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The CityGML model is now the norm for smart city or digital twin city development for better planning, management, risk-related modelling and other applications. CityGML comes with five levels of detail (LoD), mainly constructed from point cloud measurements and images of several systems, resulting in a variety of accuracies and detailed models. The LoDs, also known as pre-defined multi-scale models, require large storage-memory-graphic consumption compared to single scale models. Furthermore, these multi-scales have redundancy in geometries, attributes, are costly in terms of time and workload in updating tasks, and are difficult to view in a single viewer. It is essential for data owners to engage with a suitable multi-scale spatial management solution in minimizes the drawbacks of the current implementation. The proper construction, control and management of multi-scale models are needed to encourage and expedite data sharing among data owners, agencies, stakeholders and public users for efficient information retrieval and analyses. This paper discusses the construction of the CityGML model with different LoDs using several datasets. A scale unique ID is introduced to connect all respective LoDs for cross-LoD information queries within a single viewer. The paper also highlights the benefits of intermediate outputs and limitations of the proposed solution, as well as suggestions for the future.

Location plays a very important role in geomarketing. Location tells where the customers are, identifies something in the surrounding area or solves problems regarding the location of a new outlet. However, in an urban area, the locations have a vertical component due to high-rise and multilevel buildings. This situation requires a new approach that can handle three-dimensional data for location analysis. In this research, a novel 3D data structure is introduced to manage and constellate locations in three-dimensional space. The data structure is designed based on a group of classifications and clusters, and supplemented with the additional element of nearest-neighbour information. The locations are analysed to determine a geomarketing strategy by using several methods, such as single-nearest-neighbour, k-nearest-neighbour (kNN) and reverse-k-nearest-neighbour (RkNN) analyses. These analyses are performed based on encoded neighbour information of the Voronoi diagram that is extracted from the data structure. From the results, various tasks pertaining to geomarketing strategy can be carried out, such as identifying nearby competitors, locating target customers for marketing purposes and analysing the impact of opening a new outlet on competitors. Additionally, the proposed method is tested for its ability to handle large amounts of geomarketing data in terms of its efficiency in time retrieval and storage. The data structure is compared with 3D R-Tree to analyse its performance and efficiency. 3D R-Tree is chosen because it is the most commonly used structure in spatial databases. The test demonstrates that the proposed method requires the least amount of Input/Output than 3D R-Tree. The performance of the data structure is also evaluated; the results indicate that it is outperforms it competitors by responding 60–80% faster to query operations.

Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Smart cities depend on a great extent on wireless sensor network to manage and maintain their services. Advanced sensor technologies are used to acquire information and help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. However, no matter how much smart city may focus on sensor technology, data that are produced from sensors do not organize themselves in a database. Such tasks require a sophisticated database structure to produce informative data output. Besides that, wireless sensor network requires a proper design to improve the energy efficiency. The design will aid to prolong the lifespan of wireless network efficiently. In this study, we proposed a new technique that will be used to organize the information of wireless sensor network in the spatial database. Specific algorithm which is 3D geo-clustering algorithm is used to tackle several issues of location of the sensor in three-dimensional urban area in smart city. The algorithm is designed to minimizing the overlap among group clusters. Overlap plays an important role for energy efficiency. Thus, detection of sensors in two or more group clusters will avoid it from transmitting the same signal to cluster head node. It is prove that this algorithm would only create 5% to 10% overlap among group clusters. Several experiments are performed in this study to evaluate the algorithm. Based on the simulation results indicate that this algorithm can balance nodes energy consumption and prolong the network’s life span. It also has good stability and extensibility. Several tests are performed to validate the efficiency of the technique to measure the database performance.

Urban Heat Island (UHI) phenomenon has been a topic of intense study over the past several years. However, to visualise UHI model is still an issue. Common visualisation of UHI by using digital thematic maps shows that it is hard to perceive its impacts especially in a sophisticated micro-area such as in urbanized cities. Moreover, different building façade’s material gives different UHI value. Therefore, there is a need in computing and visualising this phenomenon in three-dimensional (3D) perspectives. Recently, the development of 3D city modelling shows the potential of solving these gaps. This can be seen from the characteristics of 3D city models that are suitable in representing micro-areas (complex cities) for UHI studies. Based on this issue, this research aims to produce a 3D UHI model by using 3D city models as a tool for efficient and sustainable building design. The main objective is to produce a new approach in visualising UHI in 3D perspectives by instigating 3D city models. Thus, the UHI effect could be predicted precisely by calculating the building façades value. This research explores the 3D shadow analysis, 3D solar radiation and 3D orientation analysis in UHI modelling via 3D city models. From the analyses, the results show that the 3D city models are capable in presenting the solar radiation value for each building façade. Furthermore, this approach can be used to simulate future UHI analysis-prediction and advantageous for pre-development planning.

