bluuebunny/crossref_metadata_2025 huggingface dataset:
CONTRIBUTION OF THE NEW WORLDVIEW-2 SPECTRAL BANDS FOR URBAN MAPPING IN COASTAL AREAS: CASE STUDY SÃO LUÍS ( MARANHÃO STATE, BRAZIL)
Authors: Souza U. D. V. , kux H. J. H.
Published: August 2012

Abstract. The objective of this study is to verify the contribution of the spectral bands from the new WorldView-2 satellite for the extraction of urban targets aiming a detailed mapping from the city of São Luis, at the coastal zone of Maranhão State, Brazil. This satellite system has 3 bands in the visible portion of the spectrum and also the following 4 new bands: Coastal (400-450 nm), Yellow (585- 625 nm), Red Edge (705-745 nm), and Near Infrared 2 (860-1040 nm). As for the methodology used, initially a fusion was made among the panchromatic and the multispectral bands, combining the spectral information of the multispectral bands with the geometric information of the panchromatic band. Following the ortho-rectification of the dataset was done, using ground control points (GCPs) obtained during field survey. The classification reached high values of Kappa indices. The use of the new bands Red Edge and Near Infrared 2, allowed the improvement of discriminations at tidal flats, mangrove and other vegetation types. The Yellow band improved the discrimination of bare soils – very important information for urban planning – and ceramic roofs. The Coastal band allowed to map the tidal channels which cross the urban area of São Luis, a typical feature of this coastal area. The functionalities of software GEODMA used, allowed an efficient attribute selection which improved the land cover classification from the test sites. The new WorldView-2 bands permit the identification and extraction of the features mentioned, because these bands are positioned at important parts of the electromagnetic spectrum, such as band Red Edge, which strongly improves the discrimination of vegetation conditions. Combining both higher spatial and spectral resolutions, WorldView-2 data allows an improvement on the discrimination of physical characteristics of the targets of interest, thus permitting a higher precision of land use/land cover maps, contributing to urban planning. The test sites of this study represent the main problem areas involving the city of São Luis and the entire region of the Maranhão Island.
COASTAL OCEAN OBSERVING NETWORK – OPEN SOURCE ARCHITECTURE FOR DATA MANAGEMENT AND WEB-BASED DATA SERVICES
Authors: Pattabhi Rama Rao E. , Venkat Shesu R. , Udaya Bhaskar T. V. S.
Published: August 2012

Abstract. The observations from the oceans are the backbone for any kind of operational services, viz. potential fishing zone advisory services, ocean state forecast, storm surges, cyclones, monsoon variability, tsunami, etc. Though it is important to monitor open Ocean, it is equally important to acquire sufficient data in the coastal ocean through coastal ocean observing systems for re-analysis, analysis and forecast of coastal ocean by assimilating different ocean variables, especially sub-surface information; validation of remote sensing data, ocean and atmosphere model/analysis and to understand the processes related to air-sea interaction and ocean physics. Accurate information and forecast of the state of the coastal ocean at different time scales is vital for the wellbeing of the coastal population as well as for the socio-economic development of the country through shipping, offshore oil and energy etc. Considering the importance of ocean observations in terms of understanding our ocean environment and utilize them for operational oceanography, a large number of platforms were deployed in the Indian Ocean including coastal observatories, to acquire data on ocean variables in and around Indian Seas. The coastal observation network includes HF Radars, wave rider buoys, sea level gauges, etc. The surface meteorological and oceanographic data generated by these observing networks are being translated into ocean information services through analysis and modelling. Centralized data management system is a critical component in providing timely delivery of Ocean information and advisory services. In this paper, we describe about the development of open-source architecture for real-time data reception from the coastal observation network, processing, quality control, database generation and web-based data services that includes on-line data visualization and data downloads by various means.
DEVELOPMENT OF A NEW GEOSPATIAL DATA SHARING/OVERLAY SYSTEM FOR LAND ENVIRONMENTAL STUDIES – CERES GAIA –
Authors: Tateishi R. , Sri Sumantyo J. T. , Miyazaki A. , Sumitani H.
Published: August 2012

Abstract. A new geospatial data sharing/overlay system, CEReS Gaia, has developed. The purpose of the system development is to promote land surface environmental studies. The system has developed to meet the requirements by academic users who wish easy data analysis by using his/her own data with existing other data. The system has the following features; a) internationally unlimited expansion of servers, b) multi-language capability (currently, only English), c) free access without user registration, d) data upload/download by registered users, e) capability to overlay user’s data on other registered data, f) option of open or selective data distribution.
A ROBUST PARALLEL FRAMEWORK FOR MASSIVE SPATIAL DATA PROCESSING ON HIGH PERFORMANCE CLUSTERS
Authors: Guan X.
Published: August 2012

