This research investigates the capability of the multitemporal RADARSAT Fine-Beam C-HH SAR imagery for landuse/land-cover mapping and change detection in therural-urban fringe of the Greater Toronto Area (GTA). Five-date RADARSAT fine-beamSAR images were acquired during May to August in 2002. One scene of Landsat TM imagery was acquired in 1988 for change detection. The major landuse/land-coverclasses were high-density built-up areas, low-density built-up areas, roads, forests, parks, golf courses, water and three types of agricultural lands. These ten classes were chosen to characterize the complex landuse/land-cover types in the rural-urban fringe of the GTA. The results demonstrated that, for identifying landuse/land-cover classes, five-date raw SAR imagery yielded very poor result due to speckles. Much better results were achieved with combined Mean, Standard Deviation and Correlation texture images using artificial neural networks (ANN) and with raw images using object-based classification. The change detection procedure was able to identify the areas of significant changes, for example, major new roads, new low-density and high-density built up areas and golf courses, even though the overall accuracy of the change detection was rather low. 

The objective of this research is to evaluate multitemporal RADARSAT Fine-Beam C-HH SAR data, QuickBird MS data, and fusion of SAR and MS for urban land-cover mapping and change detection One scene of QuickBird imagery was acquired on July 18, 2002 and five-date RADARSAT fine-beam SAR images were acquired during May to August in 2002. Landsat TM imagery from 1988 was used for change detection. QucikBird images were classified using an object-based and rule-based approach. RADARSAR SAR texture images were classified using a hybrid approach. The results demonstrated that, for identifying 19 land-cover classes, object-based and rule-based classification of Quickbird data yielded an overall classification accuracy of 86.7% (kappa 0.857). For identifying I I land-cover classes, ANN classification of the combined Mean, Standard Deviation and Correlation texture images yielded an overall accuracy: 71.4%, (Kappa: 0.69). The hybrid classification of RADARSAT fine-beam SAR data improved the ANN classification accuracy to 83.56% (kappa: 0.803). Decision level fusion of RADARSAT SAR and QuickBird data improved the classification accuracy of several land cover classes. The post-classification change detection was able to identify the areas of significant change, for example, major new roads, new low-density and high-density, builtup areas and golf courses, even though the change detection results contained large amount of noise due to classification errors of individual images. QuickBrid classification result was able add detailed change information to the major changes identified.

The objective of this research is to evaluate Quickbird multi-spectral (MS) data, multi-temporal RADARSAT Fine-Beam C-HH synthetic aperture radar (SAR) data and fusion of Quickbird MS and RADARSAT SAR for urban land-use/land-cover mapping. One scene of Quickbird multi-spectral imagery was acquired on 18 July 2002 and five-date RADARSAT fine-beam SAR images were acquired during May to August 2002. Quickbird MS images and RADARSAT SAR data were classified using an object-based and rule-based approach. The results demonstrated that the object-based and knowledge-based approach was effective in extracting urban land-cover classes. For identifying 16 land-cover classes, object-based and rule-based classification of Quickbird MS data yielded an overall classification accuracy of 87.9% (kappa: 0.868). For identifying 11 land-cover classes, object-based and rule-based classification of RADARSAT SAR data yielded an overall accuracy: 86.6% (kappa: 0.852). Decision level fusion of Quickbird classification and RADARSAT SAR classification was able to take advantage of the best classifications of both optical and SAR data, thus significantly improving the classification accuracies of several land-cover classes (25% for pasture, 19% for soybeans, 17% for rapeseeds) even though the overall classification accuracy of 16 land-cover classes increased only slightly to 89.5% (kappa: 0.885).

This paper gives an overview of several aspects of visualization for city planning as they were used in the projectViSuCity. The overall objective of ViSuCity is to develop an effective web-based, interactive visualization demonstrator,ViSuCity, to support sustainable city planning in terms of information sharing, analysis, development,presentation and communication of ideas and proposals throughout the city planning processes. In this paper, wediscuss and show some results regarding LOD, scalability, streaming, and examples of visualization of roads, etcthat are important for city planning.

This research investigates multitemporal dual-orbit RADARSAT-2 polarimetric SAR data for urban land cover classification using an object-based support vector machine (SVM). Six-date RADARSAT-2 high-resolution SAR data in both ascending and descending orbits were acquired in the rural-urban fringe of the Greater Toronto Area during the summer of 2008. The major landuse/land-cover classes include high-density residential area, low-density residential area, industrial and commercial area, construction site, park, golf course, forest, pasture, water and two types of agricultural crops. The results show that multitemporal SAR data improve urban land cover classification and the best classification result is achieved using data from all six-dates. However, similar accuracies could be achieved using only three-date data from both ascending and descending orbits with relatively longer temporal span. Combinations of SAR data with relatively short temporal span are observed to yield lower classification accuracy. Similarly, combinations of SAR data from either ascending or descending orbit alone yield lower accuracy than the combinations of ascending and descending data. The results indicate that the combination of both the ascending and descending spaceborne SAR data with appropriate temporal span are suitable for urban land cover mapping.