In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1) were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS) applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2), the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.

3D City modelling is increasingly popular and becoming valuable tools in managing big cities. Urban and energy planning, landscape, noise-sewage modelling, underground mapping and navigation are among the applications/fields which really depend on 3D modelling for their effectiveness operations. Several research areas and implementation projects had been carried out to provide the most reliable 3D data format for sharing and functionalities as well as visualization platform and analysis. For instance, BIMTAS company has recently completed a project to estimate potential solar energy on 3D buildings for the whole Istanbul and now focussing on 3D utility underground mapping for a pilot case study. The research and implementation standard on 3D City Model domain (3D data sharing and visualization schema) is based on CityGML schema version 2.0. However, there are some limitations and issues in implementation phase for large dataset. Most of the limitations were due to the visualization, database integration and analysis platform (Unity3D game engine) as highlighted in this paper.

This paper discusses 3D strata objects registration and implementation within the Land Administration Domain Model (LADM) framework in Malaysia. LADM - ISO 19152:2012 provides a conceptual description for a land administration system, including 3D strata objects registration. Standardization provides flexibility to the data model, making it easier for spatial data handling. The main concern of this research is the conceptual model which has yet to be implemented by the national authority. This research will discuss the practical pathway towards realizing LADM-based 3D strata objects registration in alignment with the jurisdictional settings in Malaysia. An accurate 3D cadastre for a property including strata has become important for the land administration system. Strata objects registration has the following aspects - parcel unit, accessory unit, common property unit, limited common property unit and land parcel. Presently, in Malaysia, all these objects’ representation is in 2D. This paper focusses on extending the representation of those strata objects to 3D. The prototype development begins with the data modelling i.e. selecting relevant object classes and extending the classes with attributes. It focuses on data conversion from an existing database i.e. strata.xml format to an open source database (i.e. PostgreSQL). The visualization and application modules will then be developed using an open source platform (i.e. QGIS). The developed prototype is able to answer all questions related to strata aspects which include ownership, share unit, Management Corporation (MC), spatial source document and strata objects. We anticipate that this work could serve as the model for other national authorities having similar land administration systems especially strata objects registration including the future Spatial Data Infrastructure (SDI) initiative in Malaysia.

Drones are becoming popular in spatial mapping or survey. The use of drones survey can be seen from it low flying heights (capable to create a clear images), accessible on difficult or non-friendly vehicle access areas, faster data acquisition and higher data resolution henceforth improve the quality of the survey. However, this paper focuses on the post-processing of drone images for 3D surface modeling. With the motivation of producing better 3D models, four software packages are used for comparison. Those software packages are eyesMap3D, Drone Deploy, Agisoft PhotoScan and Pix4Dmapper. The equipment used to ensure a high level of quality model is the Leica GPS1200+ stationary GPS module and the DJI Phantom 4 PRO drone. The Leica GPS1200+ stationary GPS module were used to track the exact position of tie points on the ground. Meanwhile the DJI Phantom 4 PRO drone is used as data inputs (images) for the software packages stated. In addition, the drone is used to fly over a golf course, with a challenge of homogenous surface for 3D surface modeling. Based on the output, it shows that each software packages produces slightly different outputs. This paper summarizes the outputs and discusses the key elements in each software packages. This variation might be useful for future references in 3D surface modeling that can conform in different applications requirements.

GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

Different users or applications need different scale model especially in computer application such as game visualization and GIS modelling. Some issues has been raised on fulfilling GIS requirement of retaining the details while minimizing the redundancy of the scale datasets. Previous researchers suggested and attempted to add another dimension such as scale or/and time into a 3D model, but the implementation of scale dimension faces some problems due to the limitations and availability of data structures and data models. Nowadays, various data structures and data models have been proposed to support variety of applications and dimensionality but lack research works has been conducted in terms of supporting scale dimension. Generally, the Dual Half Edge (DHE) data structure was designed to work with any perfect 3D spatial object such as buildings. In this paper, we attempt to expand the capability of the DHE data structure toward integration with scale dimension. The description of the concept and implementation of generating 3D-scale (2D spatial + scale dimension) for the DHE data structure forms the major discussion of this paper. We strongly believed some advantages such as local modification and topological element (navigation, query and semantic information) in scale dimension could be used for the future 3D-scale applications.

2D cadastre has been in existence for decades and most countries have found it convenient. However, in complex situations it has been found to be inadequate as ownership becomes difficult to realise. 3D cadastre data was previously not being collected, thus, making such data even more difficult to realise. 3D data collection for 3D cadastre is one of the main issues for practising surveyors. Several ways of obtaining 3D data exist namely, traditional surveying, terrestrial laser scanning and from Computer Aided Design (CAD) sources. Various data sources have different data structure and a generalized data structure for 3D cadastre hardly reported. A simple and rapid method for indoor data acquisition is proposed. This seeks to determine if the dual half edge data structure is suitable for 3D cadastre. The dual half edge data structure is applied within a graphical user interface. The concept for indoor surveying or data acquisition within the LA_SpatialUnit of the Land Administration Domain Model (LADM) is presented and proposed.

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

Indoor navigation is important for various applications such as disaster management and safety analysis. In the last decade, indoor environment has been a focus of wide research; that includes developing techniques for acquiring indoor data (e.g. Terrestrial laser scanning), 3D indoor modelling and 3D indoor navigation models. In this paper, an automated 3D topological indoor network generated from inaccurate 3D building models is proposed. In a normal scenario, 3D indoor navigation network derivation needs accurate 3D models with no errors (e.g. gap, intersect) and two cells (e.g. rooms, corridors) should touch each other to build their connections. The presented 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. For reducing time and cost of indoor building data acquisition process, Trimble LaserAce 1000 as surveying instrument is used. The modelling results were validated against an accurate geometry of indoor building environment which was acquired using Trimble M3 total station.

Supply Chain Management (SCM) is the management of the products and goods flow from its origin point to point of consumption. During the process of SCM, information and dataset gathered for this application is massive and complex. This is due to its several processes such as procurement, product development and commercialization, physical distribution, outsourcing and partnerships. For a practical application, SCM datasets need to be managed and maintained to serve a better service to its three main categories; distributor, customer and supplier. To manage these datasets, a structure of data constellation is used to accommodate the data into the spatial database. However, the situation in geospatial database creates few problems, for example the performance of the database deteriorate especially during the query operation. We strongly believe that a more practical hierarchical tree structure is required for efficient process of SCM. Besides that, three-dimensional approach is required for the management of SCM datasets since it involve with the multi-level location such as shop lots and residential apartments. 3D R-Tree has been increasingly used for 3D geospatial database management due to its simplicity and extendibility. However, it suffers from serious overlaps between nodes. In this paper, we proposed a partition-based clustering for the construction of a hierarchical tree structure. Several datasets are tested using the proposed method and the percentage of the overlapping nodes and volume coverage are computed and compared with the original 3D R-Tree and other practical approaches. The experiments demonstrated in this paper substantiated that the hierarchical structure of the proposed partitionbased clustering is capable of preserving minimal overlap and coverage. The query performance was tested using 300,000 points of a SCM dataset and the results are presented in this paper. This paper also discusses the outlook of the structure for future reference.

Nowadays, municipalities intend to have 3D city models for facility management, disaster management and architectural planning. 3D data acquisition can be done by laser scanning for indoor environment which is a costly and time consuming process. Currently, for indoor surveying, Electronic Distance Measurement (EDM) and Terrestrial Laser Scanner (TLS) are mostly used. In this paper, several techniques for indoor 3D building data acquisition have been investigated. For reducing the time and cost of indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. The accuracy of the rangefinder is evaluated and a simple spatial model is reconstructed from real data. This technique is rapid (it requires a shorter time as compared to others), but the results show inconsistencies in horizontal angles for short distances in indoor environments. The range finder was calibrated using a least square adjustment algorithm. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation are used.

Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future Refereed/Peer-reviewed

As cities and urban areas grow and become more complex, the task of managing, updating and displaying three-dimensional urban information can be challenging for city and urban authorities. The emergence of 3D city models has enabled the authorities to work with more reliable and competent data as 3D data (and maps) are proven to be more accurate and relatable in representing real world objects and scenarios. In South East Asia countries such as Malaysia and Singapore, urban development activities are dynamic causing city inventory information to change within short periods of time. The ability to detect and track the changes on building structures located in a city can avoid loss of revenue to the urban authorities as well as improving the efficiency of a city inventory in assisting the decision making process on management level. City inventory management system should be able to store and provide information especially related to the building structure that is needed by the local authority to manage a city efficiently. Current traditional methods utilized by most urban authorities in South East Asia region are inefficient and unable to cope with current complex scenarios in urban areas. This results in some valuable information for building management and information systems being discarded. This research presents a method to boost the efficiency of some aspect in city inventory for local authorities by introducing 3D change detection method on 3D city models. The proposed method is able to detect and analyse changes that occur on 3D buildings using the 3D segmentation approach. A hybrid semantic-geometric 3D segmentation method that deals with segmentation of a 3D building based on its semantic value and surface characteristics, fitted by one of the predefined primitives is presented. The technique is designed to retain existing semantic and geometric information and ultimately enrich it by adding more specialized information. For future work, the proposed method will be implemented as part of the auto-updating module that is able to detect any changes on 3D buildings such as storage and retrieval of semantic information of the changed structure, and automatically update the 3D city models for analysis.

For a better visual impression, 3D information systems and architecture need detailed, photo-realistic visualization of 3D data-sets. However, easy accessibility with efficient rendering becomes difficult due to the detailed data associated with 3D objects. Therefore, different applications demand different levels of detail (LoD). Currently, City Geography Markup Language (CityGML), as the Open Geospatial Consortium standard, is being used to model and represent buildings in different LoDs (LoD0–LoD4), but it does not provide methods to generate different LoDs automatically. Thus, generalized (abstracted) 3D scenes of buildings need to be generated to fulfill the demands of task-specific applications by reducing data volume. This paper discusses various ways to generalize building models, within the framework of CityGML, reducing the level of detail from higher LoD to lower. The LoD4 data is parsed and analyzed. Various heuristics are applied to simplify the ground plan and the results are then aggregated...

Cities and urban areas entities such as building structures are becoming more complex as the modern human civilizations continue to evolve. The ability to plan and manage every territory especially the urban areas is very important to every government in the world. Planning and managing cities and urban areas based on printed maps and 2D data are getting insufficient and inefficient to cope with the complexity of the new developments in big cities. The emergence of 3D city models have boosted the efficiency in analysing and managing urban areas as the 3D data are proven to represent the real world object more accurately. It has since been adopted as the new trend in buildings and urban management and planning applications. Nowadays, many countries around the world have been generating virtual 3D representation of their major cities. The growing interest in improving the usability of 3D city models has resulted in the development of various tools for analysis based on the 3D city models. Today, 3D city models are generated for various purposes such as for tourism, location-based services, disaster management and urban planning. Meanwhile, modelling 3D objects are getting easier with the emergence of the user-friendly tools for 3D modelling available in the market. Generating 3D buildings with high accuracy also has become easier with the availability of airborne Lidar and terrestrial laser scanning equipments. The availability and accessibility to this technology makes it more sensible to analyse buildings in urban areas using 3D data as it accurately represent the real world objects. The Open Geospatial Consortium (OGC) has accepted CityGML specifications as one of the international standards for representing and exchanging spatial data, making it easier to visualize, store and manage 3D city models data efficiently. CityGML able to represents the semantics, geometry, topology and appearance of 3D city models in five well-defined Level-of-Details (LoD), namely LoD0 to LoD4. The accuracy and structural complexity of the 3D objects increases with the LoD level where LoD0 is the simplest LoD (2.5D; Digital Terrain Model (DTM) + building or roof print) while LoD4 is the most complex LoD (architectural details with interior structures). Semantic information is one of the main components in CityGML and 3D City Models, and provides important information for any analyses. However, more often than not, the semantic information is not available for the 3D city model due to the unstandardized modelling process. One of the examples is where a building is normally generated as one object (without specific feature layers such as Roof, Ground floor, Level 1, Level 2, Block A, Block B, etc). This research attempts to develop a method to improve the semantic data updating process by segmenting the 3D building into simpler parts which will make it easier for the users to select and update the semantic information. The methodology is implemented for 3D buildings in LoD2 where the buildings are generated without architectural details but with distinct roof structures. This paper also introduces hybrid semantic-geometric 3D segmentation method that deals with hierarchical segmentation of a 3D building based on its semantic value and surface characteristics, fitted by one of the predefined primitives. For future work, the segmentation method will be implemented as part of the change detection module that can detect any changes on the 3D buildings, store and retrieve semantic information of the changed structure, automatically updates the 3D models and visualize the results in a userfriendly graphical user interface (GUI).