Abstract. Massive spatial data requires considerable computing power for real-time processing. With the help of the development of multicore technology and computer component cost reduction in recent years, high performance clusters become the only economically viable solution for this requirement. Massive spatial data processing demands heavy I/O operations however, and should be characterized as a data-intensive application. Data-intensive application parallelization strategies are imcompatible with currently available procssing frameworks, which are basically designed for traditional compute-intensive applications. In this paper we introduce a Split-and-Merge paradigm for spatial data processing and also propose a robust parallel framework in a cluster environment to support this paradigm. The Split-and-Merge paradigm efficiently exploits data parallelism for massive data processing. The proposed framework is based on the open-source TORQUE project and hosted on a multicore-enabled Linux cluster. One common LiDAR point cloud algorithm, Delaunay triangulation, was implemented on the proposed framework to evaluate its efficiency and scalability. Experimental results demonstrate that the system provides efficient performance speedup.
VISION-AIDED CONTEXT-AWARE FRAMEWORK FOR PERSONAL NAVIGATION SERVICES
Authors: Saeedi S. , Moussa A. , El-Sheimy N.
Published: August 2012

Abstract. The ubiquity of mobile devices (such as smartphones and tablet-PCs) has encouraged the use of location-based services (LBS) that are relevant to the current location and context of a mobile user. The main challenge of LBS is to find a pervasive and accurate personal navigation system (PNS) in different situations of a mobile user. In this paper, we propose a method of personal navigation for pedestrians that allows a user to freely move in outdoor environments. This system aims at detection of the context information which is useful for improving personal navigation. The context information for a PNS consists of user activity modes (e.g. walking, stationary, driving, and etc.) and the mobile device orientation and placement with respect to the user. After detecting the context information, a low-cost integrated positioning algorithm has been employed to estimate pedestrian navigation parameters. The method is based on the integration of the relative user’s motion (changes of velocity and heading angle) estimation based on the video image matching and absolute position information provided by GPS. A Kalman filter (KF) has been used to improve the navigation solution when the user is walking and the phone is in his/her hand. The Experimental results demonstrate the capabilities of this method for outdoor personal navigation systems.
DTM CROSS VALIDATION AND MERGING: PROBLEMS AND SOLUTIONS FOR A CASE STUDY WITHIN THE HELI-DEM PROJECT
Authors: Biagi L. , Carcano L. , de Agostino M.
Published: August 2012

Abstract. Almost all official national cartographic bases in Europe include Digital Terrain Models (DTMs). To perform analyses at the borders between countries, transnational geographic information is needed: a transnational DTM can be obtained by merging regional DTMs (usually at low resolution) and other typically local high resolution DTMs. To be used the different DTMs must be in the same three dimensional reference frame, they must not present biases and must be consistent at the nominal scale. The following preliminary actions are required: • 3D reference frame transformation of gridded data, • cross-validation of the regional DTMs, • cross-check of the regional LR DTMs and the local HR DTMs. The paper discusses the study, the implementation and the application of algorithms to solve these problems in the Alpine area between Italy and Switzerland. For this case study, the regional DTMs of Lombardy, Piedmont and Switzerland, respectively with a planimetric resolution of 20, 50 and 25 meters are available. In addition, a LiDAR DTM with a planimetric resolution of 1 meter for the Lombardy and Piedmont hydrographic basins is available. The different DTMs have been transformed to the same reference frame by applying the official national 3D transformations. The cross-validation and the cross-check of the elevation datasets have been performed. All these operations have required the implementation of novel approaches to interpolate and compare DTMs and to spatially analyze their differences.
Comparison of Lunar Topographic Models Derived from Multiple Sources Based on Least Squares Matching
Authors: Guo J. , Wu B.
Published: August 2012

Abstract. Lunar topographic information is of paramount importance for lunar exploration missions and lunar scientific investigations. For lunar topographic models derived from different sources or missions, it is not uncommon to see inconsistencies among them. This paper presents a detailed comparative analysis of lunar topographic models derived from the Chang'E-1 and SELENE altimeter data. A least squares matching method is developed to register one topographic model to the other through a seven parameters transformation (three translation parameters, three rotation parameters, and one scale factor). Two typical study areas on the Moon are selected for detailed investigation, including the Sinus Iridium (the primary candidate landing site area for future Chinese robotic or human landed missions) and the Apollo 15 landing site area. Experimental results indicate that there are small shifts in both horizontal and vertical directions between these two data sets. After the least squares matching and shift removal, the topography derived from the two data sets show a consistent trend.
STRATEGIC MULTIPLE SENSOR DATA FUSION FOR TIME-CRITICAL NATURAL DISASTER RESPONSE
Authors: Kim S. , Goo S. , Park Y. , Choi J. , Cho M.
Published: August 2012

