bluuebunny/crossref_metadata_2025 huggingface dataset:
LAND SURVEY FROM UNMANED AERIAL VEICHLE
Authors: Peterman V. , Mesarič M.
Published: August 2012

Abstract. In this paper we present, how we use a quadrocopter unmanned aerial vehicle with a camera attached to it, to do low altitude photogrammetric land survey. We use the quadrocopter to take highly overlapping photos of the area of interest. A “structure from motion” algorithm is implemented to get parameters of camera orientations and to generate a sparse point cloud representation of objects in photos. Than a patch based multi view stereo algorithm is applied to generate a dense point cloud. Ground control points are used to georeference the data. Further processing is applied to generate digital orthophoto maps, digital surface models, digital terrain models and assess volumes of various types of material. Practical examples of land survey from a UAV are presented in the paper. We explain how we used our system to monitor the reconstruction of commercial building, then how our UAV was used to assess the volume of coal supply for Ljubljana heating plant. Further example shows the usefulness of low altitude photogrammetry for documentation of archaeological excavations. In the final example we present how we used our UAV to prepare an underlay map for natural gas pipeline’s route planning. In the final analysis we conclude that low altitude photogrammetry can help bridge the gap between laser scanning and classic tachymetric survey, since it offers advantages of both techniques.
PLANIALTIMETRIC ACCURACY EVALUATION OF DIGITAL SURFACE MODEL (DSM) AND DIGITAL TERRAIN MODEL (DTM) OBTAINED FROM AERIAL SURVEY WITH LIDAR
Authors: Cruz C. B. M. , Barros R. S. , Rabaco L. M. L.
Published: August 2012

Abstract. It’s noticed a significant increase in the development of orbital and airborne sensors that enable the extraction of three-dimensional data. Consequently, it's important the increment of studies about the quality of altimetric values derived from these sensors to verify if the improvements implemented in the acquisition of data may influence the results. In this context, as part of a larger project that aims to evaluate the accuracy of various sensors, this work aims to analysis the planialtimetric accuracy of DSM and DTM generated from an aerial survey with LIDAR, using as reference for the planimetric analysis of the orthophotos obtained. The project was developed for an area of São Sebastião city, located in the basin of the North Coast of São Paulo state. The area's relief is very steep, with a predominance of dense forest vegetation, typical of the Atlantic Forest. All points have been established in the field, with the use of GNSS of one frequency (L1) through static relative positioning, acquiring a minimum of 1,500 epochs, for a distance less than 20 km to the base. In this work it's considered the Brazilian standard specifications for classification of cartographic bases (PEC). The Brazilian company responsible for the aerial survey (LACTEC) gave the following products for analysis: point clouds in raw format (x, y, z) using orthometric heights; point clouds (first and last pulse) for each range of flight to verify systematic errors; DTM uniformly spaced, filtering small natural obstacles, buildings and vegetation, in Geotiff format; DSM also uniformly spaced, in Geotiff format; and the mosaic of georeferenced digital images. The analysis realized on products from the LIDAR indicated their adoption to the scales 1:2,000 (Class A for the orthophotos and Class B for the DTM) and 1:5,000 (class C for the DSM). There were no indications of trends in the results. The average error was 0.01 m. It's important that new areas with different topographic characteristics may be evaluated to get an indication for other situations. As to the assessment of the altimetric accuracy, we are going to do more analysis with points obtained under the forest canopy in order to be able to assess the real accuracy of the DTM in areas with forest cover. Studies that focus the development of new methodologies for obtaining Digital Elevation Models (DEM) are very important, especially in large scales, seeking to generate data with cost-benefit's advantages. This way, topographic features can be obtained for wider areas of our country, meeting the needs of most studies and activities related to the representation of these kind of data.
MAPPING CROP STATUS FROM AN UNMANNED AERIAL VEHICLE FOR PRECISION AGRICULTURE APPLICATIONS
Authors: Guo T. , Kujirai T. , Watanabe T.
Published: August 2012

