bluuebunny/crossref_metadata_2025 huggingface dataset:
ANISOTROPIC SCATTERING SHADOW COMPENSATION METHOD FOR REMOTE SENSING IMAGE WITH CONSIDERATION OF TERRAIN
Authors: Wang Qiongjie , Yan Li
Published: August 2016

With the rapid development of sensor networks and earth observation technology, a large quantity of high resolution remote sensing data is available. However, the influence of shadow has become increasingly greater due to the higher resolution shows more complex and detailed land cover, especially under the shadow. Shadow areas usually have lower intensity and fuzzy boundary, which make the images hard to interpret automatically. In this paper, a simple and effective shadow (including soft shadow) detection and compensation method is proposed based on normal data, Digital Elevation Model (DEM) and sun position. First, we use high accuracy DEM and sun position to rebuild the geometric relationship between surface and sun at the time the image shoot and get the hard shadow boundary and sky view factor (SVF) of each pixel. Anisotropic scattering assumption is accepted to determine the soft shadow factor mainly affected by diffuse radiation. Finally, an easy radiation transmission model is used to compensate the shadow area. Compared with the spectral detection method, our detection method has strict theoretical basis, reliable compensation result and minor affected by the image quality. The compensation strategy can effectively improve the radiation intensity of shadow area, reduce the information loss brought by shadow and improve the robustness and efficiency of the classification algorithms.
DETERMINING STAND PARAMETERS FROM UAS-BASED POINT CLOUDS
Authors: Yilmaz V. , Serifoglu C. , Gungor O.
Published: August 2016

In Turkey, forest management plans are produced by terrestrial surveying techniques for 10 or 20 year periods, which can be considered quite long to maintain the sustainability of forests. For a successful forest management plan, it is necessary to collect accurate information about the stand parameters and store them in dynamic and robust databases. The position, number, height and closure of trees are among the most important stand parameters required for a forest management plan. Determining the position of each single tree is challenging in such an area consisting of too many interlocking trees. Hence, in this study, an object-based tree detection methodology has been developed in MATLAB programming language to determine the position of each tree top in a highly closed area. The developed algorithm uses the Canopy Height Model (CHM), which is computed from the Digital Terrain Model (DTM) and Digital Surface Model (DSM) generated by using the point cloud extracted from the images taken from a UAS (Unmanned Aerial System). The heights of trees have been determined by using the CHM. The closure of the trees has been determined with the written MATLAB script. The results show that the developed tree detection methodology detected more than 70% of the trees successfully. It can also be concluded that the stand parameters may be determined by using the UAS-based point clouds depending on the characteristics of the study area. In addition, determination of the stand parameters by using point clouds reduces the time needed to produce forest management plans.
ANALYSING POST-SEISMIC DEFORMATION OF IZMIT EARTHQUAKE WITH INSAR, GNSS AND COULOMB STRESS MODELLING
Authors: Barut R. Alac , Trinder J. , Rizos C.
Published: August 2016

On August 17th 1999, a Mw 7.4 earthquake struck the city of Izmit in the north-west of Turkey. This event was one of the most devastating earthquakes of the twentieth century. The epicentre of the Izmit earthquake was on the North Anatolian Fault (NAF) which is one of the most active right-lateral strike-slip faults on earth. However, this earthquake offers an opportunity to study how strain is accommodated in an inter-segment region of a large strike slip fault. In order to determine the Izmit earthquake post-seismic effects, the authors modelled Coulomb stress changes of the aftershocks, as well as using the deformation measurement techniques of Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS). The authors have shown that InSAR and GNSS observations over a time period of three months after the earthquake combined with Coulomb Stress Change Modelling can explain the fault zone expansion, as well as the deformation of the northern region of the NAF. It was also found that there is a strong agreement between the InSAR and GNSS results for the post-seismic phases of investigation, with differences less than 2mm, and the standard deviation of the differences is less than 1mm.
EVALUATING THE POTENTIAL OF SATELLITE HYPERSPECTRAL RESURS-P DATA FOR FOREST SPECIES CLASSIFICATION
Authors: Brovkina O. , Hanuš J. , Zemek F. , Mochalov V. , Grigorieva O. , Pikla M.
Published: August 2016

Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4) on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.
ESTIMATION OF PHYSICAL PARAMETERS OF A MULTILAYERED MULTI-SCALE VEGETATED SURFACE
Authors: Hosni I. , Bennaceur Farah L. , Naceur M. S. , Farah I. R.
Published: August 2016

Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification.

 Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere.

 Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own.

 This paper presents a synergistic methodology of SAR and optical remote sensing data, and it’s for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil.

 Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.
GPS AND GLONASS COMBINED STATIC PRECISE POINT POSITIONING (PPP)
Authors: Pandey D. , Dwivedi R. , Dikshit O. , Singh A. K.
Published: August 2016

With the rapid development of multi-constellation Global Navigation Satellite Systems (GNSSs), satellite navigation is undergoing drastic changes. Presently, more than 70 satellites are already available and nearly 120 more satellites will be available in the coming years after the achievement of complete constellation for all four systems- GPS, GLONASS, Galileo and BeiDou. The significant improvement in terms of satellite visibility, spatial geometry, dilution of precision and accuracy demands the utilization of combining multi-GNSS for Precise Point Positioning (PPP), especially in constrained environments. Currently, PPP is performed based on the processing of only GPS observations. Static and kinematic PPP solutions based on the processing of only GPS observations is limited by the satellite visibility, which is often insufficient for the mountainous and open pit mines areas. One of the easiest options available to enhance the positioning reliability is to integrate GPS and GLONASS observations. This research investigates the efficacy of combining GPS and GLONASS observations for achieving static PPP solution and its sensitivity to different processing methodology. Two static PPP solutions, namely standalone GPS and combined GPS-GLONASS solutions are compared. The datasets are processed using the open source GNSS processing environment gLAB 2.2.7 as well as magicGNSS software package. The results reveal that the addition of GLONASS observations improves the static positioning accuracy in comparison with the standalone GPS point positioning. Further, results show that there is an improvement in the three dimensional positioning accuracy. It is also shown that the addition of GLONASS constellation improves the total number of visible satellites by more than 60% which leads to the improvement of satellite geometry represented by Position Dilution of Precision (PDOP) by more than 30%.
DETECTION OF CRACKS IN PAVED ROAD SURFACE USING LASER SCAN IMAGE DATA
Authors: Choi J. , Zhu L. , Kurosu H.
Published: August 2016

In the current study, we developed a methodology for detecting cracks in the surface of paved road using 3D digital surface model of road created by measuring with three-dimensional laser scanner which works on the basis of the light-section method automatically. For the detection of cracks from the imagery data of the model, the background subtraction method (Rolling Ball Background Subtraction Algorithm) was applied to the data for filtering out the background noise originating from the undulation and gradual slope and also for filtering the ruts that were caused by wearing, aging and excessive use of road and other reasons. We confirmed the influence from the difference in height (depth) caused by forgoing reasons included in a data can be reduced significantly at this stage. Various parameters of ball radius were applied for checking how the result of data obtained with this process vary according to the change of parameter and it becomes clear that there are not important differences by the change of parameters if they are in a certain range radius. And then, image segmentation was performed by multi-resolution segmentation based on the object-based image analysis technique. The parameters for the image segmentation, scale, pixel value (height/depth) and the compactness of objects were used. For the classification of cracks in the database, the height, length and other geometric property are used and we confirmed the method is useful for the detection of cracks in a paved road surface.
A NEW AUTOMATIC SYSTEM CALIBRATION OF MULTI-CAMERAS AND LIDAR SENSORS
Authors: Hassanein M. , Moussa A. , El-Sheimy N.
Published: August 2016

