bluuebunny/crossref_metadata_2025 huggingface dataset:
A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods
Authors: Tien Bui Dieu , Hoang Nhat-Duc
Published: September 2017

Abstract. In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.
SEGMENTATION OF ENVIRONMENTAL TIME LAPSE IMAGE SEQUENCES FOR THE DETERMINATION OF SHORE LINES CAPTURED BY HAND-HELD SMARTPHONE CAMERAS
Authors: Kröhnert M. , Meichsner R.
Published: September 2017

Abstract. The relevance of globally environmental issues gains importance since the last years with still rising trends. Especially disastrous floods may cause in serious damage within very short times. Although conventional gauging stations provide reliable information about prevailing water levels, they are highly cost-intensive and thus just sparsely installed. Smartphones with inbuilt cameras, powerful processing units and low-cost positioning systems seem to be very suitable wide-spread measurement devices that could be used for geo-crowdsourcing purposes. Thus, we aim for the development of a versatile mobile water level measurement system to establish a densified hydrological network of water levels with high spatial and temporal resolution. This paper addresses a key issue of the entire system: the detection of running water shore lines in smartphone images. Flowing water never appears equally in close-range images even if the extrinsics remain unchanged. Its non-rigid behavior impedes the use of good practices for image segmentation as a prerequisite for water line detection. Consequently, we use a hand-held time lapse image sequence instead of a single image that provides the time component to determine a spatio-temporal texture image. Using a region growing concept, the texture is analyzed for immutable shore and dynamic water areas. Finally, the prevalent shore line is examined by the resultant shapes. For method validation, various study areas are observed from several distances covering urban and rural flowing waters with different characteristics. Future work provides a transformation of the water line into object space by image-to-geometry intersection.
FEASIBILITY OF MACHINE LEARNING METHODS FOR SEPARATING WOOD AND
LEAF POINTS FROM TERRESTRIAL LASER SCANNING DATA
Authors: Wang D. , Hollaus M. , Pfeifer N.
Published: September 2017

Abstract. Classification of wood and leaf components of trees is an essential prerequisite for deriving vital tree attributes, such as wood mass, leaf area index (LAI) and woody-to-total area. Laser scanning emerges to be a promising solution for such a request. Intensity based approaches are widely proposed, as different components of a tree can feature discriminatory optical properties at the operating wavelengths of a sensor system. For geometry based methods, machine learning algorithms are often used to separate wood and leaf points, by providing proper training samples. However, it remains unclear how the chosen machine learning classifier and features used would influence classification results. To this purpose, we compare four popular machine learning classifiers, namely Support Vector Machine (SVM), Na¨ıve Bayes (NB), Random Forest (RF), and Gaussian Mixture Model (GMM), for separating wood and leaf points from terrestrial laser scanning (TLS) data. Two trees, an Erytrophleum fordii and a Betula pendula (silver birch) are used to test the impacts from classifier, feature set, and training samples. Our results showed that RF is the best model in terms of accuracy, and local density related features are important. Experimental results confirmed the feasibility of machine learning algorithms for the reliable classification of wood and leaf points. It is also noted that our studies are based on isolated trees. Further tests should be performed on more tree species and data from more complex environments.
AUTOMATED COARSE REGISTRATION OF POINT CLOUDS IN 3D URBAN SCENES
USING VOXEL BASED PLANE CONSTRAINT
Authors: Xu Y. , Boerner R. , Yao W. , Hoegner L. , Stilla U.
Published: September 2017

Abstract. For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.
VEHICLE RECOGNITION IN AERIAL LIDAR POINT CLOUD BASED ON DYNAMIC TIME WARPING
Authors: Zhang T. , Vosselman G. , Oude Elberink S. J.
Published: September 2017