Abstract. Recently, large-scale natural disasters have been occurred in the various areas of the world. The super-sized multi-hazards over the world have required more and more scientific and systematic measurement technologies in the fields of management and response of natural disaster. The purpose of this study is to suggest a multi-sources data fusion approach like LiDAR, aerial images, and satellite imagery and evaluate its applicability for timely natural disaster response. In order to achieve a high-accurate mapping in time in disaster situation, we proposed strategic approach using multi-sensors data fusion in this paper. The data fusion approach using the satellite imagery, low altitude aerial imagery from the mini-UAV and the small manned helicopter, and LiDAR point data simultaneously is expected to enhance the capability for more accurate damage analysis and the faster hazard mapping.
ORTHO-RECTIFICATION OF HJ-1A/1B MULTI-SPECTRAL IMAGE BASED ON THE GCP IMAGE DATABASE
Authors: Li G. , Wang H. , Li C.
Published: August 2012

Abstract. HJ satellite is the abbreviation of the Small Satellite Constellation of Environment and Disaster Monitoring and Forecasting in China, which plays a very important role in forecasting and monitoring the environment problems and natural disasters. The ortho-rectification of HJ images aided by GCP (Ground Control Point) image database is presented in this paper. The GCP image database is constructed from historical LandSat-TM images and the GCP chip consists of image and geographic attribute information. Then auto-searching and matching algorithm is introduced and mis-matching elimination method is presented. The imaging model based on collinearity equation and the polynomial description of the attitude and position of scanning line is utilized for ortho-rectification. Four scene images are experimented and compared, and the result demonstrated the feasibility and high efficiency of the whole work flow.
APPLICATION POSSIBILITY OF SMARTPHONE AS PAYLOAD FOR PHOTOGRAMMETRIC UAV SYSTEM
Authors: Yun M. H. , Kim J. , Seo D. , Lee J. , Choi C.
Published: August 2012

Abstract. Smartphone can not only be operated under 3G network environment anytime and anyplace but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study is aimed to assess the possibility of smartphone as a payload for photogrammetric UAV system. Prior to such assessment, a smartphone-based photogrammetric UAV system application was developed, through which real-time image, location and attitude data was obtained using smartphone under both static and dynamic conditions. Subsequently the accuracy assessment on the location and attitude data obtained and sent by this system was conducted. The smartphone images were converted into ortho-images through image triangulation. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration. In case IO parameters were taken into account in the static experiment, the results from triangulation for any smartphone type were within 1.5 pixel (RMSE), which was improved at least by 35% compared to when IO parameters were not taken into account. On the contrary, the improvement effect of considering IO parameters on accuracy in triangulation for smartphone images in dynamic experiment was not significant compared to the static experiment. It was due to the significant impact of vibration and sudden attitude change of UAV on the actuator for automatic focus control within the camera built in smartphone under the dynamic condition. This cause appears to have a negative impact on the image-based DEM generation. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.
SEAMLESS NAVIGATION USING VARIOUS SENSORS: AN OVERVIEW OF THE SEAMLESS NAVIGATION CAMPAIGN
Authors: Nakagawa M. , Yamada Y. , Namie H. , Ebinuma T. , Kubo N. , Kawaguchi T. , Yoshida M. , Yasuda A.
Published: August 2012

Abstract. Seamless positioning techniques in indoor and outdoor environments are necessary for obtaining sensor locations. However, no definitive indoor-outdoor navigation system simultaneously provides high accuracy, high availability and low installation cost. Furthermore, crowded indoor-outdoor navigation systems consisting of multiple techniques will destructively interfere with each other, but an exclusive navigation environment will have difficulty providing stable location services for users. This anticipated issue needs to be investigated with experimental data and simulation results. However, experiments that are deliberately overcrowded with disparate location systems are rare. Therefore, the initial focus in our research was the construction of a test environment for indoor-outdoor seamless navigation experiments. Based on "Standards and Recommended Practices" (SARPs), we focused on accuracy, availability, continuity and integrity to verify the effects of seamless navigation under a combination of as many disparate systems and sensors as possible. We then conducted data acquisition and data analysis in seamless navigation through four integrated experiments. Based on the results of our experiments, we summarize some observations about seamless navigation using multiple navigation systems, and offer examples of the representative issues in our research. We also suggest some directions in indoor-outdoor navigation environment construction for seamless positioning using disparate systems and sensors.
UNDERSTANDING THE PAST, MANAGING THE FUTURE – Remotely sensed analysis of the urban sprawl of Istanbul for supporting decision making for a sustainable future
Authors: Altan O. , Kemper G.
Published: August 2012

Abstract. The GIS based analysis of the land use change of Istanbul delivers a huge and comprehensive database that can be used for further analysis. Trend analysis and scenarios enable a view to the future that highlights the needs for a proper planning. Also the understanding via comparison to other cities assists in order not to copy errors from other cities. GIS in combination with ancillary data open a wide field for managing the future of Istanbul.
THE DIRECT REGISTRATION OF LIDAR POINT CLOUDS AND HIGH RESOLUTION IMAGE BASED ON LINEAR FEATURE BY INTRODUCING AN UNKNOWN PARAMETER
Authors: Chunjing Y. , Guang G.
Published: August 2012