This research investigates the capability of the multitemporal RADARSAT Fine-Beam C-HH SAR imagery for extracting landuse/land-cover information in the rural-urban fringe of the Greater Toronto Area (GTA) using various image processing techniques and classification algorithms. Five-date RADARSAT fine-beam SAR images were acquired during May to August in 2002. The major landuse/land-cover classes were high-density built-up areas, low-density built-up areas, roads, forests, parks, golf courses, water and three types of agricultural lands. These ten classes were chosen to characterize the complex landuse/land-cover types in the rural-urban fringe of the GTA. The results demonstrated that, for identifying landuse/land-cover classes, five-date raw SAR imagery yielded very poor result due to speckles. The best result was achieved for combined Mean, Standard Deviation and Correlation texture images using artificial neural networks (ANN) (overall accuracy: 89.7% and Kappa: 0.886). These high accuracies indicated that RADARSAT fine-beam SAR has the potential for operational landuse/land-cover mapping in urban environments.

The objective of this research is to investigate multitemporal spaceborne SAR data for urbanization monitoring in China. A generalized version of Kittler- Illingworth minimum-error thresholding algorithm, that takes into account the non-Gaussian distribution of SAR images, was tested to automatically classify the change variable derived from SAR multitemporal images into two classes, change and no change. A modified ratio operator was examined for identifying both positive and negative changes by comparing the multitemporal SAR images on a pixel-by-pixel basis. Various probability density functions such as Log normal, Generalized Gaussian, Nakagami ratio, and Weibull ratio models were tested to model the distribution of the change and no change classes. The preliminary results showed that this unsupervised change detection algorithm is very effective in detecting temporal changes in urban areas using multitemporal SAR images. The initial findings indicated that change detection accuracy varies depending on how the assumed conditional class density function fits the histograms of change and no change classes.

The objective of this research is to examine unsupervised change detection methods using multitemporal spaceborne SAR data for urbanization monitoring in Beijing. One scene of ENVISAT ASAR C-VV image was acquired in July, 2008 and one scene of ERS-2 SAR C-VV image was acquired in July, 1998. To compare the two SAR images, a modified ratio operator that takes into account both positive and negative changes was developed to derive a change image. A generalized version of Kittler-Illingworth minimum-error thresholding algorithm was then tested to automatically classify the change image into two classes, change and no-change. Various probability density functions such as Log normal, Generalized Gaussian, Nakagami ratio, and Weibull ratio were investigated to model the distribution of the change and no-change classes. The preliminary results showed that Kittler-Illingworth algorithm applied to the modified ratio image is very effective in detecting temporal changes in urban areas using SAR images. Log normal and Nakagami density models achieved the best results. The Kappa coefficients of the these solutions were of 0.82 while the false alarm rates were 2.7%. The initial findings indicated that the accuracy of the change result obtained using Kittler-Illingworth algorithm varies depending on how the assumed conditional class density function fits the histograms of change and no-change classes.

Service composition with Quality of Service (QoS) is widely studied nowadays and there are some approaches effective for the composition problem in ideal conditions but no feasible solution for dynamic and uncertain QoS constraints environment. Therefore, a novel service negotiation mechanism is proposed in this paper. The mechanism is composed by three parts for negotiation: model, protocol and strategy. The model creates a new hierarchy architecture based on negotiation agent to improve the efficiency of tasks execution of each agent. The protocol dynamically updates solution search line, on which proposals are made by trading partners, and approximate Pareto-optimal solution is achieved through the neutral mediator. The strategy enhances the negotiation sensibility by considering three factors: time, opponent actions and global negotiation states. The negotiation process is coordinated by Manger Agent (MA), which provides suggestions for the next negotiation round based on the overall negotiation context. Experimental results show that the proposed approach is effective to find a feasible solution in the dynamically changeable composition environment.

With the development of Web Service, it has become a key issue to select appropriate services from a large number of candidates for creating complex composite services according to users' different QoS levels requirements. However, the existing service selection algorithms have many defects such as high time complexity, non-global optimal solutions, and poor quality solutions. To solve these defects, an efficient multi-objective services selection algorithm, EMOSS, is proposed in this paper based on particle swarm optimization. The essence of EMOSS is to model the service selection problem as a constrained multi-objective optimization problem. First the services in each sub-service set are sorted by their concept of domination, then the new sub-service set nSi , whose size is far less than the original one, is constructed and finally output pareto optimal set. The theoretical analysis and experimental results show that EMOSS can effectively obtain high quality solutions.

A phishing detection system, which comprises client-side filtering plug-in, analysis center and protected sites, is proposed. An image-based similarity detection algorithm is conceived to calculate the similarity of two web pages. The web pages are first converted into images, and then divided into sub-images with iterated dividing and shrinking. After that, the attributes of sub-images including color histograms, gray histograms and size parameters are computed to construct the attributed relational graph (ARG) of each page. In order to match two ARGs, the inner earth mover's distances (EMD) between every two nodes coming from each ARG respectively are first computed, and then the similarity of web pages by the outer EMD between two ARGs is worked out to detect phishing web pages. The experimental results show that the proposed architecture and algorithm has good robustness along with scalability, and can effectively detect phishing.

In web service computing, a business transaction is integrated by web services provided by multiple enterprises, therefore the transaction is deployed in a loose-coupled, heterogeneous and autonomous environment. When failures or exceptions occur, the traditional rolling back technique is inappropriate for recovery since locking is inapplicable. Current solutions, including forward recovery and backward recovery, didn't take into consideration enough business logic of the business transaction and thus were lack of flexibility and efficiency. In this paper, we introduce the conception-constraint rule, which express the business logic of a business transaction. A better control of recovery is achieved based on the constraint rules. A detailed description of our algorithms for recovery is given and a travel agency case study is illustrated. In addition, we compare our recovery mechanism with some existing solutions and the simulation results show that our method has both better success rate and efficiency.