Abstract. A two-step vehicle recognition method from an aerial Lidar point cloud is proposed in this paper. First, the Lidar point cloud is segmented using the region-growing algorithm with vehicle size limitation. Then the vehicle is recognized according to the profile shape based on dynamic time warping. The proposed method can detect vehicles parking under trees in an urban scene, and classifies the vehicles into different classes. The vehicle location, orientation, parking direction and size can also be determined. The experimental result based on a real urban Lidar point cloud shows that the proposed method can correctly recognize 95.1 % of vehicles.
WEB MAPPING ARCHITECTURES BASED ON OPEN SPECIFICATIONS AND FREE AND OPEN SOURCE SOFTWARE IN THE WATER DOMAIN
Authors: Arias Muñoz C. , Brovelli M. A. , Kilsedar C. E. , Moreno-Sanchez R. , Oxoli D.
Published: September 2017

Abstract. The availability of water-related data and information across different geographical and jurisdictional scales is of critical importance for the conservation and management of water resources in the 21st century. Today information assets are often found fragmented across multiple agencies that use incompatible data formats and procedures for data collection, storage, maintenance, analysis, and distribution. The growing adoption of Web mapping systems in the water domain is reducing the gap between data availability and its practical use and accessibility. Nevertheless, more attention must be given to the design and development of these systems to achieve high levels of interoperability and usability while fulfilling different end user informational needs. This paper first presents a brief overview of technologies used in the water domain, and then presents three examples of Web mapping architectures based on free and open source software (FOSS) and the use of open specifications (OS) that address different users’ needs for data sharing, visualization, manipulation, scenario simulations, and map production. The purpose of the paper is to illustrate how the latest developments in OS for geospatial and water-related data collection, storage, and sharing, combined with the use of mature FOSS projects facilitate the creation of sophisticated interoperable Web-based information systems in the water domain.
IMAGING GEOMETRY AND POSITIONING ACCURACY OF DUAL SATELLITE STEREO IMAGES: A REVIEW
Authors: Jeong J.
Published: September 2017

Abstract. Many previous studies have demonstrated the potential applications of stereo pairs obtained from high-resolution satellites for accurate geo-positioning, but it should be noted that they are based on the conventional use of single-satellite stereo images produced by integrating two images taken by the same satellite. Considering the emergence of various types of satellite data and the requirements to combine these data, it is important to investigate dual-satellite stereo images that integrate two images taken by different satellites. This study reviews the image geometry and positioning accuracy of dual-satellite stereo images based on several important studies, including comparisons with conventional single-satellite stereo images. In particular, the geometric limitation of dual-satellite stereo images often leads to very weak geometry, which degrades the positioning accuracy according to theoretical and experimental studies. Optimal ray intersection can improve the positioning accuracy using dual-satellite stereo images. This review improves our understanding of satellite stereo geometry and the handling of the dual-satellite stereo images, which are expected to become more common in real mapping applications.
POINT CLOUDS TO INDOOR/OUTDOOR ACCESSIBILITY DIAGNOSIS
Authors: Balado J. , Díaz-Vilariño L. , Arias P. , Garrido I.
Published: September 2017

Abstract. This work presents an approach to automatically detect structural floor elements such as steps or ramps in the immediate environment of buildings, elements that may affect the accessibility to buildings. The methodology is based on Mobile Laser Scanner (MLS) point cloud and trajectory information. First, the street is segmented in stretches along the trajectory of the MLS to work in regular spaces. Next, the lower region of each stretch (the ground zone) is selected as the ROI and normal, curvature and tilt are calculated for each point. With this information, points in the ROI are classified in horizontal, inclined or vertical. Points are refined and grouped in structural elements using raster process and connected components in different phases for each type of previously classified points. At last, the trajectory data is used to distinguish between road and sidewalks. Adjacency information is used to classify structural elements in steps, ramps, curbs and curb-ramps. The methodology is tested in a real case study, consisting of 100 m of an urban street. Ground elements are correctly classified in an acceptable computation time. Steps and ramps also are exported to GIS software to enrich building models from Open Street Map with information about accessible/inaccessible entrances and their locations.
TOWARDS THE INTEGRATION OF INDOORGML AND INDOORLOCATIONGML FOR INDOOR APPLICATIONS
Authors: Liu L. , Zlatanova S. , Zhu Q. , Li K.
Published: September 2017