In the last few years, multi-cameras and LIDAR systems draw the attention of the mapping community. They have been deployed on different mobile mapping platforms. The different uses of these platforms, especially the UAVs, offered new applications and developments which require fast and accurate results. The successful calibration of such systems is a key factor to achieve accurate results and for the successful processing of the system measurements especially with the different types of measurements provided by the LIDAR and the cameras. The system calibration aims to estimate the geometric relationships between the different system components. A number of applications require the systems be ready for operation in a short time especially for disasters monitoring applications. Also, many of the present system calibration techniques are constrained with the need of special arrangements in labs for the calibration procedures. In this paper, a new technique for calibration of integrated LIDAR and multi-cameras systems is presented. The new proposed technique offers a calibration solution that overcomes the need for special labs for standard calibration procedures. In the proposed technique, 3D reconstruction of automatically detected and matched image points is used to generate a sparse images-driven point cloud then, a registration between the LIDAR generated 3D point cloud and the images-driven 3D point takes place to estimate the geometric relationships between the cameras and the LIDAR.. In the presented technique a simple 3D artificial target is used to simplify the lab requirements for the calibration procedure. The used target is composed of three intersected plates. The choice of such target geometry was to ensure enough conditions for the convergence of registration between the constructed 3D point clouds from the two systems. The achieved results of the proposed approach prove its ability to provide an adequate and fully automated calibration without sophisticated calibration arrangement requirements. The proposed technique introduces high potential for system calibration for many applications especially those with critical logistic and time constraints such as in disaster monitoring applications.
ACCURACY ASSESSMENT OF MOBILE MAPPING POINT CLOUDS USING THE EXISTING ENVIRONMENT AS TERRESTRIAL REFERENCE
Authors: Hofmann S. , Brenner C.
Published: August 2016

Mobile mapping data is widely used in various applications, what makes it especially important for data users to get a statistically verified quality statement on the geometric accuracy of the acquired point clouds or its processed products. The accuracy of point clouds can be divided into an absolute and a relative quality, where the absolute quality describes the position of the point cloud in a world coordinate system such as WGS84 or UTM, whereas the relative accuracy describes the accuracy within the point cloud itself. Furthermore, the quality of processed products such as segmented features depends on the global accuracy of the point cloud but mainly on the quality of the processing steps. Several data sources with different characteristics and quality can be thought of as potential reference data, such as cadastral maps, orthophoto, artificial control objects or terrestrial surveys using a total station. In this work a test field in a selected residential area was acquired as reference data in a terrestrial survey using a total station. In order to reach high accuracy the stationing of the total station was based on a newly made geodetic network with a local accuracy of less than 3 mm. The global position of the network was determined using a long time GNSS survey reaching an accuracy of 8 mm. Based on this geodetic network a 3D test field with facades and street profiles was measured with a total station, each point with a two-dimensional position and altitude. In addition, the surface of poles of street lights, traffic signs and trees was acquired using the scanning mode of the total station.

 Comparing this reference data to the acquired mobile mapping point clouds of several measurement campaigns a detailed quality statement on the accuracy of the point cloud data is made. Additionally, the advantages and disadvantages of the described reference data source concerning availability, cost, accuracy and applicability are discussed.
ROBUST PARALLEL MOTION ESTIMATION AND MAPPING WITH STEREO CAMERAS IN UNDERGROUND INFRASTRUCTURE
Authors: Liu Chun , Li Zhengning , Zhou Yuan
Published: August 2016

Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it’s also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.
RAPID INSPECTION OF PAVEMENT MARKINGS USING MOBILE LIDAR POINT CLOUDS
Authors: Zhang Haocheng , Li Jonathan , Cheng Ming , Wang Cheng
Published: August 2016

This study aims at building a robust semi-automated pavement marking extraction workflow based on the use of mobile LiDAR point clouds. The proposed workflow consists of three components: preprocessing, extraction, and classification. In preprocessing, the mobile LiDAR point clouds are converted into the radiometrically corrected intensity imagery of the road surface. Then the pavement markings are automatically extracted with the intensity using a set of algorithms, including Otsu’s thresholding, neighbor-counting filtering, and region growing. Finally, the extracted pavement markings are classified with the geometric parameters using a manually defined decision tree. Case studies are conducted using the mobile LiDAR dataset acquired in Xiamen (Fujian, China) with different road environments by the RIEGL VMX-450 system. The results demonstrated that the proposed workflow and our software tool can achieve 93% in completeness, 95% in correctness, and 94% in F-score when using Xiamen dataset.
A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD
Authors: Zhang Zongliang , Li Jonathan , Li Xin , Lin Yangbin , Zhang Shanxin , Wang Cheng
Published: August 2016