Radon is radioactive and its origin in groundwater is principally linked to the content of its parent element, uranium or radium in bedrocks. However, an on-going research at the Department of Land andWater Resources Engineering shows that a number of factors other than bedrock may potentially influence the radon concentration in groundwater.These factors include: steepness of the terrain, soil type, distribution of uranium and the effect of fracture zone. This article presents an application of GIS and 3D visualisation to explore the radon problem in groundwater. After a GIS pre-processing, 3D visualisations of the thematic data were produced in order to see if the visual approach would be useful to preliminary identify possible relationships between the high concentration of radon and other parameters.

This paper presents a joined formal and exploratory usability evaluation of a geovisualization tool for emergency response data. The first objective of the evaluation, which is addressed by a formal usability test, is to evaluate the performance of the test participants on pre-defined exploration tasks. The second objective is to attempt to better understand how the participants explore the spatial dataset. This objective is addressed in the exploratory usability part of the experiment, where participants are given free hand to perform exploration in any way they want. The study introduces a low-cost methodology for performing usability evaluation, which uses simple and inexpensive methods for data collection and analysis, yet proves to be adequate to identify potentials and problems of the tool.

Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting this information and knowledge is data mining. Knowledge discovery is performed by applying automatic algorithms which recognise patterns in the data.

Classical data mining algorithms assume that data are independently generated and identically distributed. Geospatial data are multidimensional, spatially autocorrelated and heterogeneous. These properties make classical data mining algorithms inappropriate for geospatial data, as their basic assumptions cease to be valid. Extracting knowledge from geospatial data therefore requires special approaches. One way to do that is to use visual data mining, where the data is presented in visual form for a human to perform the pattern recognition. When visual mining is applied to geospatial data, it is part of the discipline called exploratory geovisualisation.

Both automatic and visual data mining have their respective advantages. Computers can treat large amounts of data much faster than humans, while humans are able to recognise objects and visually explore data much more effectively than computers. A combination of visual and automatic data mining draws together human cognitive skills and computer efficiency and permits faster and more efficient knowledge discovery.

This thesis investigates if a combination of visual and automatic data mining is useful for exploration of geospatial data. Three case studies illustrate three different combinations of methods. Hierarchical clustering is combined with visual data mining for exploration of geographical metadata in the first case study. The second case study presents an attempt to explore an environmental dataset by a combination of visual mining and a Self-Organising Map. Spatial pre-processing and visual data mining methods were used in the third case study for emergency response data.

Contemporary system design methods involve user participation at all stages. These methods originated in the field of Human-Computer Interaction, but have been adapted for the geovisualisation issues related to spatial problem solving. Attention to user-centred design was present in all three case studies, but the principles were fully followed only for the third case study, where a usability assessment was performed using a combination of a formal evaluation and exploratory usability.

Efficiently exploring a large spatial dataset with the aim of forming a hypothesisis one of the main challenges for information science. This studypresents a method for exploring spatial data with a combination of spatialand visual data mining. Spatial relationships are modeled during a datapre-processing step, consisting of the density analysis and vertical viewapproach, after which an exploration with visual data mining follows. The method has been tried on emergency response data about fire and rescueincidents in Helsinki.

The location of rail station and route planning for new railways in a country constitutecomplicated planning processes which involve the consideration and analysis of various datasets. It includes the evaluation of socio-economic and technical parameters to minimizeenvironmental impacts of different alternatives and to achieve the development of alternativestation and corridors for the planned rail networks link. In Kyrgyzstan, these tasks areimplemented using traditional manual routines that the choice of a location rail station andselection of corridor for new railways are based on the topography of the land.The use of modern technological tools like Geographic Information System (GIS) forsuitable location of rail stations and selection of optimum routes involves managing a varietyof data sets from different sources and at different scales. This work is intended to investigateand show the capabilities of GIS in railroad planning and station location processes using partof the China-Kyrgyzstan-Uzbekistan railway in the south of Kyrgyzstan as a case study.The study will identify the information needs of different factors and evaluationcriteria for locating station and railroad planning. To achieve these objectives spatialmulticriteria decision making (MCDM) processes for planning the rail station and the routeswere designed and developed using GIS.The relative importance of the parameters in rail station location and rail routeselection has been determined in cooperation with rail experts. The obtained scores were usedin pairwise comparison to determine the weight of factors/criteria maps related to theseparameters. These weighted factors/criteria maps were overlaid and suitability maps werecreated in GIS for rail station location and rail route selection. The Weighted linearcombination (WLC) and The Analytical Hierarchy Process (AHP) were used to derive thesesuitability maps.

This article investigates if higher levels of social capital, better governance structures, and a more ambitious conservation policy are positively linked to the ability of states to address biodiversity loss. Serving this purpose is a data set containing estimates of woodpecker diversity in 20 European countries. These data are argued to be a more valid indicator of biodiversity than most other available cross-national measures of environmental quality. A seemingly unrelated regression analysis reveals that none of the indicators are linked to higher levels of woodpecker diversity, which in turn leads to the conclusion that present institutions, environmental policies, and social structures have negligible effects on biodiversity compared to long-term landscape transformations.