Abstract. Remote sensing system mounted on unmanned aerial vehicle (UAV) could provide a complementary means to the conventional satellite and aerial remote sensing solutions especially for the applications of precision agriculture. UAV remote sensing offers a great flexibility to quickly acquire field data in sufficient spatial and spectral resolution at low cost. However a major problem of UAV is the high instability due to the low-end equipments and difficult environment situation, and this leads to image sensor being mostly operated under a highly uncertain configuration. Thus UAV images exhibit considerable derivation in spatial orientation, large geometric and spectral distortion, and low signal-to-noise ratio (SNR). To achieve the objectives of agricultural mapping from UAV, we apply a micro-helicopter UAV with a multiple spectral camera mounted and develop a framework to process UAV images. A very important processing is to generate mosaic image which can be aligned with maps for later GIS integration. With appropriate geometric calibration applied, we first decompose a homography of consecutive image pairs into a rotational component and a simple perspective component, and apply a linear interpolation to the angle of the rotational component, followed by a linear matrix interpolation operator to the perspective component, and this results in an equivalent transformation but ensures a smooth evolution between two images. Lastly to demonstrate the potential of UAV images to precision agriculture application, we perform spectral processing to derive vegetation indices (VIs) maps of crop, and also show the comparison with satellite imagery. Through this paper, we demonstrate that it is highly feasible to generate quantitative mapping products such as crop stress maps from UAV images, and suggest that UAV remote sensing is very valuable for the applications of precision agriculture.
HIGH-PRECISION DEM PRODUCTION FOR SPACEBORNE STEREO SAR IMAGES BASED ON SIFT MATCHING AND REGION-BASED LEAST SQUARES MATCHING
Authors: Xiaotian S. , Guo Z. , Xia W.
Published: August 2012

Abstract. Generally, there are two ways to generate Digital Elevation Model (DEM) using synthetic aperture radar (SAR) data, which are Interferometer Synthetic Aperture Radar(InSAR) and radargrammetry. Considering the disadvantages of InSAR data, such as the limit of terrain and the influence of water content, the application field of InSAR is relatively limited, while radargrammetry is more widely applied since it does not have such limits. However, for high-precision stereo SAR imagery, since the terrain distortion caused by shooting angle cannot be eliminated and the speckle noises are obvious, the classical matching algorithms for optical stereo images do not have the same effect on SAR data. Based on the experience of optical stereo image matching, this paper proposes a new algorithm which combines the feature of SIFT image matching, region-based least squares matching and TIN . First, SIFT matching is used as the initial matching to obtain the sparse DEM, then by using TIN the matching points are forecast, finally the region-based least squares matching is adopted to get accurate matching points. In this paper, COSMO-SkyMed and TSX stereo images of Lanzhou area are used to validate the proposed method. Experiment results show that the algorithm can be effectively used in stereo SAR matching and high-precision DEM production.
PLEIADES HR IN FLIGHT GEOMETRICAL CALIBRATION : LOCATION AND MAPPING OF THE FOCAL PLANE
Authors: de Lussy F. , Greslou D. , Dechoz C. , Amberg V. , Delvit J. M. , Lebegue L. , Blanchet G. , Fourest S.
Published: August 2012

Abstract. The Pleiades system, ORFEO system optical component (Optical and Radar Federated Earth Observation) consists of a constellation of two satellites for very High Resolution panchromatic and multispectral optical observation of the Earth. Its mission is to cover all European civilian needs (mapping, tracking floods and fires) and defence in the category of metric resolution: 0.7m Nadir. The first Pleiades satellite was launched at the end of last year. One of the key objectives of the Pleiades HR (PHR) project is to achieve a location accuracy that will allow the use of images in GIS (Geographical Information System) without geometrical model improvement by refining on ground control points. The image location without refined model was specified with the precision of the most commonly used tool ie the civil GPS. So the location accuracy has been specified at less than 12m for 90% of the images on a nominal satellite configuration. Very special care has been taken all along the PHR project realization to achieve this very good location accuracy. The final touch is given during the in-orbit commissioning phase which lasts until June 2012. The geometric quality implies to tune the parameters involved in the geolocation model (geometric calibration): besides attitude and orbit restitution tuning (not considered here), it consists in estimating the biases between the instrument orientation and the AOCS reference frame, and also the sight line of each detector in the focal plane. This is called static geometrical model. The analysis of dynamic perturbations outside of the model are the second most important image quality objective of in-flight commissioning, not described in this paper. Finally “image quality assessment” consists in evaluating the image quality obtained in the final products. For geolocation model, it is quantified by the absolute geolocation and the pointing accuracies, and it is a main contributor in length alteration and planimetric and altimetric accuracies. In this paper we will present both the different practices we have adopted (their advantages, limitations and complementarities) and the means we are using for the operational assessment of the location quality of PHR images. We will focus on the innovative methods and mention the improvements in progress. To conclude, we will present the very first accuracy results assessed after PHR1A launch on L1 and Sensor products.
ATTITUDE ASSESSMENT USING PLEIADES-HR CAPABILITIES
Authors: Delevit J. M. , Greslou D. , Amberg V. , Dechoz C. , de Lussy F. , Lebegue L. , Latry C. , Artigues S. , Bernard L.
Published: August 2012