This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.
HIGH-RESOLUTION DEBRIS FLOW VOLUME MAPPING WITH UNMANNED AERIAL SYSTEMS (UAS) AND PHOTOGRAMMETRIC TECHNIQUES
Authors: Adams M. S. , Fromm R. , Lechner V.
Published: August 2016

Debris flows cause an average € 30 million damages and 1-2 fatalities every year in Austria. Detailed documentation of their extent and magnitude is essential for understanding, preventing and mitigating these natural hazard events. The recent development of unmanned aerial systems (UAS) has provided a new possibility for on-demand high-resolution monitoring and mapping. Here, we present a study, where the spatial extent and volume of a large debris flow event were mapped with different UAS, fitted with commercial off-the-shelf sensors. Orthophotos and digital terrain models (DTM) were calculated using structure-from-motion photogrammetry software. Terrain height differences caused by the debris flow in the catchment and valley floor were derived by subtracting the pre-event airborne laser scanning (ALS) DTM from a post-event UAS-DTM. The analysis of the volumetric sediment budget showed, that approximately 265,000 m³ material was mobilised in the catchment, of which 45,000 m³ settled there; of the material, which reached the valley floor, 120,000 m³ was deposited, while another 10,000 m³ was eroded from there. The UAS-results were validated against ALS data and imagery from a traditional manned-aircraft photogrammetry campaign. In conclusion, the UAS-data can reach an accuracy and precision comparable to manned aircraft data, but with the added benefits of higher flexibility, easier repeatability, less operational constraints and higher spatial resolution.
A ROBUST REGISTRATION ALGORITHM FOR POINT CLOUDS FROM UAV IMAGES FOR CHANGE DETECTION
Authors: Al-Rawabdeh A. , Al-Gurrani H. , Al-Durgham K. , Detchev I. , He F. , El-Sheimy N. , Habib A.
Published: August 2016

Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs over the period of one year (i.e., May 2014 and May 2015). Note that due to the coarse accuracy of the on-board GPS receiver (e.g., +/- 5-10 m) the geo-tagged positions of the images were only used as initial values in the bundle block adjustment. Normal distances, signifying detected changes, varying from 20 cm to 4 m were identified between the two epochs. The accuracy of the co-registered surfaces was estimated by comparing non-active patches within the monitored area of interest. Since these non-active sub-areas are stationary, the computed normal distances should theoretically be close to zero. The quality control of the registration results showed that the average normal distance was approximately 4 cm, which is within the noise level of the reconstructed surfaces.
UAV PHOTOGRAMMETRY WITH OBLIQUE IMAGES: FIRST ANALYSIS ON DATA ACQUISITION AND PROCESSING
Authors: Aicardi I. , Chiabrando F. , Grasso N. , Lingua A. M. , Noardo F. , Spanò A.
Published: August 2016

In recent years, many studies revealed the advantages of using airborne oblique images for obtaining improved 3D city models (e.g. including façades and building footprints). Expensive airborne cameras, installed on traditional aerial platforms, usually acquired the data. The purpose of this paper is to evaluate the possibility of acquire and use oblique images for the 3D reconstruction of a historical building, obtained by UAV (Unmanned Aerial Vehicle) and traditional COTS (Commercial Off-the-Shelf) digital cameras (more compact and lighter than generally used devices), for the realization of high-level-of-detail architectural survey. The critical issues of the acquisitions from a common UAV (flight planning strategies, ground control points, check points distribution and measurement, etc.) are described. Another important considered aspect was the evaluation of the possibility to use such systems as low cost methods for obtaining complete information from an aerial point of view in case of emergency problems or, as in the present paper, in the cultural heritage application field. The data processing was realized using SfM-based approach for point cloud generation: different dense image-matching algorithms implemented in some commercial and open source software were tested. The achieved results are analysed and the discrepancies from some reference LiDAR data are computed for a final evaluation. The system was tested on the S. Maria Chapel, a part of the Novalesa Abbey (Italy).
EVALUATION OF A NOVEL UAV-BORNE TOPO-BATHYMETRIC LASER PROFILER
Authors: Mandlburger G. , Pfennigbauer M. , Wieser M. , Riegl U. , Pfeifer N.
Published: August 2016