3D geoinformation has become a base for an increasing number of today’s applications. Examples of these applications are: city and urban planning, real estate management, environmental simulation, crisis and disaster management, telecommunication, facility management and others. 3D city models are presently scattered over different public and private sectors in different systems, different conceptual models, different data formats, different data schemas, different levels of detail and different quality. In addition, the potential of 3D models goes beyond visualisation of 3D objects of virtual scenes to real 3D city models. In such an environment, integration of different sources of data for building real 3D city models becomes more difficult.

3D city models are of two types, design and real world models. Design models are usually used for building industry purposes and to fulfil the requirements of maximum level of detail in the architecture, engineering and construction (AEC) industry. Real world models are geospatial information systems that represent spatial objects around us and are largely represented in GIS applications. Research efforts in the AEC industry resulted in Building Information Modelling (BIM), a process that supports information management throughout buildings’ lifecycle and is increasingly widely used in the AEC industry. Results of different integration efforts of BIM and geospatial models show that only 3D geometric information does not fulfil the integration purpose and may lead to geometrical inconsistency. Further complex semantic information is required. Therefore, this thesis focuses on the integration of the two most prominent semantic models for the representation of BIM and geospatial objects, Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML), respectively.

In the integration of IFC and CityGML building models, substantial difficulties may arise in translating information from one to the other. Professionals from both domains have made significant attempts to integrate CityGML and IFC models to produce useful common applications. Most of these attempts, however, use a unidirectional method (mostly from IFC to CityGML) for the conversion process. A bidirectional method can lead to development of unified applications in the areas of urban planning, building construction analysis, homeland security, etc. The benefits of these unified applications clearly appear at the operational level (e.g. cost reduction, unified data-view), and at the strategic level (e.g. crisis management and increased analysis capabilities).

For a bidirectional method, a formal mapping between both domains is required. Researchers have suggested that harmonising semantics is currently the best approach for integration of IFC and CityGML. In this thesis, the focus is therefore on semantic integration of IFC and CityGML building models for bidirectional conversion. IFC and CityGML use different terminologies to describe the same domain and there is a great heterogeneity in their semantics. Following a design research method, the thesis proposes a more expressive reference ontology between IFC and CityGML semantic models. Furthermore, an intermediate unified building model (UBM) is proposed between IFC and CityGML that facilitates the transfer of spatial information from IFC to CityGML and vice versa. A unified model in the current study is defined as a superset model that is extended to contain all the features and objects from both IFC and CityGML building models. The conversion is a two-steps process in which a model is first converted to the unified model and then to the target model.

The result of the thesis contributes, through the reference ontology, towards a formal mapping between IFC and CityGML ontologies that allows bidirectional conversion between them. Future development of the reference ontology may be seen as the design of a meta-standard for 3D city modelling that can support applications in both domains. Furthermore, the thesis also provides an approach towards a complete integration of CityGML and IFC through the development of the UBM. The latter contribution demonstrates how different classes, attributes and relations have been considered from IFC and CityGML in the building of the UBM.

To illustrate the applicability of the proposed approach, a hospital building located in Norrtälje City, north of Stockholm, Sweden, is used as a case study. The purpose of the case study is to show how different building elements at different levels of detail can be constructed. Considering future research possibilities, the integration approach in the thesis is seen as a starting-point for developing a common database that formulates a UBM’s platform. With such a platform, data from IFC and CityGML can be automatically integrated and processed in different analyses. Other formats can also be included in further steps. Finally, the proposed approach is believed to need future research beyond the building models alone and on an implementation process for testing and verification.

The gravity field and steady-state ocean circulation explorer (GOCE) (ESA 1999,Albertella et al. 2002, Balmino et al. 1998 and 2001) was finally launched on 17thMarch in 2009. In this satellite mission the second-order derivatives of the Earth’sgravitational potential are measured based on differential accelerometer at a satellitebornegradiometer. It is expected to recover the geopotential coefficients to higherdegrees and orders than those were obtained from the former satellite missions; sayup to degree and order 300. Such an Earth’s gravity model will have an accuracy of 1cm in global geoid height and of 1 mGal for the gravity anomalies, which areextremely good accuracies of the long-wavelength structure of the gravity field.

The present report is a summary of the studies of Mehdi Eshagh when a postdoct/research associate position in division of Geodesy was available for him. Theresearch work consists of the studies continuing his thesis work and completingproject no. 63/07:1, funded by the Swedish National Space Board (SNSB). Thereport is of collective papers type with a series of Papers A-Q. In the following wepresent summaries of his complementary studies. We just present the background ofeach study and the author’s contributions in comparing his research to others’ works.The details about the methodology, theory, numerical investigations and conclusionsare given in the corresponding papers of each subject

The traditional expressions of the gravitational vector (GV) and gravitational gradient tensor (GGT) have complicated forms depending on the first and second order derivatives of associated Legendre functions (ALF), and also singular terms when approaching the poles. The article presents alternative expressions for the GV and GGT, which are independent of the derivatives, and are also non-singular. By using such expressions, it suffices to compute the ALF to two additional degrees and orders, instead of computing the first and second derivatives of all the ALF.  Therefore the formulas are suitable for computer programming. Matlab software as well as an output of a numerical computation around the North Pole is also presented based on the derived formulas.