Abstract. The registration between optical images and point clouds is the first task when the combination of these two datasets is concerned. Due to the discrete nature of the point clouds, and the 2D-3D transformation in particular, a tie points based registration strategy which is commonly adopted in image-to-image registration is hard to be used directly in this scenario. A derived collinear equation describing the map relationship between an image point and a ground point is used as the mathematical model for registration, with the point in the LiDAR space expressed by its parametric form. such a map relation can be viewed as the mathematical model which registers the image pixels to point clouds. This model is not only suitable for a single image registration but also applicable to multiple consecutive images. We also studied scale problem in image and point clouds registration, with scale problem is defined by the optimal corresponding between the image resolution and the density of point clouds. Test dataset includes the DMC images and point clouds acquired by the Leica ALS50 II over an area in Henan Prov., China. Main contributions of the paper includes: [1] an derived collinear equation is introduced by which a ground point is expressed by its parametric form, which makes it possible to replace point feature by linear feature, hence avoiding the problem that it is almost impossible to find a point in the point clouds which is accurately corresponds to a point in the image space; [2] least square method is used to calculate the registration transformation parameters and the unknown parameter λ in the same time;[3] scale problem is analyzed semi-quantitatively and to the authors’ best knowledge, it is the first time in literature that clearly defines the scale problem and carries out semi-quantitative analysis in the context of LiDAR data processing.
NATIONAL LAND COVER AND RESOURCE STATISTICS
Authors: Nilsen A. B. , Bjørkelo K.
Published: August 2012

Abstract. An overall societal aim is to ensure a sustainable use and management of a country’s land resources. This requires continuous deliv-ery of reliable and up-to-date information to decision-makers. To be able to deliver this information the Norwegian Forest and Land-scape Institute (Skog og landskap) produces, among others, land resource statistics for all municipalities in Norway. The statistics are also produced on a county level and for the whole country. The acreage numbers are retrieved from a combination of different na-tional datasets in various scales together with interpretation of satellite images. Through a reclassification, statistics are calculated for certain land resource classes like arable land, pasture, forest based on productivity class, fresh water, snow and glacier, mountain-ous/scarcely vegetated area and built up area. Skog og landskap has for the last couple of years been using open source software. The whole statistics production line is carried out by the means of such software. The results are stored in XML-files that are published on the internet. The production requires processing of several databases with national coverage, and needs to handle geometric opera-tions efficiently and without error. The open software solution is reliable, stable and fast.
DESIGN OF LIVESTOCK MANAGEMENT TOOL FOR CLIMATE CHANGE RISK IN MONGOLIA
Authors: Oba A. , Yan W.
Published: August 2012

Abstract. In Mongolia, from 1999 to 2001 and 2009 to 2010, about 10 million livestock animals were seriously died due to starvation and the cold by effects of overgrazing and Zud: extreme snow in winter season. Thus, it is required to reduce its risk by controlling number of overwinter livestock animals. In order to do that, it is required to simulate how many animals do herders have to sell followed by carrying capacity. In order to avoid climate risk, it is necessary to manage farming comprehensively and control livestock numbers. Nevertheless it needs to consider about management, we have to research information about each management under different conditions of each area in all Mongolia. Thus, it needs to survey livestock management workflows of regional administration and GIS data about rangeland areas and their attributes in order to evaluate their nomadic life and their livestock objectively. It is essential to use some tools that have the function of processing the spatial data. It could cover wide areas and have different abilities for spatial relations. To solve this problem; we analyzed management workflows of herder and regional administration working in Mongolia, and designed a hierarchical structure of tables and data layers with the relational database. With this structure, we developed the structure of a WebGIS tool on the Adobe Flex platform for livestock management visually. It will be also useful for them to improve the accountability of activities. This system is a versatile WebGIS tool which can interact with various spatial scales.
SENSOR WEB SERVICES FOR EARLY FLOOD WARNINGS BASED ON SOIL MOISTURE PROFILES
Authors: Brinkhoff T. , Jansen S.
Published: August 2012

Abstract. As result of improved computing and communication capabilities, the use of sensors and sensor networks for environmental monitoring has gained considerable importance in the recent years. For an interoperable integration of sensor data like sensor descriptions, sensor measurements and alarm events, the Open Geospatial Consortium (OGC) started the Sensor Web Enablement (SWE) initiative and proposed several specifications in respect to a geospatial sensor web. First implementations of SWE software frameworks are available. In this paper, we present the results of the recent WEBBOS project. Its objective was to build up a system for early flood warnings by measuring soil moisture profiles. The use of soil moisture profiles is motivated by the fact that traditional approaches like the observation of water gauges are suitable for the prediction of large-river flooding but not for smaller drainage areas. We describe the architecture of our system and how it is built up by using existing software components to a large extent. Our special focus is on the incorporation of 3D soil moisture profiles into the SWE data model, on the integration of the new OGC Sensor Event Service, and on the development of a flexible web client for mapping and other visualization purposes.
ON THE NATIONAL GEOGRAPHICAL CONDITION MONITORING SEVERAL STRATEGIC ISSUES
Authors: Gui D. , Lin Z. , Zhang C. , Liu F.
Published: August 2012