One of the most dangerous disaster threatening the high rise and complex buildings of today's world including thousands of occupants inside is fire with no doubt. When we consider high population and the complexity of such buildings it is clear to see that performing a rapid and safe evacuation seems hard and human being does not have good memories in case of such disasters like world trade center 9/11. Therefore, it is very important to design knowledge based realtime interactive evacuation methods instead of classical strategies which lack of flexibility. This paper presents a 3D-GIS implementation which simulates the behaviour of an intelligent indoor pedestrian navigation model proposed for a self -evacuation of a person in case of fire. The model is based on Multilayer Perceptron (MLP) which is one of the most preferred artificial neural network architecture in classification and prediction problems. A sample fire scenario following through predefined instructions has been performed on 3D model of the Corporation Complex in Putrajaya (Malaysia) and the intelligent evacuation process has been realized within a proposed 3D-GIS based simulation.

Scaling factor is one of the most crucial aspect in 2D and 3D models especially in computer graphics, CAD, GIS, and games. Different user or/and application need different scale models during various stages of the use of data, including visualization and interaction. There are some arisen issues on 3D data model especially to meet GIS requirements while minimize the redundancy of the datasets. In GIS modelling, various data structures and data models have been proposed to support variety of applications and dimensionalities, but only a few in scale dimension. Some of them have succeeded in modelling scale such as in Space-Scale Cube (SSC) model. The recently implemented Dual Half-Edge (DHE) data structure within the PostgreSQL database is suitable for any valid 3D spatial model; not yet being explored for other dimensional such as scale environment. Using the same vario-scale approach, the DHE data model is also capable to implement a variable Level of Detail (LoD) representation such as SSC model. Some advantages of the DHE are described in this paper such as the dynamic property (valid updates based on Euler operations) and topology approach in comparison with other existing data structures. The last section of this paper describes capability of the DHE data structure to provide a better platform for GIS integrated space-scale data model.

This paper describes the usage of MUSCLE (Multidirectional Scanning for Line Extraction) Model for automatic generation of 3D networks in CityGML format (from raster floor plans). MUSCLE (Multidirectional Scanning for Line Extraction) Model is a conversion method which was developed to vectorize the straight lines through the raster images including floor plans, maps for GIS, architectural drawings, and machine plans. The model allows user to define specific criteria which are crucial for acquiring the vectorization process. Unlike traditional vectorization process, this model generates straight lines based on a line thinning algorithm, without performing line following-chain coding and vector reduction stages. In this method the nearly vertical lines were obtained by scanning the images horizontally, while the nearly horizontal lines were obtained by scanning the images vertically. In a case where two or more consecutive lines are nearly horizontal or nearly vertical, raster data become unmanageable and the process generates wrongly vectorized lines. In this situation, to obtain the precise lines, the image with the wrongly vectorized lines is diagonally scanned. By using MUSCLE model, the network models are topologically structured in CityGML format. After the generation process, it is possible to perform 3D network analysis based on these models. Then, by using the software that was designed based on the generated models, a geodatabase of the models could be established. This paper presents the correction application in MUSCLE and explains 3D network construction in detail.

Buildings are often modelled as two-dimensional (2D) footprints which are extruded to simple cubes. Buildings are also represented as more complex objects with roofs, facades, etc. – in this case they are polyhedra, sometimes of a complex shape. These allow for visualisation and analysis of a wide area like a city, but micro-scale analysis of interiors is not possible. An example can be rescue operation simulation where information about the internal structure of a building and the external terrain is crucial to improve the response time. It demands a three-dimensional (3D) model where each room is represented as a separate element; there are also doors, windows, walls and other objects that have to be included. Even complex geometrical models can be easily constructed using Computer-Aided Design (CAD) systems. However, lack of semantic information and topological relations makes such models poor choices for GIS analysis. With the new dual half-edge (DHE) data structure and a set of Euler operators a 3D model can be built as in CAD systems, and represented as a cell complex. Construction of non-manifold objects is also possible. An advantage of the DHE is simplicity – only edges and nodes are used. Because of the 3D duality implemented in the structure volumes (cells) and faces are also present in the model. The geometry of a model is constructed explicitly by using Euler operators: connections between elements are created automatically, and semantic information is represented with attributes which can be assigned to any element of the model.