The objective of this research is to investigate the extent of land-cover change in and around Stockholm from 1986 to 2006 and the nature of the resulting landscape fragmentation with a particular focus on the possible environmental impact. Four scenes of SPOT imagery over the Stockholm area were acquired for this study: two on 13 June 1986, one on 5 August 2006 and one on 4 June 2008. Various image processing and classification algorithms were tested and compared. The best classification results were obtained using an object-based and rule-based approach with texture measures as well as spectral data as inputs. The image pairs from the two decades were classified into seven land cover categories for Stockholm Municipality, i.e., low-density built-up, high-density built-up, industrial areas, open land, forest, mixed forest and open land, and water. The overall accuracies were 93% (kappa: 0.91) for 1986 and 97% (kappa: 0.96) for 2006. Landscape fragmentation and change was evaluated using spatial metrics. The spatial metric results reveal that urban areas increased at the expense of non-built up areas by around 2% both on the municipal and regional levels. The 2006/2008 classification gives evidence of being a more fragmented landscape than that of 1986. While urban areas have become denser within Stockholm municipality, which is in line with the region's development policy, more natural land cover types have at the same time been eroded; a development not in line with the regional goal of maintaining the area's green spaces. The classification technique used on the municipality will be expanded to the region as a whole, and regional trends and consequent recommendations will be the focus of future research

As a new technique of SAR interferometry (InSAR), permanent scatterersSAR interferometry (PS InSAR) has been successfully applied on some urban areas tomeasure the terrain deformation.[1][2][5] But it is not easy to use it in the mountainousand humid areas due to the uncorrelated and atmospheric errors. Wanzhou is such aplace where landslides frequently take place. It locates in the Three Gorges region,China. In this paper, we present our PS InSAR application on Wanzhou. Investigationsare also made on PS processing flow.

The efficient management of moving object databases has gained much interest in recent years due to the development of mobile communication and positioning technologies. A typical way of representing moving objects is to use the trajectories. Much work in the database community has focused on the topics of indexing, query processing and data mining of moving object trajectories, but little attention has been paid to the preservation of privacy in this setting.

In many applications such as intelligent transport systems (ITS) and fleet management, floating car data (FCD), i.e., tracked vehicle locations, are collected, and used for mining traffic patterns. For instance, by mining vehicle trajectories in urban transportation networks over time one can easily identify dense areas (roads, junctions, etc.), and use this knowledge to predict traffic congestion. By data mining the periodic movement patterns (objects follow similar routes at similar times) of individual drivers, personalized, context–aware services can be delivered. However, exposing location / trajectory data of moving objects to application servers can cause threats to the location privacy of individual users. For example, a service provider with access to trajectory data can study a user’s personal habits. The naïve approach of keeping the user’s identity a secret by hiding / encoding the user’s ID does not work: Frequent user locations, such as the home and office addresses can be found by first self–correlating the user’s trajectory, and then cross–referencing the frequent locations with publicly available spatial data sources, e.g., Yellow Pages, thereby revealing the user’s identity.

In recent years, the study of privacy–preserving data mining has appeared due to the advances in data collection and dissemination technologies which force existing data mining algorithms to be reconsidered from the point of view of privacy protection. Various privacy concepts and measures, such as k–anonymity and l–diversity, and related privacy–preservation techniques, such as perturbation, condensation, generalization and data hiding with conceptual reconstruction have been proposed in the general setting. However, their extension or applicability to the spatio–temporal domain, in particular the privacy–preserving data mining of moving object trajectories has not been investigated. Hence the chapter is focused on addressing the unique challenge of obtaining detailed, accurate patterns from anonymized location and trajectory data.

After a thorough status report on research works related to the issue of privacy–preserving data mining on moving object trajectories, first, the chapter proposes a novel anonymization model for preservation of location privacy on moving object trajectories. In this model, users specify their requirements of location privacy, based on the notions of anonymization rectangles and location probabilities, intuitively saying how precisely they want to be located in given areas. Second, the chapter shows a common problem with existing methods that are based on the notion of k–anonymity. This problem allows an adversary to infer a frequently occurring location of a user, e.g., the home address, by correlating several observations. Third, the chapter presents an effective grid–based framework for data collection and mining over the anonymized trajectory data. The framework is based on the notions of anonymization grids and anonymization partitionings which allow effective management of both the user–specified location privacy requirements and the anonymized trajectory data. Along with the framework, three policies for constructing anonymization rectangles, called common regular partitioning, individual regular partitioning, and individual irregular partitioning are presented. All three policies avoid the aforementioned privacy problems of existing methods. Fourth, the chapter presents a client–server architecture for an efficient implementation of the system. A distinguishing feature of the architecture is that anonymization is performed solely on the client, thus removing the need for trusted middleware. Fifth, the chapter presents techniques for solving two basic trajectory data mining operation, namely finding dense spatio–temporal areas and finding frequent routes. The techniques are based on probabilistic counting. Finally, extensive experiments with prototype implementations show the effectiveness of the approach, by comparing the presented solutions to their non–privacy–preserving equivalents. The experiments show that the framework still allows most patterns to be found, even when privacy is preserved.