We present a novel topo-bathymetric laser profiler. The sensor system (RIEGL BathyCopter) comprises a laser range finder, an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver, a control unit, and digital cameras mounted on an octocopter UAV (RiCOPTER). The range finder operates on the time-of-flight measurement principle and utilizes very short laser pulses (<1 ns) in the green domain of the spectrum (λ=532 nm) for measuring distances to both the water surface and the river bottom. For assessing the precision and accuracy of the system an experiment was carried out in October 2015 at a pre-alpine river (Pielach in Lower Austria). A 200 m longitudinal section and 12 river cross sections were measured with the BathyCopter sensor system at a flight altitude of 15-20 m above ground level and a measurement rate of 4 kHz. The 3D laser profiler points were compared with independent, quasi-simultaneous data acquisitions using (i) the RIEGL VUX1-UAV lightweight topographic laser scanning system (bare earth, water surface) and (ii) terrestrial survey (river bed). Over bare earth the laser profiler heights have a std. dev. of 3 cm, the water surface height appears to be underestimated by 5 cm, and river bottom heights differ from the reference measurements by 10 cm with a std. dev. of 13 cm. When restricting the comparison to laser profiler bottom points and reference measurements with a lateral offset below 1 m, the values improve to 4 cm bias with a std. dev. of 6 cm. We report additionally on challenges in comparing UAV-borne to terrestrial profiles. Based on the accuracy and the small footprint (3.5 cm at the water surface) we concluded that the acquired 3D points can potentially serve as input data (river bed geometry, grain roughness) and validation data (water surface, water depth) for hydrodynamic-numerical models.
VOLUME COMPUTATION OF A STOCKPILE – A STUDY CASE COMPARING GPS AND UAV MEASUREMENTS IN AN OPEN PIT QUARRY
Authors: Raeva P. L. , Filipova S. L. , Filipov D. G.
Published: August 2016

The following paper aims to test and evaluate the accuracy of UAV data for volumetric measurements to the conventional GNSS techniques. For this purpose, an appropriate open pit quarry has been chosen. Two sets of measurements were performed. Firstly, a stockpile was measured by GNSS technologies and later other terrestrial GNSS measurements for modelling the berms of the quarry were taken. Secondly, the area of the whole quarry including the stockpile site was mapped by a UAV flight. Having considered how dynamic our world is, new techniques and methods should be presented in numerous fields. For instance, the management of an open pit quarry requires gaining, processing and storing a large amount of information which is constantly changing with time. Fast and precise acquisition of measurements regarding the process taking place in a quarry is the key to an effective and stable maintenance. In other words, this means getting an objective evaluations of the processes, using up-to-date technologies and reliable accuracy of the results. Often legislations concerning mine engineering state that the volumetric calculations are to present ±3% accuracy of the whole amount. On one hand, extremely precise measurements could be performed by GNSS technologies, however, it could be really time consuming. On the other hand, UAV photogrammetry presents a fast, accurate method for mapping large areas and calculating stockpiles volumes. The study case was performed as a part of a master thesis.
3D GEO-INFORMATION REQUIREMENTS FOR DISASTER AND EMERGENCY MANAGEMENT
Authors: Demir Ozbek E. , Zlatanova S. , Ates Aydar S. , Yomralioglu T.
Published: August 2016

A conceptual approach is proposed to define 3D geo-information requirement for different types of disasters. This approach includes components such as Disaster Type-Sector-Actor-Process-Activity-Task-Data. According to disaster types processes, activities, tasks, sectors, and responsible and operational actors are derived. Based on the tasks, the needed level of detail for 3D geo-information model is determined. The levels of detail are compliant with the 3D international standard CityGML. After a brief introduction on the disaster phases and geo-information requirement for actors to perform the tasks, the paper discusses the current situation of disaster and emergency management in Turkey and elaborates on components of conceptual approach. This paper discusses the 3D geo-information requirements for the tasks to be used in the framework of 3D geo-information model for Disaster and Emergency Management System in Turkey. The framework is demonstrated for an industrial fire case in Turkey.
BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT
Authors: Haunert Jan-Henrik , Wolff Alexander
Published: August 2016