Abstract. This paper introduces and compares two types of GML-based data standards for indoor location-based services, i.e., IndoorGML and IndoorLocationGML. By elaborating the advantages of the both standards and their data models, we conclude that the two data standards are complementary to each other. A jointed data model is presented to show the integration of the two standards. IndoorGML can supply subdivision of building for data of IndoorLocationGML, and the semantics of locations defined in IndoorLocationGML can be added to IndoorGML. By proposing two use cases, we take the initiative in attempting to combine the use of the two standards. The first case is to collect details from files of the two standards for an indoor path; the second one is to generate verbal directions for indoor guidance from files of the two standards. Some future work is given for further development, such as automatic integration of separate data from both standards.
RELATIVE PANORAMIC CAMERA POSITION ESTIMATION
FOR IMAGE-BASED VIRTUAL REALITY NETWORKS IN INDOOR ENVIRONMENTS
Authors: Nakagawa M. , Akano K. , Kobayashi T. , Sekiguchi Y.
Published: September 2017

Abstract. Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
FUSION OF LOCATION FINGERPRINTING AND TRILATERATION BASED ON THE
EXAMPLE OF DIFFERENTIAL WI-FI POSITIONING
Authors: Retscher G.
Published: September 2017

Abstract. Positioning of mobile users in indoor environments with Wireless Fidelity (Wi-Fi) has become very popular whereby location fingerprinting and trilateration are the most commonly employed methods. In both the received signal strength (RSS) of the surrounding access points (APs) are scanned and used to estimate the user’s position. Within the scope of this study the advantageous qualities of both methods are identified and selected to benefit their combination. By a fusion of these technologies a higher performance for Wi-Fi positioning is achievable. For that purpose, a novel approach based on the well-known Differential GPS (DGPS) principle of operation is developed and applied. This approach for user localization and tracking is termed Differential Wi-Fi (DWi-Fi) by analogy with DGPS. From reference stations deployed in the area of interest differential measurement corrections are derived and applied at the mobile user side. Hence, range or coordinate corrections can be estimated from a network of reference station observations as it is done in common CORS GNSS networks. A low-cost realization with Raspberry Pi units is employed for these reference stations. These units serve at the same time as APs broadcasting Wi-Fi signals as well as reference stations scanning the receivable Wi-Fi signals of the surrounding APs. As the RSS measurements are carried out continuously at the reference stations dynamically changing maps of RSS distributions, so-called radio maps, are derived. Similar as in location fingerprinting this radio maps represent the RSS fingerprints at certain locations. From the areal modelling of the correction parameters in combination with the dynamically updated radio maps the location of the user can be estimated in real-time. The novel approach is presented and its performance demonstrated in this paper.
EXTRACTING TOPOLOGICAL RELATIONS BETWEEN INDOOR SPACES FROM POINT CLOUDS
Authors: Tran H. , Khoshelham K. , Kealy A. , Díaz-Vilariño L.
Published: September 2017

Abstract. 3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.
USING OPENSTREETMAP DATA TO GENERATE BUILDING MODELS WITH THEIR INNER STRUCTURES FOR 3D MAPS
Authors: Wang Z. , Zipf A.
Published: September 2017

Abstract. With the development of Web 2.0, more and more data related to indoor environments has been collected within the volunteered geographic information (VGI) framework, which creates a need for construction of indoor environments from VGI. In this study, we focus on generating 3D building models from OpenStreetMap (OSM) data, and provide an approach to support construction and visualization of indoor environments on 3D maps. In this paper, we present an algorithm which can extract building information from OSM data, and can construct building structures as well as inner building components (e.g., doors, rooms, and windows). A web application is built to support the processing and visualization of the building models on a 3D map. We test our approach with an indoor dataset collected from the field. The results show the feasibility of our approach and its potentials to provide support for a wide range of applications, such as indoor and outdoor navigation, urban planning, and incident management.
LOCATION DISTRIBUTION OPTIMIZATION OF PHOTOGRAPHING SITES FOR INDOOR PANORAMA MODELING
Authors: Zhang S. , Wu J. , Zhang Y. , Zhang X. , Xin Z. , Liu J.
Published: September 2017