Urban areas around the world are changing constantly and therefore it is necessary to update urban land cover maps regularly. Remote sensing techniques have been used to monitor changes and update land-use/land-cover information in urban areas for decades. Optical imaging systems have received most of the attention in urban studies. The development of SAR applications in urban monitoring has been accelerated with more and more advanced SAR systems operating in space.

This research investigated object-based and rule-based classification methodologies for extracting urban land-cover information from high resolution SAR data. The study area is located in the north and northwest part of the Greater Toronto Area (GTA), Ontario, Canada, which has been undergoing rapid urban growth during the past decades. Five-date RADARSAT-1 fine-beam C-HH SAR images with a spatial resolution of 10 meters were acquired during May to August in 2002. Three-date RADARSAT-2 ultra-fine-beam C-HH SAR images with a spatial resolution of 3 meters were acquired during June to September in 2008.

SAR images were pre-processed and then segmented using multi-resolution segmentation algorithm. Specific features such as geometric and texture features were selected and calculated for image objects derived from the segmentation of SAR images. Both neural network (NN) and support vector machines (SVM) were investigated for the supervised classification of image objects of RADARSAT-1 SAR images, while SVM was employed to classify image objects of RADARSAT-2 SAR images. Knowledge-based rules were developed and applied to resolve the confusion among some classes in the object-based classification results.

The classification of both RADARSAT-1 and RADARSAT-2 SAR images yielded relatively high accuracies (over 80%). SVM classifier generated better result than NN classifier for the object-based supervised classification of RADARSAT-1 SAR images. Well-designed knowledge-based rules could increase the accuracies of some classes after the object-based supervised classification. The comparison of the classification results of RADARSAT-1 and RADARSAT-2 SAR images showed that SAR images with higher resolution could reveal more details, but might produce lower classification accuracies for certain land cover classes due to the increasing complexity of the images. Overall, the classification results indicate that the proposed object-based and rule-based approaches have potential for operational urban land cover mapping from high-resolution space borne SAR images.

The analysis of spatial structure features in high resolution imagery is one of the most important research fields in remote sensing information processing. In this study, we attempt to quantitatively describe the differences of some spatial structure features of the selected urban land cover(use) types in 0.61-metre resolution Quickbird panchromatic imagery using morphological method. Gray-scale granulometry based on opening of each selected land use type with discs of increasing size provided a size distribution which indicates the prevailing sizes of the image structures and the corresponding volume measurement (sum of grey levels of all image pixels) losses at these sizes which are normalized. A series of directional openings with linear structuring elements were applied for each land use type and the predominant orientation of the land use type Was obtained by selecting the direction in which the volume measurement was maximal when opening was used. Also the strength of the predominant orientation information was obtained. Clear distinctions among different kinds of selected urban land use types were presented through the previously obtained prevailing sizes, normalized volume losses at these sizes, predominant orientation and its strength. It shows that these variables which reflect the size and orientation information could be integrated to characterize spatial structure features of urban land use types, which can be used in the extraction of some land use types from high resolution images.

Differential interferometric synthetic aperture radar (DInSAR) technique has been widely accepted as a powerful tool to map surface deformation. To quantitatively evaluate the surface displacement caused by Wenchuan Earthquake on 12 May 2008 in Sichuan Province, China, a series of interferograms were generated from 25 ALOS/PALSAR image pairs, and the surface displacement was then mapped. According to the wrapped differential interferogram, the main rupture fault was plotted with an orientation of North-East 47° and a spanning length of approximately 230 km. The serious affected region with area of 5,000 km2 and the affected region with area of 250,000 km2 were also mapped. Along the radar look of sight (LOS), it is estimated that the ground surface displaced approximated a maximum of 57 cm and 119 cm away from and towards the satellite respectively, i.e. the vertical displacement was a maximum of 73 cm and 150 cm down lift and uplift respectively. The capability of DInSAR technique and ALOS PALSAR data for co-seismic deformation mapping has been demonstrated and proved to be useful in the surface deformation applications. In addition, some limitations were discussed including the topographic, atmospheric, and orbital errors.

Rapid economic development, combined with tremendous population growth and migration from rural areas, has resulted in a dramatic urbanization in the Yangtze River Delta over the last three decades. In order to develop a more quantitative understanding of urbanization trajectory in the Yangtze Delta from the late 1980s to 2005, the time-series national land cover/land-use database (NLCD), interpreted from remote sensing imagery (including Landsat TM, ETM+ and CBERS), was examined from the aspects of spatial pattern and temporal process. The results showed that the urban land in the Yangtze River Delta has increased from 2.29x10(3) km(2) in the late 1980s to 4.19x10(3) km(2) in 2005. The percentages of total land area in the Yangtze Delta occupied by urban environments in the late 1980s, 1995, 2000 and 2005 were 2.09%, 3.03%, 3.28%, and 3.82% respectively. During the late 1980s - 2005, the total urban expansion in this region was 1.92x10(3) km(2), resulting in an annual urban expansion area (UXa) of about 118.72 km(2) per year, with an urban erpansion intensity (UXt)of 83.03%. There were significant spatial trends and differences in urbanization level and urban expansion. Most urban land and urban expansion have occurred along the Huning Railway (Shanghai-Nanjing) and the Hanzhou Bay. This study also revealed substantial temporal differences in the rate at which urban areas have expanded. There was a great deal of urban growth in the late 1980s - 1995, and also in 2000 - 2005. The 1995 - 2000 period saw a slow expansion speed due to government initiatives designed to hall the loss of agricultural land. In this study, both patterns and dynamics of urban distribution and urban expansion were examined on temporal and spatial scales, and integrated to produce a comprehensive evaluation of recent urbanization trajectory in the Yangtze River Delta.