In the next few years, 3D data is expected to be an intrinsic part of geospatial data. However, issues on 3D spatial data management are still in the research stage. One of the issues is performance deterioration during 3D data retrieval. Thus, a practical 3D index structure is required for efficient data constellation. Due to its reputation and simplicity, R-Tree has been received increasing attention for 3D geospatial database management. However, the transition of its structure from 2D to 3D had caused a serious overlapping among nodes. Overlapping nodes also occur during splitting operation of the overflown node N of M + 1 entry. Splitting operation is the most critical process of 3D R-Tree. The produced tree should satisfy the condition of minimal overlap and minimal volume coverage in addition with preserving a minimal tree height. Based on these concerns, in this paper, we proposed a crisp clustering algorithm for the construction of a 3D R-Tree. Several datasets are tested using the proposed method and the percentage of the overlapping parallelepipeds and volume coverage are computed and compared with the original R-Tree and other practical approaches. The experiments demonstrated in this research substantiated that the proposed crisp clustering is capable to preserve minimal overlap, coverage and tree height, which is advantageous for 3D geospatial data implementations. Another advantage of this approach is that the properties of this crisp clustering algorithm are analogous to the original R-Tree splitting procedure, which makes the implementation of this approach straightforward.

Topology is one of the mechanisms to describe relationships between spatial objects. Thus, it is the basis for many spatial operations. Models utilizing the topological properties of spatial objects are usually called topological models, and are considered by many researchers as the best suited for complex spatial analysis (i.e., the shortest path search). A number of topological models for two-dimensional and 2.5D spatial objects have been implemented (or are under consideration) by GIS and DBMS vendors. However, when we move to one more dimension (i.e., three-dimensions), the complexity of the relationships increases, and this requires new approaches, rules and representations. This paper aims to give an overview of the 3D topological models presented in the literature, and to discuss generic issues related to 3D modeling. The paper also considers models in object-oriented (OO) environments. Finally, future trends for research and development in this area are highlighted.

In the last few years, 3D urban data and its information are rapidly increased due to the growth of urban area and urbanization phenomenon. These datasets are then maintain and manage in 3D spatial database system. However, performance deterioration is likely to happen due to the massiveness of 3D datasets. As a solution, 3D spatial index structure is used as a booster to increase the performance of data retrieval. In commercial database, commonly and widely used index structure for 3D spatial database is 3D R-Tree. This is due to its simplicity and promising method in handling spatial data. However, 3D R-Tree produces serious overlapping among nodes. The overlapping factor is important for an efficient 3D R-Tree to avoid replicated data entry in a different node. Thus, an efficient and reliable method is required to reduce the overlapping nodes in 3D R-Tree nodes. In this paper, we proposed a 3D geospatial data clustering to be used in the construction of 3D R-Tree and respectively could reduce the overlapping among nodes. The proposed method is tested on 3D urban dataset for the application of urban infill development. By using several cases of data updating operations such as building infill, building demolition and building modification, the proposed method indicates that the percentage of overlapping coverage among nodes is reduced compared with other existing approaches.

2D cadastre has been in existence for decades and most countries have found it convenient. However, in complex situations it has been found to be inadequate as ownership becomes difficult to realise. 3D cadastre data was previously not being collected, thus, making such data even more difficult to realise. 3D data collection for 3D cadastre is one of the main issues for practicing surveyors. Several ways of obtaining 3D data exist namely, traditional surveying, terrestrial laser scanning and from Computer Aided Design (CAD) sources. Various data sources have different data structure and a generalized data structure for 3D cadastre hardly reported. A simple and rapid method for indoor data acquisition is proposed. This seeks to determine if the dual half edge data structure is suitable for 3D cadastre. The dual half edge data structure is applied within a graphical user interface. The concept for indoor surveying or data acquisition within the LA_SpatialUnit of the Land Administration Domain Model (LADM) is presented and proposed. Results show inconsistency of Trimble LaserAce 1000 for distance below 5 m with wide and narrow angle of measurement in indoor environment.