Abstract. Generally, panoramas image modeling is costly and time-consuming because of photographing continuously to capture enough photos along the routes, especially in complicated indoor environment. Thus, difficulty follows for a wider applications of panoramic image modeling for business. It is indispensable to make a feasible arrangement of panorama sites locations because the locations influence the clarity, coverage and the amount of panoramic images under the condition of certain device. This paper is aim to propose a standard procedure to generate the specific location and total amount of panorama sites in indoor panoramas modeling. Firstly, establish the functional relationship between one panorama site and its objectives. Then, apply the relationship to panorama sites network. We propose the Distance Clarity function (FC and Fe) manifesting the mathematical relationship between panoramas and objectives distance or obstacle distance. The Distance Buffer function (FB) is modified from traditional buffer method to generate the coverage of panorama site. Secondly, transverse every point in possible area to locate possible panorama site, calculate the clarity and coverage synthetically. Finally select as little points as possible to satiate clarity requirement preferentially and then the coverage requirement. In the experiments, detailed parameters of camera lens are given. Still, more experiments parameters need trying out given that relationship between clarity and distance is device dependent. In short, through the function FC, Fe and FB, locations of panorama sites can be generated automatically and accurately.
A SAR INTENSITY IMAGES CHANGE DETECTION METHOD BASED ON FUSION DIFFERENCE DETECTOR AND STATISTICAL PROPERTIES
Authors: Cui B. , Zhang Y. , Yan L. , Cai X.
Published: September 2017

Abstract. Detecting the land cover changes is an important application of multi-temporal synthetic aperture radar (SAR) images. This study puts forward a novel SAR change detection method which has two-steps: change detector construction and change threshold selection. For change detector construction, considering the SAR intensity images follow the gamma distribution, the conditional probabilities of the binary hypothesis test are provided, then the log likelihood ratio (LLR) combined with the log ratio (LR) to construct a detector which can enhance the degree of change to calculate the diversity degree convenient between the two images; for change threshold selection, owing to the characteristic that the curve about the ratio value of adjacent grey-level (GL) values in normalized difference map, the normalized difference map can be segmented in three parts by two thresholds selected which correspond to the regions of unchanged, backscatter enhanced and weakened separately. And as this, the change areas can be also determined simultaneously. The experimental results on different areas and sensors indicate that the proposed algorithm is effective and feasible.
A COMPARISON OF SIMULATED ANNEALING, GENETIC ALGORITHM AND PARTICLE SWARM OPTIMIZATION IN OPTIMAL FIRST-ORDER DESIGN OF INDOOR TLS NETWORKS
Authors: Jia F. , Lichti D.
Published: September 2017

Abstract. The optimal network design problem has been well addressed in geodesy and photogrammetry but has not received the same attention for terrestrial laser scanner (TLS) networks. The goal of this research is to develop a complete design system that can automatically provide an optimal plan for high-accuracy, large-volume scanning networks. The aim in this paper is to use three heuristic optimization methods, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO), to solve the first-order design (FOD) problem for a small-volume indoor network and make a comparison of their performances. The room is simplified as discretized wall segments and possible viewpoints. Each possible viewpoint is evaluated with a score table representing the wall segments visible from each viewpoint based on scanning geometry constraints. The goal is to find a minimum number of viewpoints that can obtain complete coverage of all wall segments with a minimal sum of incidence angles. The different methods have been implemented and compared in terms of the quality of the solutions, runtime and repeatability. The experiment environment was simulated from a room located on University of Calgary campus where multiple scans are required due to occlusions from interior walls. The results obtained in this research show that PSO and GA provide similar solutions while SA doesn’t guarantee an optimal solution within limited iterations. Overall, GA is considered as the best choice for this problem based on its capability of providing an optimal solution and fewer parameters to tune.
LINE SEGMENTS MATCHING ALGORITHMl C0MBINING MSLD DESCRIPTION AND CORRESPONDING P0INTS CONSTRAINT
Authors: Zhang X. , Zhang J.
Published: September 2017