The Padma and the Jamuna are the two of three major rivers those flow within few meters of height in Bangladesh. These rivers are very important in context of water navigation, irrigation, fishing and fresh water for down stream. On the other side, those are the rivers of erosion of riverbanks and deposition of sandbanks. The main objective of this study is to estimate the eroded and deposited banks of the Padma and the Jamuna and to visualize movement of their channels from 1977 to 2000. Three dates of Landsat images were acquired in 1977 (MSS), 1989 (TM) and 2000 (ETM+) over the study area. Processing of Landsat images was performed by PCI Geomatics and ArcGIS 9.2 was used for quantification of eroded and deposited land covers. Subset the data was performed as preprocessing of image. Seven types of land covers of level I were decided for imagery classification where settlement areas were separated using mask. Supervised classification method was applied using 200 pixels for each class as test set other than training area for accuracy assessment where average accuracies of 85.64%, 89.14% and 90.07% were achieved in 1977 (MSS), 1989 (TM) and 2000 (ETM+) respectively. ArcGIS 9.2 was used to transfer the classified images to GIS layer for quantification. Eroded and deposited areas of the Padma and the Jamuna between the years were calculated by superimposition and pair-wise comparison of river layers in 1977-89 and 1989-2000. From 1977 to 1989 and 1989 to 2000, estimated average erosion was 5436 and 2954 hectares/year and deposition was 773 and 1954 hectares/year correspondingly. In 1977, 1989 and 2000, estimated rivers area in the study area were 2789, 3348, 3458 sq km. During this period, there was more erosion than deposition which indicates that rivers were getting wider. The confluence point of the Padma and the Jamuna was migrated toward southeast and their channels were moved by erosion and deposition following their direction. General trend of channel movement of the Padma was toward south but for the Jamuna, it was quite irregular.

Coastal erosion has become an important phenomenon for all the beaches in theworld. There are many physical changes involved in the Coastal erosion. This paperis more concentrated towards the quantification of the coastal erosion andmovements of sediments along the beach. It tries to understand the volumetricchanges and Sediment movement along the Spey Mouth and River Spey. The thesisincludes the study of the changes along the beach and river over a long period oftime. The study area is located to the Northeastern part of the Scotland, UK. The areais located at Latitude 490N and Longitude 30W .The main purpose of this thesis work is to create the DTMs from the stereo imagesgot from the year 2000 using the software Socet Set 5.3. Then Orthophotos arecreated using the same software for further study of the Geomorphologic changesalong the Spey mouth and River Spey. The DTM and images derived from LiDAR inthe year 2003 are also used to study the changes. This research explains thephotogrammetrical methods used to generate the Orthophoto and DTM for theLower Spey River and Spey beach. Using the generated models in the GIS analysis tocalculate the volume and area change in the Spey area. This paper aims to visualizeand understand the changes in height that took place from 2000 to 2003.The main objectives of this project include the calculation of the changes in volumeof the Spey River and the Spey Bay Beach; generate the height changes in differentparts of the Spey area and to visualize the processes.

Geographic information research and technologies have experienced over four decades of development, from the mainframe to the workstation to the desktop, and to today’s laptop and mobile devices. Every important GIS development is driven by a significant breakthrough of mainstream information technology. For example, the 1980s was characterized by the popularity of personal computers that were increasingly becoming affordable to university departments, governmental agencies and private sectors. Many university GIS programs were established during this time period, and the NSF-funded NCGIA played an important role in coordinating the development of course curriculum and related research activities. The next decade can be named the age of GIScience. GIScience is the science behind GISystens, dealing with fundamental questions raised by the use of GISystems and technologies (Goodchild 1997). It occurred at the time when the Internet and the World Wide Web started to change the way we led our lives and ran our businesses. It was the Internet and the Web that made the GIS community think of a service oriented approach to GIS, namely GIServices (Günther and Müller 1999). Instead of owning a GIS, end users can be served by GIS functionalities from a remote GIService center. GIServices aim to develop distributed or decentralized GIS to serve individuals and communities for spatial planning and decision making, as well as for their daily life. Another perspective of GIS is GIStudies for studying the impacts of geographic information and technologies on society.

With the rapid industrial development, the Geographic Information System (GIS) and Multi CriteriaEvaluation (MCE) have been widely used to analysis the land utilization. In this project, the area ofPanzhihua was chosen to conduct the industrial suitability and economic land analysis. GIS analysis wasperformed to investigate the suitability and cost of land using various data such as DEM and various landuseinformation. The most important spatial analysis techniques used in this project are Multi Criteria Evaluationand a dual equation. Costs associated with terrain conditions (slope), green land, build up area, factories,streets, country road, highway, railway and water body were derived from virtual costs that are used toidentify the relative costs of all criteria. The suitability- cost ratio was performed incorporating with the landsuitability map and land cost map to identify the suitable-low cost industrial siting.