Abstract. The state council of China approved national sustainable development strategy for land and natural resources research in the overall plan, presenting "building digital China, monitoring the national geographical conditions, developing geographical information industry, constructing surveying and mapping power Country," 24 character strategy. National geographical conditions monitoring is the new requirements of economic and social development, and also is important role and strategic tasks for surveying and mapping services to the scientific development of the sector initiative. In this paper, the content, main tasks and facing situation of national geographical conditions monitoring in China are elaborated analyzed. At last, several initiatives to promote national geographical situation monitoring realization, standardization and normalization are introduced. There are four parts in the paper as below.
Object-Based Building Extraction from High Resolution Satellite Imagery
Authors: Attarzadeh R. , Momeni M.
Published: August 2012

Abstract. Automatic building extraction from high resolution satellite imagery is considered as an important field of research in remote sensing and machine vision. Many algorithms for extraction of buildings from satellite images have been presented so far. These algorithms mainly have considered radiometric, geometric, edge detection and shadow criteria approaches to perform the building extraction. In this paper, we propose a novel object based approach for automatic and robust detection and extraction of building in high spatial resolution images. To achieve this goal, we use stable and variable features together. Stable features are derived from inherent characteristics of building phenomenon and variable features are extracted using SEparability and THresholds analysis tool. The proposed method has been applied on a QuickBird imagery of an urban area in Isfahan city and visual validation demonstrates that the proposed method provides promising results.
AUTOMATED 3D ROAD SIGN MAPPING WITH STEREOVISION-BASED MOBILE MAPPING EXPLOITING DISPARITY INFORMATION FROM DENSE STEREO MATCHING
Authors: Cavegn S. , Nebiker S.
Published: August 2012

Abstract. This paper presents algorithms and investigations on the automated detection, classification and mapping of road signs which systematically exploit depth information from stereo images. This approach was chosen due to recent progress in the development of stereo matching algorithms enabling the generation of accurate and dense depth maps. In comparison to mono imagery-based approaches, depth maps also allow 3D mapping of the objects. This is essential for efficient inventory and for future change detection purposes. Test measurements with the mobile mapping system by the Institute of Geomatics Engineering of the FHNW University of Applied Sciences and Arts Northwestern Switzerland demonstrated that the developed algorithms for the automated 3D road sign mapping perform well, even under difficult to poor lighting conditions. Approximately 90% of the relevant road signs with predominantly red, blue and yellow colors in Switzerland can be detected, and 85% can be classified correctly. Furthermore, fully automated mapping with a 3D accuracy of better than 10 cm is possible.
MULTITEMPORAL QUALITY ASSESSMENT OF GRASSLAND AND CROPLAND OBJECTS OF A TOPOGRAPHIC DATASET
Authors: Helmholz P. , Büschenfeld T. , Breitkopf U. , Müller S. , Rottensteiner F.
Published: August 2012

Abstract. As a consequence of the wide-spread application of digital geo-data in geographic information systems (GIS), quality control has become increasingly important to enhance the usefulness of the data. For economic reasons a high degree of automation is required for the quality control process. This goal can be achieved by automatic image analysis techniques. An example of how this can be achieved in the context of quality assessment of cropland and grassland GIS objects is given in this paper. The quality assessment of these objects of a topographic dataset is carried out based on multi-temporal information. The multi-temporal approach combines the channels of all available images as a multilayer image and applies a pixel-based SVM-classification. In this way multispectral as well as multi-temporal information is processed in parallel. The features used for the classification consist of spectral, textural (Haralick features) and structural (features derived from a semi-variogram) features. After the SVM-classification, the pixel-based result is mapped to the GIS-objects. Finally, a simple ruled-based approach is used in order to verify the objects of a GIS database. The approach was tested using a multi-temporal data set consisting of one 5-channel RapidEye image (GSD 5 m) and two 3-channel Disaster Monitoring Constellation (DMC) images (GSD 32 m). All images were taken within one year. The results show that by using our approach, quality control of GIS- cropland and grassland objects is possible and the human operator saves time using our approach compared to a completely manual quality assessment.
HOUSEDIFF: A MAP-BASED BUILDING CHANGE DETECTION FROM HIGH RESOLUTION SATELLITE IMAGERY USING GEOMETRIC OPTIMIZATION METHOD
Authors: Ishimaru N. , Iwamura K. , Kagawa Y. , Hino T.
Published: August 2012