3D navigation within a 3D-GIS environment is increasingly getting more popular and spreading to various fields. In the last decade, especially after the 9/11 disaster, evacuating the complex and tall buildings of today in case of emergency has been an important research area for scientists. Most of the current navigation systems are still in the 2D environment and that is insufficient to visualize 3D objects and to obtain satisfactory solutions for the 3D environment. Therefore, there is currently still a lack of implementation of 3D network analysis and navigation for indoor spaces in respect to evacuation. The objective of this paper is to investigate and implement 3D visualization and navigation techniques and solutions for indoor spaces within 3D-GIS. For realizing this, we have proposed a GIS implementation that is capable of carrying out 3D visualization of a building model stored in the CityGML format and perform analysis on a network model stored in Oracle Spatial. The proposed GUI also provides r...

With the emerging communication technology in recent years, geospatial data sharing is getting important and popular. Spatial data could be accessed and shared by various stakeholders anytime with the support of a common platform, the Spatial Data Infrastructure (SDI). Data sharing for 3D city building is getting popular using Open Geospatial Consortium (OGC) standard named City Geographic Markup Language (CityGML). Due to human readable schema, data sharing in CityGML often consumes high bandwidth and storage. Transmitting CityGML over web services without compression is not practical. As CityGML represented in Extensible Markup Language (XML) schema, XML compression seemed useful for CityGML. Conventional dictionary compressor such as WinZIP, GZip or BZip could reduce data size; however, the decompressed documents certainly produce the original file, which is still consuming large storage space. This paper discussed the existing 3D-SDI framework, compression techniques and how the schema-aware compressor is developed to achieve a higher compression ratio. The proposed compressor is tested by using Putrajaya city 3D building and results are compared against existing techniques. The results are then decompressed and compared with original 3D buildings by visualizing using CityGML viewer. The future directions are highlighted in the final section.

In this research, different texture enhancement methods were investigated and proposed. Rectified perpendicular symmetric photos of 3D objects such as buildings and trees were used to generate the texture for the 3D models. Texture enhancement methods such as higher radiometric adjustment for raised surfaces and Dynamic Pulse Function (DPF) were utilized based on the form of the facade and operators’ observation along with tessellation method. The result of DPF compared with the photorealistic texturing in aspects, quality and data size. The problem of missing faces in a polyhedron and missing object within a CityGML viewer has been solved and described in this chapter. The chapter also describes the development of External code-Lists for objects of the study area which is a starting point for Malaysian Spatial Data Infrastructure (MySDI).

Generally, National Mapping Agencies (NMAs) produce and maintain topographic and cadastral maps. Regular update of map products is the most critical problem faced by NMAs. Therefore, implementation of new technology to automate map generalization has become crucial in updating smaller-scale maps from frequently updated larger-scale maps. Additionally, customized data products can be produced. Implementation of single database and derivation (generalization) of multiple-scale maps from one database can improve the efficiency and maintenance of derived data products. However, consensus between NMAs on a common generalization technique has not been achieved due to incompatibility and complexity of data models. Definitions of terms, technology and organizational structures of the NMAs across the globe are different. This chapter reviews the pertinent generalization efforts made by a number of European NMAs. A framework is proposed based on two correlated models: process-oriented generalization models and object-level-oriented generalization models, which is related to level of map objects. A portion of this framework is implemented and tested on datasets of Kelantan state in Malaysia to produce generalized maps. Generalization operations (e.g., simplification, aggregation, smoothing, etc.) are applied with the aim to generalize polygons and transportation network (e.g., roads, etc.). The proposed framework could be adopted, implemented and tested on datasets maintained by Malaysian National Mapping Agency known as JUPEM (Portal Rasmi Jabatan Ukur Dan Pemetaan Malaysia).