Abstract. Since SPOT1, the French national space centre (CNES) has worked on improving the geometry of Earth observation spacecrafts. The accuracy of sensor calibration is one of the main key points for any Earth observation application such as orthorectification, DEM generation or surface change detection. For the last twenty years CNES has developed two families of methods: absolute methods and relative methods. These methods are used to characterize a pushbroom acquisition along the detector line and the time line. By this way, the viewing directions are measured and the residual of the spacecraft’s attitude angles (not restituted by the Attitude and Orbit Control System) is estimated. This information can complete the geometric model of all the scenes acquired by the instrument and is used in all geometric applications. This paper presents new attitude assessment methods taking advantage of the capabilities of Pléiades-HR in terms of agility and focal plane arrangement – panchromatic band and multispectral (MS) bands.
STAR-BASED METHODS FOR PLEIADES HR COMMISSIONING
Authors: Fourest S. , Kubik P. , Lebègue L. , Déchoz C. , Lacherade S. , Blanchet G.
Published: August 2012

Abstract. PLEIADES is the highest resolution civilian earth observing system ever developed in Europe. This imagery program is conducted by the French National Space Agency, CNES. It has been operating since 2012 a first satellite PLEIADES-HR launched on 2011 December 17th, a second one should be launched by the end of the year. Each satellite is designed to provide optical 70 cm resolution colored images to civilian and defense users. Thanks to the extreme agility of the satellite, new calibration methods have been tested, based on the observation of celestial bodies, and stars in particular. It has then been made possible to perform MTF measurement, re-focusing, geometrical bias and focal plane assessment, absolute calibration, ghost images localization, micro-vibrations measurement, etc… Starting from an overview of the star acquisition process, this paper will discuss the methods and present the results obtained during the first four months of the commissioning phase.
RESTORATION TECHNIQUE FOR PLEIADES-HR PANCHROMATIC IMAGES
Authors: Latry C. , Fourest S. , Thiebaut C.
Published: August 2012

Abstract. 17th of December 2011 from Kourou Space Centre, French Guyana. Like others high resolution optical satellites, it acquires both panchromatic images, with 70cm spatial resolution, and lower resolution multispectral images with 2.8m spatial resolution. Pleiades-HR is an optimized system, which means that the Modulation Transfer Function has a low value at Nyquist frequency, in order to reduce both the telescope diameter and aliasing effects. Shannon sampling condition is thus met at first order, which also makes classical ground processing, such as image matching or resampling, more justified for a mathematical point of view. Raw images are thus blurry which implies a deconvolution stage that restores sharpness but also increases the noise level in the high frequency domain. A denoising step, based upon wavelet packet coefficients thresholding/shrinkage technique, allows controlling the final noise level. Each of these methods includes numerous parameters that have to be assessed during the inflight commissioning period: deconvolution filter that depends on MTF assessment, instrumental noise model, noise level target for denoised images, wavelet packet decomposition level. This paper aims to precisely describe the deconvolution/denoising algorithms and how their main parameters have been set up during the inflight commissioning stage. Special attention will be given to structured noise induced by Pleiades-HR on board wavelet-based compression algorithm
A PRELIMINARY STUDY ON MECHANISM OF LAI INVERSION SATURATION
Authors: Zhao J. , Li J. , Liu Q. , Yang L.
Published: August 2012

Abstract. Many parameters, such as albedo, vegetation index and leaf area index (LAI) inversed from satellite images, often get saturated when the surface vegetation cover reaches a certain high level. In order to analyze the saturation phenomena in parameter inversion, we analyze the changing of canopy reflectance and backscattering with increasing of LAI through PROSAIL and MIMICS model respectively. The results show that the canopy reflectances get saturated when LAI exceed 3, and the crown backscatters have strong relationship with biomass, which changes at various incident angles and frequencies. When LAI>3, the reflectance variations between red band and near-infrared band were no longer obvious with the vegetation growing, which directly leaded to the vegetation indices and LAI saturation. This paper is an exploratory research about the LAI saturation, and the reducing saturation methods still need further studies.
A PROCEDURE FOR THE REGISTRATION AND SEGMENTATION OF HETEROGENEOUS LIDAR DATA
Authors: Al-Durgham M. , Habib A.
Published: August 2012