Abstract. Aiming at stability of line descriptor in the process of line segment matching, MSLD mean-standard deviation descriptor with corresponding points constraint method is proposed.The method is based on close-range images corresponding points matching and line extraction, in the beginning, determined the points which have the closest distance between the both sides of the target lines on the reference images, virtual line is composed by connecting corresponding points on the search image, and the line which intersects virtual line on the search image is defined as the candidate line segment. Then calculating the MSLD description of the straight lines and the candidate lines respectively, the specific construction steps are as followed: (1) gradient direction and normal direction of the straight line should be determined firstly; (2) for each pixel on the straight line, a rectangular area which is defined as Pixel Support Region (PSR) is established along the gradient direction and the normal direction, and the PSR is decomposed into several same size sub-regions in the normal direction; (3) recording each sub-region the gradient vectors of four directions to obtain a four-dimensional feature vector, and the gradient description matrix of straight line L is composed of all sub-regions feature vectors; (4) mean and standard deviation of the description matrix should be calculated by the row vector, then mean and standard deviation vectors should be normalized to obtain the normalized mean-standard deviation description. Finally, the similarity between the target lines and each candidate lines descriptor is calculated based on the Euclidean distance, using the nearest neighbor distance ratio to determine the corresponding line. Typical region image is selected to perform line matching experiment in this paper, results show that the proposed method has great stability and matching accuracy.
FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES
Authors: Zhao J. , Huang G. , Zhang J.
Published: September 2017

Abstract. The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.
EXTRACTION OF ROCKY DESERTIFICATION FROM DISP IMAGERY: A CASE STUDY OF LIUPANSHUI, GUIZHOU, CHINA
Authors: Zhou G. , Wu Z. , Wang W. , Shi Y. , Mao G. , Huang Y. , Jia B. , Gao G. , Chen P.
Published: September 2017

Abstract. Karst rocky desertification is a typical type of land degradation in Guizhou Province, China. It causes great ecological and economical implications to the local people. This paper utilized the declassified intelligence satellite photography (DISP) of 1960s to extract the karst rocky desertification area to analyze the early situation of karst rocky desertification in Liupanshui, Guizhou, China. Due to the lack of ground control points and parameters of the satellite, a polynomial orthographic correction model with considering altitude difference correction is proposed for orthorectification of DISP imagery. With the proposed model, the 96 DISP images from four missions are orthorectified. The images are assembled into a seamless image map of the karst area of Guizhou, China. The assembled image map is produced to thematic map of karst rocky desertification by visual interpretation in Liupanshui city. With the assembled image map, extraction of rocky desertification is conducted.
ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE
Authors: Zou Z. , Zhan W. , Jiang L.
Published: September 2017

Abstract. Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST) data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC) model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs) of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.
INVESTIGATION OF ROADWAY GEOMETRIC AND TRAFFIC FLOW FACTORS FOR
VEHICLE CRASHES USING SPATIOTEMPORAL INTERACTION
Authors: Gill G. , Sakrani T. , Cheng W. , Zhou J.
Published: September 2017

Abstract. Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.
POPULATION ESTIMATION IN SINGAPORE BASED ON REMOTE SENSING AND OPEN DATA
Authors: Guo H. , Cao K. , Wang P.
Published: September 2017

Abstract. Population estimation statistics are widely used in government, commercial and educational sectors for a variety of purposes. With growing emphases on real-time and detailed population information, data users nowadays have switched from traditional census data to more technology-based data source such as LiDAR point cloud and High-Resolution Satellite Imagery. Nevertheless, such data are costly and periodically unavailable. In this paper, the authors use West Coast District, Singapore as a case study to investigate the applicability and effectiveness of using satellite image from Google Earth for extraction of building footprint and population estimation. At the same time, volunteered geographic information (VGI) is also utilized as ancillary data for building footprint extraction. Open data such as Open Street Map（OSM）could be employed to enhance the extraction process. In view of challenges in building shadow extraction, this paper discusses several methods including buffer, mask and shape index to improve accuracy. It also illustrates population estimation methods based on building height and number of floor estimates. The results show that the accuracy level of housing unit method on population estimation can reach 92.5 %, which is remarkably accurate. This paper thus provides insights into techniques for building extraction and fine-scale population estimation, which will benefit users such as urban planners in terms of policymaking and urban planning of Singapore.
AN ENCODING METHOD FOR COMPRESSING GEOGRAPHICAL COORDINATES IN 3D SPACE
Authors: Qian C. , Jiang R. , Li M.
Published: September 2017