High-resolution multispectral remote sensing image provides both spectral and structural information about land cover/land use types. In segmentation of such complex image scenes with obvious texture, the efficient image segmentation is required. In this study, a method for high resolution image segmentation based on the extended morphological profiles is proposed. First, fundamental morphological vector operations (erosion and dilation) are defined by the extension, taking into account the spatial and spectral information in simultaneous fashion. Theoretical definitions of extended morphological operations are used in the formal definition of the concept of extended morphological profiles, which is constructed based on the repeated use of openings and closings by reconstruction with a structuring element (SE) of increasing size. Then, the morphological multiscale characteristic (MMC) of each pixel is gained through the derivative of the extended morphological profiles (DEMP). A modified method was proposed to obtain the right morphological characteristics of the pixel, which will be used for the final segmentation results. Finally, a simple region merging method based on the distance between two centroids of the neighboring regions was adopted to further improve the segmentation result. The proposed approach is applied to high-resolution QuickBird multispectral images from urban, agricultural and forest areas for evaluation and comparison with existing methods, in terms of qualitative visual inspection and quantitative criteria. The proposed method demonstrated better performance than the classical morphological segmentation approaches.

The usage of single geographical footprint model in existing Geographical Information Retrieval (GIR) system will cause manyproblems like overestimation or underestimation of the geographical scopes for documents to search. To be honest, the singlegeographical footprint model is not applicable in modern GIR system although it is simple, fast and widely applied today. In order toimprove the quality of answers given to a spatial query, a new model as well as a dedicated algorithm will be proposed to study thegeographical information attached to documents. Besides, a dedicated algorithm based on network graph, which is inspired by theGoogle PageRank and Bayesian network theory, is also invented to estimate the geographical similarity between document€d andquery€q based on this new model. We believe that the new model and algorithm proposed here could better estimate thegeographical similarity between document and query for a GIR system. Because it not only consider the geometric adjacency ofdocument and query, but also take into account the importance of each places towards the hosting documents. By using the newmodel, the geographical scope of document could be better studied, and thus improve the quality of answers from GIR systemconcerning the spatial query.

3D city models have been widely used in different applications such as urban planning, traffic control, disaster management etc. Effective visualisation of 3D city models in various scales is one of the pivotal techniques to implement these applications. In this thesis, a framework is proposed to visualise the 3D city models both online and offline using City Geography Makeup Language (CityGML) and Extensible 3D (X3D) to represent and present the models. Then, generalisation methods are studied and tailored to create 3D city scenes in multi-scale dynamically. Finally, the quality of generalised 3D city models is evaluated by measuring the visual similarity from the original models.

In the proposed visualisation framework, 3D city models are stored in CityGML format which supports both geometric and semantic information. These CityGML files are parsed to create 3D scenes and be visualised with existing 3D standard. Because the input and output in the framework are all standardised, it is possible to integrate city models from different sources and visualise them through the different viewers.

Considering the complexity of the city objects, generalisation methods are studied to simplify the city models and increase the visualisation efficiency. In this thesis, the aggregation and typification methods are improved to simplify the 3D city models.

Multiple representation data structures are required to store the generalisation information for dynamic visualisation. One of these is the CityTree, a novel structure to represent building group, which is tested for building aggregation. Meanwhile, Minimum Spanning Tree (MST) is employed to detect the linear building group structures in the city models and they are typified with different strategies. According to the experiments results, by using the CityTree, the generalised 3D city model creation time is reduced by more than 50%.

Different generalisation strategies lead to different outcomes. It is important to evaluate the quality of the generalised models. In this thesis a new evaluation method is proposed: visual features of the 3D city models are represented by Attributed Relation Graph (ARG) and their similarity distances are calculated with Nested Earth Mover’s Distance (NEMD) algorithm. The calculation results and user survey show that the ARG and NEMD methods can reflect the visual similarity between generalised city models and the original ones.

In this paper, a novel framework based on CityGML and X3D is proposed to support visualization of 3D City Model through Internet. In the proposed framework, the CityGML files are first parsed to acquire the city model information. Citygml4j, an open source java API, is used for this parsing. Then, the X3D representation is generated based on the city model by the proposed algorithm which can dynamically create different 3D city models according to corresponding Levels of Detail (LOD). Finally, the 3D city scene in X3D format is displayed through Internet with java applet or other X3D viewers. The Java Applets are created using the Xj3D toolkit. The preliminary experiment shows that the framework can correctly and efficiently exhibit the3D city model via Internet.

The objective of this research is to evaluate multi-temporal RADARSAT-2 polarimetric SAR data for urban land-cover classification using a novel classification scheme. Six-date RADARSAT-2 Polarimetric SAR data in both ascending and descending orbits were acquired during June to September 2008 in the rural-urban fringe of the Greater Toronto Area. The major land-cover types are builtup areas, roads, golf courses, forest, water and several types of agricultural crops. In this research, the different urban land-cover types and their corresponding polarimetric behaviors were studied. The polarimetric signatures of the various urban land-cover types were extracted from the RADARSAT-2 SAR images and analyzed using a new hierarchical multitemporal classification method. The results showed that the new classification method yielded high classification accuracy, with overall accuracy of 82.1% and Kappa coefficient 0.80 for the major 11 land-cover classes. The classification scheme can effectively extract the urban structures by mapping urban related classes such as streets and major roads with the higher user's accuracy, which is difficult to achieve using a single-date data.