Describing 3D city model over distributed service architecture using Open Geospatial Consortium (OGC) standard, CityGML, is getting popular e.g., Berlin-3D Spatial Data Infrastructure (SDI), Heidelberg-3D SDI, etc. Currently, visualizing 3D city model over the web using X3D is getting common where Web 3D Service (W3DS) publish 3D models in compliance with W3C X3D standard. However, involvement of 3D analysis in 3D SDI environment for Web Processing Service (WPS) requires CityGML whilst this human readable schema often raises issues such as large data that consumes high bandwidth and storage etc. Transmitting CityGML over web services without compression is unpractical due to the typical problem for CityGML. Utilizing conventional compression techniques like WinZIP, GZip, and etc., could reduce large bandwidth consumption for transmitting CityGML over the internet. However, specific schema-aware compression technique shown in this chapter could achieve even higher compression ratio and require lesser time due to utilizing the advantage of parallel programming. Moreover, compressed data is filtered and can be used for smart devices. This distinguishes the advantage using this compressor instead of conventional compression as the filtered data is relatively smaller in file size whilst maintaining essential geometries and attributes information without requiring to decompress back to original file. This chapter discusses how the technique is developed and integrated into simulated Putrajaya 3D SDI, and the results are also illustrated. We also highlight the future directions of the research in the final section.

DBMS becomes very important for GIS as it used to handle large volume of spatial data and could ensure the stability of dataset handling. Next generation of GIS software would highly depend on DBMS in both geometrical modeling and analysis. One of the desired components in such future software or system is the geometric modeling that works with 3D spatial operations. This paper presents a portion of the problems, which are 3D topological operations for DBMS. These operations are very important for 3D spatial analysis. This paper discusses implementation of a 3D data type (Polyhedron) and eight 3D topological relationships between polyhedrons. The relationships are compliant with the 4-intersection model, and it could be extended to 9-intersection model if the exterior component is considered. The implementations are tested for PostgreSQL.

Next generation of GIS software should be able to manipulate and analyse complex situations of real world phenomena. One of the desired components in such software or system is the geometric modeling that works with 3D spatial operations. This paper presents a portion of problem that we currently attempt to solve, that is the 3D spatial operations for Geo DBMS. Some popular spatial operations in 3D GIS for example 3D XOR, 3D union, 3D intersection, and 3D difference are vital for 3D spatial analysis and forms major discussion of this paper and part of our research effort to address the 3D GIS problem. To formulate this research in a suitable way, our approach is to develop the new 3D data type, polyhedron, within geo-DBMS. The basic idea is to relate the implementation of intersection point in 3D planar polygon (Chen and Abdul-Rahman, 2006) into the geometrical modeling for 3D spatial operations. The approach works and we highlighted the results by using the real world data sets. The research shows that the essential mathematical algorithms are applicable for real world objects and provides a solution towards a full 3D analytical operation in future.

Nowadays, 2D GISs are common and their related theories, concepts and models like for geometrical modeling and spatial relationships of objects are also well addressed and investigated. Most of the tasks related to 2D GIS applications are quite straightforward and relatively easy to handle. 2D GIS spatial analysis such as proximity analysis or proximity computation, network analysis, overlay function, neighborhood function, metric measurement and other analytical operations are also well understood and well researched by the GIS community. However, problem started to surface once we move towards 3D domain, i.e. to add an additional dimension to the current 2D GIS situations such as in spatial data modeling, analysis and application. Manipulating and handling spatial objects become more complicated as we move toward 3D. This paper attempts to address one of the problems in 3D analytical operation, i.e. 3D proximity analysis.

3D building models of the world exhibit multi-scale properties. Different level-of-details (LoDs) are important for different applications. Therefore, generation of multi-scale representation of 3D building models to fulfill the demands of these applications is a generalization problem. In order to generalize 3D buildings, different pieces of information need to be preserved or removed to restrict the amount of data represented on a certain LoD. In this work, a three-step strategy based on simplification, aggregation and reconstruction of generalized buildings represented in City Geography Markup Language (CityGML) is proposed. The minimum length of edges (threshold value) for removal of amount of data is restricted to generalization specifications of CityGML characterized by differing accuracies and minimal dimensions of objects for each LoD. The main part of this paper is simplification of ground plans. For this purpose, a new approach is proposed to restrict number of edges, curves, and corners of ground plan of 3D building model on a certain LoD. Algorithms for simplification with the aim to derive LoD1 from exterior shells of buildings at LoD3 are implemented and tested on a number of buildings of Putrajaya city. The experiments showed that length of edge as threshold value is directly proportional to the size of generalized models.