Abstract. This paper proposed an encoding method for compressing geographical coordinates in 3D space. By the way of reducing the length of geographical coordinates, it helps to lessen the storage size of geometry information. In addition, the encoding algorithm subdivides the whole space according to octree rules, which enables progressive transmission and loading. Three main steps are included in this method: (1) subdividing the whole 3D geographic space based on octree structure, (2) resampling all the vertices in 3D models, (3) encoding the coordinates of vertices with a combination of Cube Index Code (CIC) and Geometry Code. A series of geographical 3D models were applied to evaluate the encoding method. The results showed that this method reduced the storage size of most test data by 90 % or even more under the condition of a speed of encoding and decoding. In conclusion, this method achieved a remarkable compression rate in vertex bit size with a steerable precision loss. It shall be of positive meaning to the web 3d map storing and transmission.
ANALYZING IMPACT FACTORS OF AIRPORT TAXIING DELAY BASED ON ADS-B DATA
Authors: Li J. , Wang X. , Xu Y. , Li Q. , He C. , Li Y.
Published: September 2017

Abstract. Identifying the factors that cause taxiing delay on airports is a prerequisite for optimizing aircraft taxiing schemes, and helps improve the efficiency of taxiing system. Few of current studies had quantified the potential influencing factors and further investigated their intrinsic relationship. In view of these problems, this paper uses ADS-B data to calculate taxiing delay time by restoring taxiing route and identifying key status points, and further analyzes the impact factors of airport taxiing delay by investigating the relationship between delay time and environmental data such as weather, wind, visibility etc. The case study in Guangzhou Baiyun Airport validates the effectiveness of the proposed method.
HOTSPOTS DETECTION FROM TRAJECTORY DATA BASED ON SPATIOTEMPORAL DATA FIELD CLUSTERING
Authors: Qin K. , Zhou Q. , Wu T. , Xu Y. Q.
Published: September 2017

Abstract. City hotspots refer to the areas where residents visit frequently, and large traffic flow exist, which reflect the people travel patterns and distribution of urban function area. Taxi trajectory data contain abundant information about urban functions and citizen activities, and extracting interesting city hotspots from them can be of importance in urban planning, traffic command, public travel services etc. To detect city hotspots and discover a variety of changing patterns among them, we introduce a data field-based cluster analysis technique to the pick-up and drop-off points of taxi trajectory data and improve the method by introducing the time weight, which has been normalized to estimate the potential value in data field. Thus, in the light of the new potential function in data field, short distance and short time difference play a powerful role. So the region full of trajectory points, which is regarded as hotspots area, has a higher potential value, while the region with thin trajectory points has a lower potential value. The taxi trajectory data of Wuhan city in China on May 1, 6 and 9, 2015, are taken as the experimental data. From the result, we find the sustaining hotspots area and inconstant hotspots area in Wuhan city based on the spatiotemporal data field method. Further study will focus on optimizing parameter and the interaction among hotspots area.
SPATIOTEMPORAL PATTERNS AND ITS INSTABILITY OF LAND USE CHANGE IN FIVE CHINESE NODE CITIES OF THE BELT AND ROAD
Authors: Quan B. , Guo T. , Liu P. L. , Ren H. G.
Published: September 2017

Abstract. It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.
ARTISTIC VISUALIZATION OF TRAJECTORY DATA USING CLOUD MODEL
Authors: Wu T. , Zhou Y. , Zhang L.
Published: September 2017