Map labeling is a classical problem of cartography that has frequently been approached by combinatorial optimization. Given a set of features in the map and for each feature a set of label candidates, a common problem is to select an independent set of labels (that is, a labeling without label–label overlaps) that contains as many labels as possible and at most one label for each feature. To obtain solutions of high cartographic quality, the labels can be weighted and one can maximize the total weight (rather than the number) of the selected labels. We argue, however, that when maximizing the weight of the labeling, interdependences between labels are insufficiently addressed. Furthermore, in a maximum-weight labeling, the labels tend to be densely packed and thus the map background can be occluded too much. We propose extensions of an existing model to overcome these limitations. Since even without our extensions the problem is NP-hard, we cannot hope for an efficient exact algorithm for the problem. Therefore, we present a formalization of our model as an integer linear program (ILP). This allows us to compute optimal solutions in reasonable time, which we demonstrate for randomly generated instances.
THE NEED OF NESTED GRIDS FOR AERIAL AND SATELLITE IMAGES AND DIGITAL ELEVATION MODELS
Authors: Villa G. , Mas S. , Fernández-Villarino X. , Martínez-Luceño J. , Ojeda J. C. , Pérez-Martín B. , Tejeiro J. A. , García-González C. , López-Romero E. , Soteres C.
Published: August 2016

Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in “Big Data” environments. Most of them can be avoided, or at least greatly reduced, with the use of a common “nested grid” for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. “Nested grids” are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A “nested grid” must be complemented by an appropriate “tiling schema”, ideally based on the “quad-tree” concept. In the last years a “de facto standard” grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its “WMTS Simple Profile” standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.
A Multi-Scale Settlement Matching Algorithm Based on ARG
Authors: Yue Han , Zhu Xinyan , Chen Di , Liu Lingjia
Published: August 2016

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
SCHOOL MAPPING AND GEOSPATIAL ANALYSIS OF THE SCHOOLS IN JASRA DEVELOPMENT BLOCK OF INDIA
Authors: Agrawal S. , Gupta R. D.
Published: August 2016

GIS is a collection of tools and techniques that works on the geospatial data and is used in the analysis and decision making. Education is an inherent part of any civil society. Proper educational facilities generate the high quality human resource for any nation. Therefore, government needs an efficient system that can help in analysing the current state of education and its progress. Government also needs a system that can support in decision making and policy framing. GIS can serve the mentioned requirements not only for government but also for the general public. In order to meet the standards of human development, it is necessary for the government and decision makers to have a close watch on the existing education policy and its implementation condition. School mapping plays an important role in this aspect. School mapping consists of building the geospatial database of schools that supports in the infrastructure development, policy analysis and decision making. The present research work is an attempt for supporting Right to Education (RTE) and Sarv Sikha Abhiyaan (SSA) programmes run by Government of India through the use of GIS. School mapping of the study area is performed which is followed by the geospatial analysis. This research work will help in assessing the present status of educational infrastructure in Jasra block of Allahabad district, India.
A TEMPORAL AND SPATIAL ANALYSIS OF URBAN HEAT ISLAND IN BASIN CITY UTILIZING REMOTE SENSING TECHNIQUES
Authors: Chang Hsiao-Tung
Published: August 2016

Urban Heat Island (UHI) has been becoming a key factor in deteriorating the urban ecological environment. Spatial-temporal analysis on its prototype of basin city’s UHI and quantitatively evaluating effect from rapid urbanization will provide theoretical foundation for relieving UHI effect. Based on Landsat 8, ETM+ and TM images of Taipei basin areas from 1900 to 2015, this article has retrieved the land surface temperature (LST) at summer solstice of each year, and then analysed spatial-temporal pattern and evolution characters of UHI in Taipei basin in this decade. The results showed that the expansion built district, UHI area constantly expanded from centre city to the suburb areas. The prototype of UHI in Taipei basin that showed in addition to higher temperatures in the centre city also were relatively high temperatures gathered boundaries surrounded by foot of mountains side. It calls “sinking heat island”. From 1900 to 2000, the higher UHI areas were different land use type change had obvious difference by public infrastructure works. And then, in next 15 years till 2015, building density of urban area has been increasing gradually. It has the trend that UHI flooding raises follow urban land use density. Hot spot of UHI in Taipei basin also has the same characteristics. The results suggest that anthropogenic heat release probably plays a significant role in the UHI effect, and must be considered in urban planning adaptation strategies.
ON-LINE GIS ANALYSIS AND IMAGE PROCESSING FOR GEOPORTAL KIELCE/POLAND DEVELOPMENT
Authors: Hejmanowska B. , Głowienka E. , Florek-Paszkowski R.
Published: August 2016