Abstract. Laser scanning, whether airborne or terrestrial is being used nowadays for wide spectrum of applications. In addition, many advances have been introduced to the laser scanning technology in the last decade; thus resulting into increased performance in terms of the point density, scanner range, and expected point accuracy. On the other hand, users are encountering scenarios where the integration of various laser datasets becomes essential in order to avoid data gaps (e.g., missing building roofs in the terrestrial scans, or missing structure facades in the airborne case). This problem is usually solved seamlessly through a classical transformation when the average point accuracy is relatively homogeneous over a given dataset. However, this is not usually the case; in this work, we propose a workflow for the optimal registration of multisource point clouds using weighted conformal transformation. First, the individual scans are filtered and the local point attributes are populated through a data characterization step. Then, an ICPP-based weighted registration algorithm is performed over the entire datasets until convergence. Finally, our heterogeneous segmentation procedure is performed in a simultaneous fashion to ensure exploiting the full potential of a dataset. The performance of this algorithm in terms of correctness, automation level, and other factors is evaluated using real datasets with significant variations in point densities and accuracy.
A CACHE DESIGN METHOD FOR SPATIAL INFORMATION VISUALIZATION IN 3D REAL-TIME RENDERING ENGINE
Authors: Dai X. , Xiong H. , Zheng X.
Published: August 2012

Abstract. A well-designed cache system has positive impacts on the 3D real-time rendering engine. As the amount of visualization data getting larger, the effects become more obvious. They are the base of the 3D real-time rendering engine to smoothly browsing through the data, which is out of the core memory, or from the internet. In this article, a new kind of caches which are based on multi threads and large file are introduced. The memory cache consists of three parts, the rendering cache, the pre-rendering cache and the elimination cache. The rendering cache stores the data that is rendering in the engine; the data that is dispatched according to the position of the view point in the horizontal and vertical directions is stored in the pre-rendering cache; the data that is eliminated from the previous cache is stored in the eliminate cache and is going to write to the disk cache. Multi large files are used in the disk cache. When a disk cache file size reaches the limit length（128M is the top in the experiment), no item will be eliminated from the file, but a new large cache file will be created. If the large file number is greater than the maximum number that is pre-set, the earliest file will be deleted from the disk. In this way, only one file is opened for writing and reading, and the rest are read-only so the disk cache can be used in a high asynchronous way. The size of the large file is limited in order to map to the core memory to save loading time. Multi-thread is used to update the cache data. The threads are used to load data to the rendering cache as soon as possible for rendering, to load data to the pre-rendering cache for rendering next few frames, and to load data to the elimination cache which is not necessary for the moment. In our experiment, two threads are designed. The first thread is to organize the memory cache according to the view point, and created two threads: the adding list and the deleting list, the adding list index the data that should be loaded to the pre-rendering cache immediately, the deleting list index the data that is no longer visible in the rendering scene and should be moved to the eliminate cache; the other thread is to move the data in the memory and disk cache according to the adding and the deleting list, and create the download requests when the data is indexed in the adding but cannot be found either in memory cache or disk cache, eliminate cache data is moved to the disk cache when the adding list and deleting are empty. The cache designed as described above in our experiment shows reliable and efficient, and the data loading time and files I/O time decreased sharply, especially when the rendering data getting larger.
TRACKING VEHICLE IN GSM NETWORK TO SUPPORT INTELLIGENT TRANSPORTATION SYSTEMS
Authors: Koppanyi Z. , Lovas T. , Barsi A. , Demeter H. , Beeharee A. , Berenyi A.
Published: August 2012

Abstract. The penetration of GSM capable devices is very high, especially in Europe. To exploit the potential of turning these mobile devices into dynamic data acquisition nodes that provides valuable data for Intelligent Transportation Systems (ITS), position information is needed. The paper describes the basic operation principles of the GSM system and provides an overview on the existing methods for deriving location data in the network. A novel positioning solution is presented that rely on handover (HO) zone measurements; the zone geometry properties are also discussed. A new concept of HO zone sequence recognition is introduced that involves application of Probabilistic Deterministic Finite State Automata (PDFA). Both the potential commercial applications and the use of the derived position data in ITS is discussed for tracking vehicles and monitoring traffic flow. As a practical cutting edge example, the integration possibility of the technology in the SafeTRIP platform (developed in an EC FP7 project) is presented.
Critical Metadata Protocols in Hyperspectral Field Campaigns for Building Robust Hyperspectral Datasets
Authors: Rasaiah B. , Jones S. D. , Malthus T. J. , Bellman C.
Published: August 2012