Abstract. This paper presents a novel structural image analysis method based on geometric optimization techniques towards automatic building change detection. The aim of this method is to efficiently detect the changes of various buildings such as small houses and houses with complex roof in an urban area from high resolution satellite imagery by comparing with spatial database (maps). The previous research has indicated of the effectiveness of a map-based building change detection approach, and further investigation suggests the following three problems; (1) the large diversity of building types, roof shape, roof materials, illumination condition and shadow, (2) the difficulty of imagery and maps matching which normally leads to considerable position error, (3) the capacity of extracting various types of newly-built buildings. To solve these problems, we propose a new geometric optimization method which consists of the following two steps; (1) the building recognition based on a combinatorial optimization method for optimal building boundary extraction, (2) the newly-built building extraction based on an optimal building hypothesis search method. The experimental results showed that the detection rate was approximately 89% for existing and changed buildings, and approximately 83% for newly-built buildings. These results demonstrate the effectiveness of the proposed geometric optimization methods to integrate bottom-up and top-down analysis. By combining the locally detected image features with consideration of regional contexts from map, our method can achieve highly accurate building change detection in urban area. The method has been applied to a building change detection service named "HouseDiff" and succeeded in assisting users.
IN-DATABASE RASTER ANALYTICS: MAP ALGEBRA AND PARALLEL PROCESSING IN ORACLE SPATIAL GEORASTER
Authors: Xie Q. J. , Zhang Z. Z. , Ravada S.
Published: August 2012

Abstract. Over the past decade several products have been using enterprise database technology to store and manage geospatial imagery and raster data inside RDBMS, which in turn provides the best manageability and security. With the data volume growing exponentially, real-time or near real-time processing and analysis of such big data becomes more challenging. Oracle Spatial GeoRaster, different from most other products, takes the enterprise database-centric approach for both data management and data processing. This paper describes one of the central components of this database-centric approach: the processing engine built completely inside the database. Part of this processing engine is raster algebra, which we call the In-database Raster Analytics. This paper discusses the three key characteristics of this in-database analytics engine and the benefits. First, it moves the data processing closer to the data instead of moving the data to the processing, which helps achieve greater performance by overcoming the bottleneck of computer networks. Second, we designed and implemented a new raster algebra expression language. This language is based on PL/SQL and is currently focused on the "local" function type of map algebra. This language includes general arithmetic, logical and relational operators and any combination of them, which dramatically improves the analytical capability of the GeoRaster database. The third feature is the implementation of parallel processing of such operations to further improve performance. This paper also presents some sample use cases. The testing results demonstrate that this in-database approach for raster analytics can effectively help solve the biggest performance challenges we are facing today with big raster and image data.
PROTECTING UNESCO WORLD HERITAGE PROPERTIES'S INTEGRITY: THE ROLE OF RECORDING AND DOCUMENTATION IN RISK MANAGEMENT FOR PETRA
Authors: Santana Quintero M. , Cesaro G. , Ishakat F. , Vandesande A. , Vileikis O. , Vadafari A. , Paolini A. , Van Balen K. , Fakhoury L.
Published: August 2012

Abstract. Risk management – as it has been defined – involves the decision-making process following a risk assessment (Ball, Watt, 2003). It is the process that involves managing to minimize losses and impacts on the significant of historic structures and to reach the balance between gaining and losing opportunities. This contribution explains the "heritage information" platform developed using low-cost recording, documentation and information management tools to serve as container for assessments resulting from the application of a risk methodology at a pilot area of the Petra Archaeological Park, in particular those that permit digitally and cost effective to prepare an adequate baseline record to identify disturbances and threats. Furthermore, this paper will reflect on the issue of mapping the World Heritage property's boundaries by illustrating a methodology developed during the project and further research to overcome the lack of boundaries and buffer zone for the protection of the Petra World Heritage site, as identified in this project. This paper is based on on-going field project from a multidisciplinary team of experts from the Raymond Lemaire International Centre for Conservation (University of Leuven), UNESCO Amman, Petra Development Tourism and Region Authority (PDTRA), and Jordan's Department of Antiquities (DoA), as well as, experts from Jordan. The recording and documentation approach included in this contribution is part of an on-going effort to develop a methodology for mitigating (active and preventive) risks on the Petra Archaeological Park (Jordan). The risk assessment has been performed using non-intrusive techniques, which involve simple global navigation satellite system (GNSS), photography, and structured visual inspection, as well as, a heritage information framework based on Geographic Information Systems. The approach takes into consideration the comparison of vulnerability to sites with the value assessment to prioritize monuments at risk based on their importance of significance and magnitude of risk, in order for the authorities to plan more in-depth assessment for those highly significant monuments or areas at risk. A decision tool is envisaged as outcome of this project.
HIGH-RESOLUTION SURFACE RECONSTRUCTION FROM IMAGERY FOR CLOSE RANGE CULTURAL HERITAGE APPLICATIONS
Authors: Wenzel K. , Abdel-Wahab M. , Cefalu A. , Fritsch D.
Published: August 2012