GIS databases are widely available on the Internet, but mainly for visualization with limited functionality; very simple queries are possible i.e. attribute query, coordinate readout, line and area measurements or pathfinder. A little more complex analysis (i.e. buffering or intersection) are rare offered. Paper aims at the concept of Geoportal functionality development in the field of GIS analysis. Multi-Criteria Evaluation (MCE) is planned to be implemented in web application. OGC Service is used for data acquisition from the server and results visualization. Advanced GIS analysis is planned in PostGIS and Python programming. In the paper an example of MCE analysis basing on Geoportal Kielce is presented. Other field where Geoportal can be developed is implementation of processing new available satellite images free of charge (Sentinel-2, Landsat 8, ASTER, WV-2). Now we are witnessing a revolution in access to the satellite imagery without charge. This should result in an increase of interest in the use of these data in various fields by a larger number of users, not necessarily specialists in remote sensing. Therefore, it seems reasonable to expand the functionality of Internet's tools for data processing by non-specialists, by automating data collection and prepared predefined analysis.
ACCURACY AND SPATIAL VARIABILITY IN GPS SURVEYING FOR LANDSLIDE MAPPING ON ROAD INVENTORIES AT A SEMI-DETAILED SCALE: THE CASE IN COLOMBIA
Authors: Murillo Feo C. A. , Martnez Martinez L. J. , Correa Muñoz N. A.
Published: August 2016

The accuracy of locating attributes on topographic surfaces when, using GPS in mountainous areas, is affected by obstacles to wave propagation. As part of this research on the semi-automatic detection of landslides, we evaluate the accuracy and spatial distribution of the horizontal error in GPS positioning in the tertiary road network of six municipalities located in mountainous areas in the department of Cauca, Colombia, using geo-referencing with GPS mapping equipment and static-fast and pseudo-kinematic methods. We obtained quality parameters for the GPS surveys with differential correction, using a post-processing method. The consolidated database underwent exploratory analyses to determine the statistical distribution, a multivariate analysis to establish relationships and partnerships between the variables, and an analysis of the spatial variability and calculus of accuracy, considering the effect of non-Gaussian distribution errors. The evaluation of the internal validity of the data provide metrics with a confidence level of 95% between 1.24 and 2.45 m in the static-fast mode and between 0.86 and 4.2 m in the pseudo-kinematic mode. The external validity had an absolute error of 4.69 m, indicating that this descriptor is more critical than precision. Based on the ASPRS standard, the scale obtained with the evaluated equipment was in the order of 1:20000, a level of detail expected in the landslide-mapping project. Modelling the spatial variability of the horizontal errors from the empirical semi-variogram analysis showed predictions errors close to the external validity of the devices.
A VERSION-SIMILARITY BASED TRUST DEGREE COMPUTATION MODEL FOR CROWDSOURCING GEOGRAPHIC DATA
Authors: Zhou Xiaoguang , Zhao Yijiang
Published: August 2016

Quality evaluation and control has become the main concern of VGI. In this paper, trust is used as a proxy of VGI quality, a version-similarity based trust degree computation model for crowdsourcing geographic data is presented. This model is based on the assumption that the quality of VGI objects mainly determined by the professional skill and integrity (called reputation in this paper), and the reputation of the contributor is movable. The contributor’s reputation is calculated using the similarity degree among the multi-versions for the same entity state. The trust degree of VGI object is determined by the trust degree of its previous version, the reputation of the last contributor and the modification proportion. In order to verify this presented model, a prototype system for computing the trust degree of VGI objects is developed by programming with Visual C# 2010. The historical data of Berlin of OpenStreetMap (OSM) are employed for experiments. The experimental results demonstrate that the quality of crowdsourcing geographic data is highly positive correlation with its trustworthiness. As the evaluation is based on version-similarity, not based on the direct subjective evaluation among users, the evaluation result is objective. Furthermore, as the movability property of the contributors’ reputation is used in this presented method, our method has a higher assessment coverage than the existing methods.
DO THE VISUAL COMPLEXITY ALGORITHMS MATCH THE GENERALIZATION PROCESS IN GEOGRAPHICAL DISPLAYS?
Authors: Brychtová A. , Çöltekin A. , Pászto V.
Published: August 2016