Abstract. Field spectroscopic metadata is a central component in the quality and reliability of hyperspectral data and the products derived from it. The impact of the quantity and format of metadata created at this fundamental stage of hyperspectral research is amplified as hyperspectral data exchange becomes prolific in the international remote sensing community. Cataloguing, mining, and interoperability of these datasets rely upon the robustness of metadata protocols for field spectroscopy. Currently no standardized methodology for collecting in situ spectroscopy data or metadata protocols exist. This paper presents initial results of an international expert panel survey investigating metadata protocols in field spectroscopy. Field measurement methods, data representativeness and their expression as metadata entities are examined across a range of campaigns. Consensus between expert groups and variance in agreement on criticality are also investigated. The survey is part of a doctoral research project to investigate approaches to a coordinated evolution of hyperspectral metadata protocols, field spectroscopic methods and data exchange standards within the hyperspectral remote sensing community.
MULTISCALE AND MULTITEMPORAL URBAN REMOTE SENSING
Authors: Mesev V.
Published: August 2012

Abstract. The remote sensing of urban areas has received much attention from scientists conducting studies on measuring sprawl, congestion, pollution, poverty, and environmental encroachment. Yet much of the research is case and data-specific where results are greatly influenced by prevailing local conditions. There seems to be a lack of epistemological links between remote sensing and conventional theoretical urban geography; in other words, an oversight for the appreciation of how urban theory fuels urban change and how urban change is measured by remotely sensed data. This paper explores basic urban theories such as centrality, mobility, materiality, nature, public space, consumption, segregation and exclusion, and how they can be measured by remote sensing sources. In particular, the link between structure (tangible objects) and function (intangible or immaterial behavior) is addressed as the theory that supports the wellknow contrast between land cover and land use classification from remotely sensed data. The paper then couches these urban theories and contributions from urban remote sensing within two analytical fields. The first is the search for an "appropriate" spatial scale of analysis, which is conveniently divided between micro and macro urban remote sensing for measuring urban structure, understanding urban processes, and perhaps contributions to urban theory at a variety of scales of analysis. The second is on the existence of a temporal lag between materiality of urban objects and the planning process that approved their construction, specifically how time-dependence in urban structural-functional models produce temporal lags that alter the causal links between societal and political functional demands and structural ramifications.
A COMPARISON OF SEMANTIC SIMILARITY MODELS IN EVALUATING CONCEPT SIMILARITY
Authors: Xu Q. X. , Shi W. Z.
Published: August 2012

Abstract. The semantic similarities are important in concept definition, recognition, categorization, interpretation, and integration. Many semantic similarity models have been established to evaluate semantic similarities of objects or/and concepts. To find out the suitability and performance of different models in evaluating concept similarities, we make a comparison of four main types of models in this paper: the geometric model, the feature model, the network model, and the transformational model. Fundamental principles and main characteristics of these models are introduced and compared firstly. Land use and land cover concepts of NLCD92 are employed as examples in the case study. The results demonstrate that correlations between these models are very high for a possible reason that all these models are designed to simulate the similarity judgement of human mind.
CARDINAL DIRECTION RELATIONS QUERY MODELING BASED ON GEO-ONTOLOGY
Authors: Zhu X. , Chen D. , Zhou C. , Li M. , Xiao W.
Published: August 2012

Abstract. Direction relations, as an important spatial relationship, is simply expressed as object prosperity in traditional geo-ontology. The lacking of explicit specifications and reasoning rules of direction relations in geo-ontology result in the difficult or inflexible of spatial reasoning. Also, digital gazetteers provide information on named features, linking the feature's name with its location and its type. Although the location information is incomplete and not exact, the implicit spatial information, for example spatial relationships and spatial scale, can be extract using the appropriate models based on geo-ontology. In this paper, we proposed a novel conceptual framework of direction relations in order to formalize the semantics and implicit information of direction relations, and present an extraction algorithm of implicit information based on previous researches, which will produce a complete query instance of direction relations. At last, the most suitable direction physical model is recommended to calculation module according to relevant rules. And the experimental results show that this direction query model not only extracted the implicit information effectively, but also made a reasonable interpretation for the user's intention.
DELAUNAY TRIANGULATION PARALLEL CONSTRUCTION METHOD AND ITS APPLICATION IN MAP GENERALIZATION
Authors: Shen J. , Guo L. , Qi L. , Zhu W.
Published: August 2012

Abstract. Delaunay triangulated irregular network (D-TIN) has been widely used in various fields and also played an increasingly important role on map generalization. But for massive data processing, current D-TIN algorithm is still not efficient enough to meet the requirements of map generalization. Data partitioning is an important step of parallel algorithm design. The load balance and efficiency of data partitioning is the precondition of improving parallel algorithm efficiency. For aggregated distributed point sets, the traditional Delaunay Triangulation parallel algorithm can’t ensure the balance and the execution’s efficiency of the partitioning result. The paper introduces a partitioning method using dynamic strips aiming to guarantee the computing load balance. We tested the speed-up of the D-TIN parallel algorithm using different type of point sets and the results of the experiments shows that the method of dynamic strips partitioning can help to get high and stable speed-up and the data distributional pattern and size has less influence to it. The paper realizes a mesh simplification algorithm based on parallel D-TIN and compares the efficiency based on parallel and serial D-TIN.
A STUDY OF VARIABLES CHARACTERIZING DRAINAGE PATTERNS IN RIVER NETWORKS
Authors: Zhang L. , Guilbert E.
Published: August 2012