Abstract. Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. In this paper, we explore a cloud model-based method for the generation of stylized renderings of trajectory data. The artistic visualizations of the proposed method do not have the goal to allow for data mining tasks or others but instead show the aesthetic effect of the traces of moving objects in a distorted manner. The techniques used to create the images of traces of moving objects include the uncertain line using extended cloud model, stroke-based rendering of geolocation in varying styles, and stylistic shading with aesthetic effects for print or electronic displays, as well as various parameters to be further personalized. The influence of different parameters on the aesthetic qualities of various painted images is investigated, including step size, types of strokes, colour modes, and quantitative comparisons using four aesthetic measures are also involved into the experiment. The experimental results suggest that the proposed method is with advantages of uncertainty, simplicity and effectiveness, and it would inspire professional graphic designers and amateur users who may be interested in playful and creative exploration of artistic visualization of trajectory data.
SPATIOTEMPORAL ANALYSIS OF THE EBOLA HEMORRHAGIC FEVER IN WEST AFRICA IN 2014
Authors: Xu M. , Cao C. X. , Guo H. F.
Published: September 2017

Abstract. Ebola hemorrhagic fever (EHF) is an acute hemorrhagic diseases caused by the Ebola virus, which is highly contagious. This paper aimed to explore the possible gathering area of EHF cases in West Africa in 2014, and identify endemic areas and their tendency by means of time-space analysis. We mapped distribution of EHF incidences and explored statistically significant space, time and space-time disease clusters. We utilized hotspot analysis to find the spatial clustering pattern on the basis of the actual outbreak cases. spatial-temporal cluster analysis is used to analyze the spatial or temporal distribution of agglomeration disease, examine whether its distribution is statistically significant. Local clusters were investigated using Kulldorff’s scan statistic approach. The result reveals that the epidemic mainly gathered in the western part of Africa near north Atlantic with obvious regional distribution. For the current epidemic, we have found areas in high incidence of EVD by means of spatial cluster analysis.
ECOSYSTEM HEALTH ASSESSMENT OF MINING CITIES BASED ON
LANDSCAPE PATTERN
Authors: Yu W. , Liu Y. , Lin M. , Fang F. , Xiao R.
Published: September 2017

Abstract. Ecosystem health assessment (EHA) is one of the most important aspects in ecosystem management. Nowadays, ecological environment of mining cities is facing various problems. In this study, through ecosystem health theory and remote sensing images in 2005, 2009 and 2013, landscape pattern analysis and Vigor-Organization-Resilience (VOR) model were applied to set up an evaluation index system of ecosystem health of mining city to assess the healthy level of ecosystem in Panji District Huainan city. Results showed a temporal stable but high spatial heterogeneity landscape pattern during 2005–2013. According to the regional ecosystem health index, it experienced a rapid decline after a slight increase, and finally it maintained at an ordinary level. Among these areas, a significant distinction was presented in different towns. It indicates that the ecosystem health of Tianjijiedao town, the regional administrative centre, descended rapidly during the study period, and turned into the worst level in the study area. While the Hetuan Town, located in the northwestern suburb area of Panji District, stayed on a relatively better level than other towns. The impacts of coal mining collapse area, land reclamation on the landscape pattern and ecosystem health status of mining cities were also discussed. As a result of underground coal mining, land subsidence has become an inevitable problem in the study area. In addition, the coal mining subsidence area has brought about the destruction of the farmland, construction land and water bodies, which causing the change of the regional landscape pattern and making the evaluation of ecosystem health in mining area more difficult. Therefore, this study provided an ecosystem health approach for relevant departments to make scientific decisions.
THE YARLUNG ZANGBO RIVER EXTRACTION AND CHANGE DETECTION BASED ON LANDSAT SERIES
Authors: Cao Y. J. , Qiao G.
Published: September 2017