In this study, we first develop a hypothesis that existing quantitative visual complexity measures will overall reflect the level of cartographic generalization, and test this hypothesis. Specifically, to test our hypothesis, we first selected common geovisualization types (i.e., cartographic maps, hybrid maps, satellite images and shaded relief maps) and retrieved examples as provided by Google Maps, OpenStreetMap and SchweizMobil by swisstopo. Selected geovisualizations vary in cartographic design choices, scene contents and different levels of generalization. Following this, we applied one of Rosenholtz et al.’s (2007) visual clutter algorithms to obtain quantitative visual complexity scores for screenshots of the selected maps. We hypothesized that visual complexity should be constant across generalization levels, however, the algorithm suggested that the complexity of small-scale displays (less detailed) is higher than those of large-scale (high detail). We also observed vast differences in visual complexity among maps providers, which we attribute to their varying approaches towards the cartographic design and generalization process. Our efforts will contribute towards creating recommendations as to how the visual complexity algorithms could be optimized for cartographic products, and eventually be utilized as a part of the cartographic design process to assess the visual complexity.
ON THE USABILITY AND USEFULNESS OF 3D (GEO)VISUALIZATIONS – A FOCUS ON VIRTUAL REALITY ENVIRONMENTS
Authors: Çöltekin A. , Lokka I. , Zahner M.
Published: August 2016

Whether and when should we show data in 3D is an on-going debate in communities conducting visualization research. A strong opposition exists in the information visualization (Infovis) community, and seemingly unnecessary/unwarranted use of 3D, e.g., in plots, bar or pie charts, is heavily criticized. The scientific visualization (Scivis) community, on the other hand, is more supportive of the use of 3D as it allows ‘seeing’ invisible phenomena, or designing and printing things that are used in e.g., surgeries, educational settings etc. Geographic visualization (Geovis) stands between the Infovis and Scivis communities. In geographic information science, most visuo-spatial analyses have been sufficiently conducted in 2D or 2.5D, including analyses related to terrain and much of the urban phenomena. On the other hand, there has always been a strong interest in 3D, with similar motivations as in Scivis community. Among many types of 3D visualizations, a popular one that is exploited both for visual analysis and visualization is the highly realistic (geo)virtual environments. Such environments may be engaging and memorable for the viewers because they offer highly immersive experiences. However, it is not yet well-established if we should opt to show the data in 3D; and if yes, a) what type of 3D we should use, b) for what task types, and c) for whom. In this paper, we identify some of the central arguments for and against the use of 3D visualizations around these three considerations in a concise interdisciplinary literature review.
IMPACT OF SCHEMATIC DESIGNS ON THE COGNITION OF UNDERGROUND TUBE MAPS
Authors: Liu Zheng , Li Zhilin
Published: August 2016

Schematic maps have been popularly employed to represent transport networks, particularly underground tube lines (or metro lines), since its adoption by the Official London Underground in early 1930s. Such maps employ straightened lines along horizontal, vertical and diagonal directions. Recently, some researchers started to argue that the distortion in such a schematization may cause big distortion and some new designs are proposed. This project aims to make a comparative analysis of such a schematic design with a new design proposed by Mark Noad in 2011, which makes use of lines along 30º and 60º directions instead of the 45º direction. Tasks have been designed for evaluating the effect of schematic designs on route planning by travellers. The participant was asked to choose the route s/he would take among two or three possible route options and then read the name of the selected transfer station. Eye-tracking technique has been employed to track the map recognition process. Total travel time is used as criterion for effectiveness; completion time and mental work cost are used for efficiency evaluation. It has been found that (1) the design of map style has significant impact on users’ travel decision making, especially map distance and transfer station symbol designs, and (2) the design style of a schematic map will have great impact on the effectiveness and efficiency of map recognition.