Abstract. In GIS and in terrain analysis, drainage systems are important components. Due to local topography and subsurface geology, a drainage system achieves a particular drainage pattern based on the form and texture of its network of stream channels and tributaries. Drainage pattern recognition helps to provide a qualitative description of the terrain for analysis and classification and is useful for terrain modelling and visualization and applications in environment. Much research has been done on the description of drainage patterns in geography and hydrology. However automatic drainage pattern recognition in river networks is not well developed. This paper introduces a method based on geometric quantitative indicators to recognize drainage patterns in a river network automatically. Experiment results are presented and discussed.
FOREST DISTURBANCE LEADS TO THE RAPID SPREAD OF THE INVASIVE LEUCAENA LEUCOCEPHALA IN TAIWAN
Authors: Chen J. C. , Chen C. T. , Jump A. S.
Published: August 2012

Abstract. This study, based on different investigative documents and analytical methods, elucidates spatial distribution of habitats for major invasive exotic plants, Leucaena leucocephala, in Taiwan. Results show that Leucaena leucocephala is most harmful to broad-leaved trees and its invasion directly relates to changes in the physical environment. Leucaena leucocephala can bloom and bear fruits all year round and during the period of seeds sprouting and saplings, the invasion varies greatly among different soil types. Leucaena leucocephala prefers weakly acidic soil, though it grows well with other soil textures and nutrients as well. The average spreading rate of Leucaena leucocephala is 3.55 ha year−1 on abandoned farm land calculated from the aerial photographs taken in 1982, 1992, 2003, and 2007.
SPACE-TIME ANALYSIS OF CRIME PATTERNS IN CENTRAL LONDON
Authors: Cheng T. , Williams D.
Published: August 2012

Abstract. Crime continues to cast a shadow over citizen well-being in big cities today, while also imposing huge economic and social costs. Timely understanding of how criminality emerges and how crime patterns evolve is crucial to anticipating crime, dealing with it when it occurs and developing public confidence in the police service. Every day, about 10,000 crime incidents are reported by citizens, recorded and geo-referenced in the London Metropolitan Police Service Computer Aided Dispatch (CAD) database. The unique nature of this dataset allows the patterns to be explored at particularly fine temporal granularity and at multiple spatial resolutions. This study provides a framework for the exploratory spatio-temporal analysis of crime patterns that combines visual inquiry tools (interactive animations, space-time cubes and map matrices) with cluster analysis (spatial-temporal scan statistics and the self-organizing map). This framework is tested on the CAD dataset for the London Borough of Camden in March 2010. Patterns of crime through space and time are discovered and the clustering methods were evaluated on their ability to facilitate the discovery and interpretation of these patterns.
ANALYSIS OF THE RELATIONSHIP BETWEEN INTRA-URBAN VEGETATION CHANGE AND SOCIO-ECONOMIC DATA
Authors: Fonseca L. M. G. , Boggione G. A. , Monteiro A. M. V. , Santos R.
Published: August 2012

Abstract. Understanding the vegetation dynamics in urban areas in both quantitative and qualitative aspects is essential to population welfare and also to economic, social and environmental development. However, it is necessary appropriate tools for monitoring and analysis of the landscape dynamic in a systematic way. Therefore, this study proposes a methodology to analyze the relationship between intra-urban vegetation and the social-economic data using the integrated techniques of remote sensing and GIS as well as data mining. This research intends to answer questions such as: Is it possible to extract the intra-urban vegetation as well as identify the intra-urban vegetation changes from medium spatial resolution images and digital image processing techniques? Is it possible to establish a relationship between the intra-urban vegetation changes and social-economic information using data mining techniques?
GIS-BASED SPATIAL STATISTICAL ANALYSIS OF COLLEGE GRADUATES EMPLOYMENT
Authors: Tang R.
Published: August 2012

Abstract. It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004–2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.
PLANAR PROJECTION OF MOBILE LASER SCANNING DATA IN TUNNELS
Authors: Gonçalves J. A. , Mendes R. , Araújo E. , Oliveira A. , Boavida J.
Published: August 2012