Abstract. Yarlung Zangbo River is one of the most important rivers in the southwest river source area, it is the longest plateau river in China, the cradle of the birth and development of Tibet civilization, and also an international water system. It is of great significance to study its water resources utilization and water environment protection. This paper compared different river extraction methods, including the normalized difference water index, multi-band spectral correlation threshold method, maximum likelihood classification method and object-oriented classification method, based on Landsat images, and combined with remote sensing and GIS technologies. The study area is Yarlung Zangbo River, one of the main rivers in southwest river source region. Meanwhile, river changes have been analysed based on upstream and midstream of Yarlung Zangbo River extracting results of four images in different periods. The result shows that object-oriented classification method has advantage of removing mountain shadow, its accuracy of river extraction is the highest, and Yarlung Zangbo River area shows a decreasing trend from 2000 to 2016, and there are some changes of watercourse in midstream as well.
WHAT ISWEBMAPPING ANYWAY?
Authors: Veenendaal B. , Brovelli M. A. , Li S. , Ivánová I.
Published: September 2017

Abstract. Although maps have been around for a very long time, web maps are yet very young in their origin. Despite their relatively short history, web maps have been developing very rapidly over the past few decades. The use, users and usability of web maps have rapidly expanded along with developments in web technologies and new ways of mapping. In the process of these developments, the terms and terminology surrounding web mapping have also changed and evolved, often relating to the new technologies or new uses. Examples include web mapping, web GIS, cloud mapping, internet mapping, internet GIS, geoweb, map mashup, online mapping etc., not to mention those with prefixes such as “web-based” and “internet-based”. So, how do we keep track of these terms, relate them to each other and have common understandings of their meanings so that references to them are not ambiguous, misunderstood or even different? This paper explores the terms surrounding web mapping and web GIS, and the development of their meaning over time. The paper then suggests the current context in which these terms are used and provides meanings that may assist in better understanding and communicating using these terms in the future.
ANTARCTIC ICE SHEET SLOPE AND ASPECT BASED ON ICESAT’S REPEAT
ORBIT MEASUREMENT
Authors: Yuan L. , Li F. , Zhang S. , Xie S. , Xiao F. , Zhu T. , Zhang Y.
Published: September 2017

Abstract. Accurate information of ice sheet surface slope is essential for estimating elevation change by satellite altimetry measurement. A study is carried out to recover surface slope of Antarctic ice sheet from Ice, Cloud and land Elevation Satellite (ICESat) elevation measurements based on repeat orbits. ICESat provides repeat ground tracks within 200 meters in cross-track direction and 170 meters in along-track direction for most areas of Antarctic ice sheet. Both cross-track and along-track surface slopes could be obtained by adjacent repeat ground tracks. Combining those measurements yields a surface slope model with resolution of approximately 200 meters. An algorithm considering elevation change is developed to estimate the surface slope of Antarctic ice sheet. Three Antarctic Digital Elevation Models (DEMs) were used to calculate surface slopes. The surface slopes from DEMs are compared with estimates by using in situ GPS data in Dome A, the summit of Antarctic ice sheet. Our results reveal an average surface slope difference of 0.02 degree in Dome A. High resolution remote sensing images are also used in comparing the results derived from other DEMs and this paper. The comparison implies that our results have a slightly better coherence with GPS observation than results from DEMs, but our results provide more details and perform higher accuracy in coastal areas because of the higher resolution for ICESat measurements. Ice divides are estimated based on the aspect, and are weakly consistent with ice divides from other method in coastal regions.
AN INFORMATION SERVICE MODEL FOR REMOTE SENSING EMERGENCY SERVICES
Authors: Zhang Z. , Zhao S. , Li X. , Cong D. , Sun D.
Published: September 2017

Abstract. This paper presents a method on the semantic access environment, which can solve the problem about how to identify the correct natural disaster emergency knowledge and return to the demanders. The study data is natural disaster knowledge text set. Firstly, based on the remote sensing emergency knowledge database, we utilize the sematic network to extract the key words in the input documents dataset. Then, using the semantic analysis based on words segmentation and PLSA, to establish the sematic access environment to identify the requirement of users and match the emergency knowledge in the database. Finally, the user preference model was established, which could help the system to return the corresponding information to the different users. The results indicate that semantic analysis can dispose the natural disaster knowledge effectively, which will realize diversified information service, enhance the precision of information retrieval and satisfy the requirement of users.