INDOOR NAVIGATION ELEMENTS FROM KINECT POINT CLOUDS
Authors: Zeng L. , Kang Z.
Published: September 2017

Abstract. This paper realizes automatically the navigating elements defined by indoorGML data standard – door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor – histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor – in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.
ASSESSING THE AGREEMENT BETWEEN EO-BASED SEMI-AUTOMATED LANDSLIDE MAPS WITH FUZZY MANUAL LANDSLIDE DELINEATION
Authors: Albrecht F. , Hölbling D. , Friedl B.
Published: September 2017

Abstract. Landslide mapping benefits from the ever increasing availability of Earth Observation (EO) data resulting from programmes like the Copernicus Sentinel missions and improved infrastructure for data access. However, there arises the need for improved automated landslide information extraction processes from EO data while the dominant method is still manual delineation. Object-based image analysis (OBIA) provides the means for the fast and efficient extraction of landslide information. To prove its quality, automated results are often compared to manually delineated landslide maps. Although there is awareness of the uncertainties inherent in manual delineations, there is a lack of understanding how they affect the levels of agreement in a direct comparison of OBIA-derived landslide maps and manually derived landslide maps. In order to provide an improved reference, we present a fuzzy approach for the manual delineation of landslides on optical satellite images, thereby making the inherent uncertainties of the delineation explicit. The fuzzy manual delineation and the OBIA classification are compared by accuracy metrics accepted in the remote sensing community. We have tested this approach for high resolution (HR) satellite images of three large landslides in Austria and Italy. We were able to show that the deviation of the OBIA result from the manual delineation can mainly be attributed to the uncertainty inherent in the manual delineation process, a relevant issue for the design of validation processes for OBIA-derived landslide maps.
ERROR SOURCES IN PROCCESSING LIDAR BASED BRIDGE INSPECTION
Authors: Bian H. , Chen S. E. , Liu W.
Published: September 2017

Abstract. Bridge inspection is a critical task in infrastructure management and is facing unprecedented challenges after a series of bridge failures. The prevailing visual inspection was insufficient in providing reliable and quantitative bridge information although a systematic quality management framework was built to ensure visual bridge inspection data quality to minimize errors during the inspection process. The LiDAR based remote sensing is recommended as an effective tool in overcoming some of the disadvantages of visual inspection. In order to evaluate the potential of applying this technology in bridge inspection, some of the error sources in LiDAR based bridge inspection are analysed. The scanning angle variance in field data collection and the different algorithm design in scanning data processing are the found factors that will introduce errors into inspection results. Besides studying the errors sources, advanced considerations should be placed on improving the inspection data quality, and statistical analysis might be employed to evaluate inspection operation process that contains a series of uncertain factors in the future. Overall, the development of a reliable bridge inspection system requires not only the improvement of data processing algorithms, but also systematic considerations to mitigate possible errors in the entire inspection workflow. If LiDAR or some other technology can be accepted as a supplement for visual inspection, the current quality management framework will be modified or redesigned, and this would be as urgent as the refine of inspection techniques.
TSUNAMI RISK ASSESSMENT MODELLING IN CHABAHAR PORT, IRAN
Authors: Delavar M. R. , Mohammadi H. , Sharifi M. A. , Pirooz M. D.
Published: September 2017

Abstract. The well-known historical tsunami in the Makran Subduction Zone (MSZ) region was generated by the earthquake of November 28, 1945 in Makran Coast in the North of Oman Sea. This destructive tsunami killed over 4,000 people in Southern Pakistan and India, caused great loss of life and devastation along the coasts of Western India, Iran and Oman. According to the report of "Remembering the 1945 Makran Tsunami", compiled by the Intergovernmental Oceanographic Commission (UNESCO/IOC), the maximum inundation of Chabahar port was 367 m toward the dry land, which had a height of 3.6 meters from the sea level. In addition, the maximum amount of inundation at Pasni (Pakistan) reached to 3 km from the coastline. For the two beaches of Gujarat (India) and Oman the maximum run-up height was 3 m from the sea level. In this paper, we first use Makran 1945 seismic parameters to simulate the tsunami in generation, propagation and inundation phases. The effect of tsunami on Chabahar port is simulated using the ComMIT model which is based on the Method of Splitting Tsunami (MOST). In this process the results are compared with the documented eyewitnesses and some reports from researchers for calibration and validation of the result. Next we have used the model to perform risk assessment for Chabahar port in the south of Iran with the worst case scenario of the tsunami. The simulated results showed that the tsunami waves will reach Chabahar coastline 11 minutes after generation and 9 minutes later, over 9.4 Km2 of the dry land will be flooded with maximum wave amplitude reaching up to 30 meters.
BDS/GPS INTEGRATED POSITIONING METHOD RESEARCH BASED ON NONLINEAR KALMAN FILTERING
Authors: Ma Y. , Yuan W. , Sun H.
Published: September 2017