Abstract. Laser scanning is now a common technology in the surveying and monitoring of large engineering infrastructures, such as tunnels, both in motorways and railways. Extended possibilities exist now with the mobile terrestrial laser scanning systems, which produce very large data sets that need efficient processing techniques in order to facilitate their exploitation and usability. This paper deals with the implementation of a methodology for processing and presenting 3D point clouds acquired by laser scanning in tunnels, making use of the approximately cylindrical shape of tunnels. There is a need for a 2D presentation of the 3D point clouds, in order to facilitate the inspection of important features as well as to easily obtain their spatial location. An algorithm was developed to treat automatically point clouds obtained in tunnels in order to produce rectified images that can be analysed. Tests were carried with data acquired with static and mobile Riegl laser scanning systems, by Artescan company, in highway tunnels in Portugal and Spain, with very satisfactory results. The final planar image is an alternative way of data presentation where image analysis tools can be used to analyze the laser intensity in order to detect problems in the tunnel structure.
AUTOMATED RECONSTRUCTION OF WALLS FROM AIRBORNE LIDAR DATA FOR COMPLETE 3D BUILDING MODELLING
Authors: He Y. , Zhang C. , Awrangjeb M. , Fraser C. S.
Published: August 2012

Abstract. Automated 3D building model generation continues to attract research interests in photogrammetry and computer vision. Airborne Light Detection and Ranging (LIDAR) data with increasing point density and accuracy has been recognized as a valuable source for automated 3D building reconstruction. While considerable achievements have been made in roof extraction, limited research has been carried out in modelling and reconstruction of walls, which constitute important components of a full building model. Low point density and irregular point distribution of LIDAR observations on vertical walls render this task complex. This paper develops a novel approach for wall reconstruction from airborne LIDAR data. The developed method commences with point cloud segmentation using a region growing approach. Seed points for planar segments are selected through principle component analysis, and points in the neighbourhood are collected and examined to form planar segments. Afterwards, segment-based classification is performed to identify roofs, walls and planar ground surfaces. For walls with sparse LIDAR observations, a search is conducted in the neighbourhood of each individual roof segment to collect wall points, and the walls are then reconstructed using geometrical and topological constraints. Finally, walls which were not illuminated by the LIDAR sensor are determined via both reconstructed roof data and neighbouring walls. This leads to the generation of topologically consistent and geometrically accurate and complete 3D building models. Experiments have been conducted in two test sites in the Netherlands and Australia to evaluate the performance of the proposed method. Results show that planar segments can be reliably extracted in the two reported test sites, which have different point density, and the building walls can be correctly reconstructed if the walls are illuminated by the LIDAR sensor.
HIERARCHICAL ALGORITHM IN DTM GENERATION AND AUTOMATIC EXTRACTION OF ROAD FROM LIDAR DATA
Authors: Hui-ying L. , Yu-jun X. , Zhi W. , Yi-nan L.
Published: August 2012

Abstract. Growing demand for an efficient land use above and below the ground is motivating cadastre and land management systems to move from traditional 2D systems toward three dimensional ones. Airborne laser technology offers direct acquisition of dense and accurate 3D data. In order to get 3D road this paper proposes a hierarchical algorithm to extract terrain point from LIDAR data. We stratify the raw LiDAR data according to the height, judge terrain points and non-terrain points by the connectivity. In the case of road network, it indicates the morphological characteristics of network structure with a certain length continuous strip and small difference in intensity. All these information, including elevation information, the intensity information, the morphological characteristics and other local features, are used for extracting the road network from DTM. Local morphological filtering method is implementing for finding clear boundaries and rich details of the road profile. Following the presentation of the algorithm results for this approach are shown and evaluated
STRUCTURE LINE DETECTION FROM LIDAR POINT CLOUDS USING TOPOLOGICAL ELEVATION ANALYSIS
Authors: Lo C. Y. , Chen L. C.
Published: August 2012

Abstract. Airborne LIDAR point clouds, which have considerable points on object surfaces, are essential to building modeling. In the last two decades, studies have developed different approaches to identify structure lines using two main approaches, data-driven and modeldriven. These studies have shown that automatic modeling processes depend on certain considerations, such as used thresholds, initial value, designed formulas, and predefined cues. Following the development of laser scanning systems, scanning rates have increased and can provide point clouds with higher point density. Therefore, this study proposes using topological elevation analysis (TEA) to detect structure lines instead of threshold-dependent concepts and predefined constraints. This analysis contains two parts: data pre-processing and structure line detection. To preserve the original elevation information, a pseudo-grid for generating digital surface models is produced during the first part. The highest point in each grid is set as the elevation value, and its original threedimensional position is preserved. In the second part, using TEA, the structure lines are identified based on the topology of local elevation changes in two directions. Because structure lines can contain certain geometric properties, their locations have small relieves in the radial direction and steep elevation changes in the circular direction. Following the proposed approach, TEA can be used to determine 3D line information without selecting thresholds. For validation, the TEA results are compared with those of the region growing approach. The results indicate that the proposed method can produce structure lines using dense point clouds.
MIN-CUT BASED SEGMENTATION OF AIRBORNE LIDAR POINT CLOUDS
Authors: Ural S. , Shan J.
Published: August 2012