Abstract. The recording of high resolution point clouds with sub-mm resolution is a demanding and cost intensive task, especially with current equipment like handheld laser scanners. We present an image based approached, where techniques of image matching and dense surface reconstruction are combined with a compact and affordable rig of off-the-shelf industry cameras. Such cameras provide high spatial resolution with low radiometric noise, which enables a one-shot solution and thus an efficient data acquisition while satisfying high accuracy requirements. However, the largest drawback of image based solutions is often the acquisition of surfaces with low texture where the image matching process might fail. Thus, an additional structured light projector is employed, represented here by the pseudo-random pattern projector of the Microsoft Kinect. Its strong infrared-laser projects speckles of different sizes. By using dense image matching techniques on the acquired images, a 3D point can be derived for almost each pixel. The use of multiple cameras enables the acquisition of a high resolution point cloud with high accuracy for each shot. For the proposed system up to 3.5 Mio. 3D points with sub-mm accuracy can be derived per shot. The registration of multiple shots is performed by Structure and Motion reconstruction techniques, where feature points are used to derive the camera positions and rotations automatically without initial information.
HIGH PRECISION TEXTURE RECONSTRUCTION FOR 3D SCULPTURE MODEL
Authors: Zhang F. , Huang H. , Zhang Z. , Fang W. , Li D.
Published: August 2012

Abstract. High precision 3D sculpture model can take the accurate records of the shape, material and color on the surface of the sculpture. It is an important foundation work of digital documentation, preservation, archaeological research and analysis for the sculpture types of cultural heritage. Constructing high precision 3D sculpture model includes two aspects: geometry modeling and texture reconstruction. But, there are many urgent problems still existing in the method of high precision texture reconstruction. This paper discussed a method of high precision texture reconstruction based on non-rigid transformation for 3D sculpture model. First, coarse registration of texture image to geometrical model is conducted with direct linear transformation (DLT) method. Then, the registration is optimized with thin plane spline (TPS) function to reduce local matching errors between texture image and geometrical model. Finally, texture mapping is implemented with optimized registration result. The experiments based on the sculpture in Dunhuang Mogao Grottoes of China are conducted, and the efficiency and feasibility of the proposed methods are proved.
ANALYSIS OF MOBILE LASER SCANNING DATA AND MULTI-VIEW IMAGE RECONSTRUCTION
Authors: Briese C. , Zach G. , Verhoeven G. , Ressl C. , Ullrich A. , Studnicka N. , Doneus M.
Published: August 2012

Abstract. The combination of laser scanning (LS, active, direct 3D measurement of the object surface) and photogrammetry (high geometric and radiometric resolution) is widely applied for object reconstruction (e.g. architecture, topography, monitoring, archaeology). Usually the results are a coloured point cloud or a textured mesh. The geometry is typically generated from the laser scanning point cloud and the radiometric information is the result of image acquisition. In the last years, next to significant developments in static (terrestrial LS) and kinematic LS (airborne and mobile LS) hardware and software, research in computer vision and photogrammetry lead to advanced automated procedures in image orientation and image matching. These methods allow a highly automated generation of 3D geometry just based on image data. Founded on advanced feature detector techniques (like SIFT (Scale Invariant Feature Transform)) very robust techniques for image orientation were established (cf. Bundler). In a subsequent step, dense multi-view stereo reconstruction algorithms allow the generation of very dense 3D point clouds that represent the scene geometry (cf. Patch-based Multi-View Stereo (PMVS2)). Within this paper the usage of mobile laser scanning (MLS) and simultaneously acquired image data for an advanced integrated scene reconstruction is studied. For the analysis the geometry of a scene is generated by both techniques independently. Then, the paper focuses on the quality assessment of both techniques. This includes a quality analysis of the individual surface models and a comparison of the direct georeferencing of the images using positional and orientation data of the on board GNSS-INS system and the indirect georeferencing of the imagery by automatic image orientation. For the practical evaluation a dataset from an archaeological monument is utilised. Based on the gained knowledge a discussion of the results is provided and a future strategy for the integration of both techniques is proposed.
RIGOROUS POINT-TO-PLANE REGISTRATION OF TERRESTRIAL LASER SCANS
Authors: Grant D. , Bethel J. , Crawford M.
Published: August 2012

Abstract. Terrestrial laser scanning data that are acquired from multiple scan locations need to be registered before any 3D modeling and/or analysis is conducted. This paper presents a rigorous point-to-plane registration approach that minimizes the distances between two overlapping laser scans, using the General Least Squares adjustment model. The proposed approach falls under the class of fine registration and does not require any targets or tie points. Given some initial registration parameters, the proposed approach utilizes the scanned points and estimated planar features on both scans to determine the optimum parameters in the least squares sense. Both the uncertainty of the points due to the incidence angle, and the uncertainty of the local normal vectors of the planar features are taken into account in the stochastic model of the adjustment. The impact that these considerations with the stochastic model have on the registration is then demonstrated with comparisons on real terrestrial laser scanning data, and on smaller simulated data.
CONTINUOUSLY DEFORMATION MONITORING OF SUBWAY TUNNEL BASED ON TERRESTRIAL POINT CLOUDS
Authors: Kang Z. , Tuo L. , Zlatanova S.
Published: August 2012