Abstract. In order to realize fast and accurate BDS/GPS integrated positioning, it is necessary to overcome the adverse effects of signal attenuation, multipath effect and echo interference to ensure the result of continuous and accurate navigation and positioning. In this paper, pseudo-range positioning is used as the mathematical model. In the stage of data preprocessing, using precise and smooth carrier phase measurement value to promote the rough pseudo-range measurement value without ambiguity. At last, the Extended Kalman Filter(EKF), the Unscented Kalman Filter(UKF) and the Particle Filter(PF) algorithm are applied in the integrated positioning method for higher positioning accuracy. The experimental results show that the positioning accuracy of PF is the highest, and UKF is better than EKF.
ELEVATION-BASED SEA-LEVEL RISE VULNERABILITY ASSESSMENT OF MINDANAO, PHILIPPINES: ARE FREELY-AVAILABLE 30-M DEMS GOOD ENOUGH?
Authors: Santillan J. R. , Makinano-Santillan M.
Published: September 2017

Abstract. We assessed the vertical accuracies and uncertainties of three freely-available global DEMs as inputs to elevation-based sea-level rise vulnerability assessment of Mindanao, Philippines – an area where above average SLR of 14.7 mm/year was recently found. These DEMs are the Shuttle Radar Topography Mission (SRTM) DEM, ASTER Global DEM (GDEM Version 2), and ALOS World 3D-30 (AW3D30). Using 2,076 ground control points, we computed each DEM’s vertical accuracies and uncertainties, and from these we determined the smallest increment of sea-level rise (SLRImin) that should be considered when using the DEMs for SLR impact assessment, as well as the Minimum Planning Timeline (TLmin) for an elevation-based SLR assessment. Results of vertical accuracy assessment revealed Root Mean Square Errors of 9.80 m for ASTER GDEM V2, 5.16 m for SRTM DEM, and 4.32 m for AW3D30. Vertical uncertainties in terms of the Linear Error at 95 % Confidence (LE95) were found to be as follows: 19.21 m for ASTER GDEM V2, 10.12 m for SRTM DEM, and 8.47 m for AW3D30. From these, we found that ASTER GDEM2 is suitable to model SLR increments of at least 38.41 m and it will take 2,613 years for the cumulative water level increase of 14.7 mm/year to reach the minimum SLR increment afforded by this DEM. For the SRTM DEM, SLRImin and TLmin were computed as 20.24 m and 1,377 years, respectively. For the AW3D30, SLRImin and TLmin were computed as 16.92 m and 1,151 years, respectively. These results suggest that the readily available global DEMs' suitability for mapping coastal inundations due to SLR in our study area is limited by their low vertical accuracies and high uncertainties. All the three DEMs do not have the necessary accuracy and minimum uncertainties that will make them suitable for mapping inundations of Mindanao at smaller increments of SLR (e.g., SLR ≤ 5 m). Hence, users who apply any of these DEMs for SLR impact assessment at SLRIs lower than the DEM’s SLRImin must be cautious in reporting the areas of SLR vulnerable zones. Reporting the inundated areas as a range instead of a singular value for a given SLR scenario can highlight the inherent accuracy and uncertainty of the DEM used in the assessment.
ROI-ORIENTATED SENSOR CORRECTION BASED ON VIRTUAL STEADY REIMAGING MODEL FOR WIDE SWATH HIGH RESOLUTION OPTICAL SATELLITE IMAGERY
Authors: Zhu Y. , Jin S. , Tian Y. , Wang M.
Published: September 2017

Abstract. To meet the requirement of high accuracy and high speed processing for wide swath high resolution optical satellite imagery under emergency situation in both ground processing system and on-board processing system. This paper proposed a ROI-orientated sensor correction algorithm based on virtual steady reimaging model for wide swath high resolution optical satellite imagery. Firstly, the imaging time and spatial window of the ROI is determined by a dynamic search method. Then, the dynamic ROI sensor correction model based on virtual steady reimaging model is constructed. Finally, the corrected image corresponding to the ROI is generated based on the coordinates mapping relationship which is established by the dynamic sensor correction model for corrected image and rigours imaging model for original image. Two experimental results show that the image registration between panchromatic and multispectral images can be well achieved and the image distortion caused by satellite jitter can be also corrected efficiently.