Abstract. Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance parameter does not strongly conform to the natural structure of the points. Including shape information within the energy function by assigning costs based on the local properties may help to achieve a better representation for segmentation.
A MULTI-SENSOR APPROACH TO SEMI-GLOBAL MATCHING
Authors: Gehrke S. , Downey M. , Uebbing R. , Welter J. , LaRocque W.
Published: August 2012

Abstract. After we first presented the Semi-Global Matching (SGM) implementation for Leica ADS line-scanner data, the interest in applying this surface extraction to aerial frame imagery has increased. The reason is the combination of high-resolution geometry and multi-spectral information in the resulting point clouds. Such comprehensive point clouds or, more generic, information clouds (info clouds) allow for many different uses of the data, including applications that make currently use of LiDAR. The DSM extraction tool for the ADS is based on SGM, which enables the derivation of disparity maps and eventually point clouds at the very image resolution. This approach was now extended to support both frame sensors and line-scanners in order to provide an integrated workflow for different sensor types. This paper describes how SGM is used in a sensor-agnostic system, based on few specific pre- and post-processing steps, within the DSM extraction tool we developed. Results from the ADS line-scanner as well as from DMC-II and RCD30 frame data are presented.
A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA
Authors: Zhou M. , Tang L.-L. , Li C.-R. , Peng Z. , Li J.-M.
Published: August 2012

Abstract. LiDAR is capable of obtaining three dimension coordinates of the terrain and targets directly and is widely applied in digital city, emergent disaster mitigation and environment monitoring. Especially because of its ability of penetrating the low density vegetation and canopy, LiDAR technique has superior advantages in hidden and camouflaged targets detection and recognition. Based on the multi-echo data of LiDAR, and combining the invariant moment theory, this paper presents a recognition method for classic airplanes (even hidden targets mainly under the cover of canopy) using KD-Tree segmented point cloud data. The proposed algorithm firstly uses KD-tree to organize and manage point cloud data, and makes use of the clustering method to segment objects, and then the prior knowledge and invariant recognition moment are utilized to recognise airplanes. The outcomes of this test verified the practicality and feasibility of the method derived in this paper. And these could be applied in target measuring and modelling of subsequent data processing.
IMAGE FUSION APPLIED TO SATELLITE IMAGERY FOR THE IMPROVED MAPPING AND MONITORING OF CORAL REEFS: A PROPOSAL
Authors: Gholoum M. , Bruce D. , Al Hazeam S.
Published: August 2012

Abstract. A coral reef ecosystem, one of the most complex marine environmental systems on the planet, is defined as biologically diverse and immense. It plays an important role in maintaining a vast biological diversity for future generations and functions as an essential spawning, nursery, breeding and feeding ground for many kinds of marine species. In addition, coral reef ecosystems provide valuable benefits such as fisheries, ecological goods and services and recreational activities to many communities. However, this valuable resource is highly threatened by a number of environmental changes and anthropogenic impacts that can lead to reduced coral growth and production, mass coral mortality and loss of coral diversity. With the growth of these threats on coral reef ecosystems, there is a strong management need for mapping and monitoring of coral reef ecosystems. Remote sensing technology can be a valuable tool for mapping and monitoring of these ecosystems. However, the diversity and complexity of coral reef ecosystems, the resolution capabilities of satellite sensors and the low reflectivity of shallow water increases the difficulties to identify and classify its features. This paper reviews the methods used in mapping and monitoring coral reef ecosystems. In addition, this paper proposes improved methods for mapping and monitoring coral reef ecosystems based on image fusion techniques. This image fusion techniques will be applied to satellite images exhibiting high spatial and low to medium spectral resolution with images exhibiting low spatial and high spectral resolution. Furthermore, a new method will be developed to fuse hyperspectral imagery with multispectral imagery. The fused image will have a large number of spectral bands and it will have all pairs of corresponding spatial objects. This will potentially help to accurately classify the image data. Accuracy assessment use ground truth will be performed for the selected methods to determine the quality of the information derived from image classification. The research will be applied to the Kuwait's southern coral reefs: Kubbar and Um Al-Maradim.