Abstract. The deformation monitoring of subway tunnel is of extraordinary necessity. Therefore, a method for deformation monitoring based on terrestrial point clouds is proposed in this paper. First, the traditional adjacent stations registration is replaced by sectioncontrolled registration, so that the common control points can be used by each station and thus the error accumulation avoided within a section. Afterwards, the central axis of the subway tunnel is determined through RANSAC (Random Sample Consensus) algorithm and curve fitting. Although with very high resolution, laser points are still discrete and thus the vertical section is computed via the quadric fitting of the vicinity of interest, instead of the fitting of the whole model of a subway tunnel, which is determined by the intersection line rotated about the central axis of tunnel within a vertical plane. The extraction of the vertical section is then optimized using RANSAC for the purpose of filtering out noises. Based on the extracted vertical sections, the volume of tunnel deformation is estimated by the comparison between vertical sections extracted at the same position from different epochs of point clouds. Furthermore, the continuously extracted vertical sections are deployed to evaluate the convergent tendency of the tunnel. The proposed algorithms are verified using real datasets in terms of accuracy and computation efficiency. The experimental result of fitting accuracy analysis shows the maximum deviation between interpolated point and real point is 1.5 mm, and the minimum one is 0.1 mm; the convergent tendency of the tunnel was detected by the comparison of adjacent fitting radius. The maximum error is 6 mm, while the minimum one is 1 mm. The computation cost of vertical section abstraction is within 3 seconds/section, which proves high efficiency..
SIMPLE ROOM SHAPE MODELING WITH SPARSE 3D POINT INFORMATION USING PHOTOGRAMMETRY AND APPLICATION SOFTWARE
Authors: Hirose S.
Published: August 2012

Abstract. In this paper, we propose an automated technique for creating a simplified 3D structure shape model of indoor environments from the sparse 3D point information provided by the photogrammetric method. Multiple coded-targets are used for the automatic detection, recognition and measurement of 3D coordinates of points on the room walls from the acquired stereo images. The sparse 3D information is then processed by our software for the estimation of a simplified 3D structure shape model of the room. Additionally, the 3D model is also translated into a development figure which represents multiple orthographic projections of the room. The proposed method is implemented into a flawless procedure which allows to obtain, by a few operations, a simplified 3D structure shape model of a room and its orthographic representation in drawing sheets. The developed application software can be used for the determination of the shape of rooms easily also by persons without experience in 3D measurement techniques.
PRODUCING A LINEAR LASER SYSTEM FOR 3D MODELIMG OF SMALL OBJECTS
Authors: Amini A. Sh. , Mozaffar M. H.
Published: August 2012

Abstract. Today, three dimensional modeling of objects is considered in many applications such as documentation of ancient heritage, quality control, reverse engineering and animation In this regard, there are a variety of methods for producing three-dimensional models. In this paper, a 3D modeling system is developed based on photogrammetry method using image processing and laser line extraction from images. In this method the laser beam profile is radiated on the body of the object and with video image acquisition, and extraction of laser line from the frames, three-dimensional coordinates of the objects can be achieved. In this regard, first the design and implementation of hardware, including cameras and laser systems was conducted. Afterwards, the system was calibrated. Finally, the software of the system was implemented for three dimensional data extraction. The system was investigated for modeling a number of objects. The results showed that the system can provide benefits such as low cost, appropriate speed and acceptable accuracy in 3D modeling of objects.
KILIMANJARO ICE CLIFF MONITORING WITH CLOSE RANGE PHOTOGRAMMETRY
Authors: Winkler M. , Pfeffer W. T. , Hanke K.
Published: August 2012

Abstract. The glaciers on the summit plateau of Kibo, the main peak of the Kilimanjaro massif (3°S, 37°E, 5895 m a.s.l.) in Tanzania, are characterized by steep ice cliffs at their margins. These form-persistent cliffs continuously retreat and, consequently, govern the decrease in plateau glacier area. In order to quantify the ice cliff recession and study their morphology, close-range terrestrial photogrammetry combined with automatic stereo matching techniques was used to derive high resolution digital surface models of a south-facing “sample cliff” at four different dates. Results confirm, firstly, the annually bimodal nature of the recession being 15 cm/month during a 4.5 month sunlit phase and 2 cm/month during the remaining 7.5 month shaded phase, and, secondly, the tendency towards an “ideal cliff orientation”, which is either south- or north-facing and about 70°-75° steep. Moreover, the hypothesis of a predefined decay period for the plateau ice is supported by this study and it is shown that terrestrial photogrammetry is not only cheap and lightweight but also very suitable for ice surveys at the decameter scale.