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A full 3D cadastre that supports volume parcels is one interpretation of the phrase "3D cadastre", whereas traditional cadastres that maintain only a limited amount of information about 3D circumstances are another. Three-dimensional (3D) cadastres are sometimes referred to as the 3D computerized illustration of real estate rights, constraints, and obligations. These include all the portions of legal objects, below or above the earth. The paper attempted to clarify the idea of developing 4D marine cadastral data models by evaluating and synthesizing the existing literature on how operators and stakeholders influence the applications of these models in the management of marine objects and properties. In this paper, the authors will identify the phases of marine cadastre models and their current status and more curiously seeks to update the current dimension of the time component to the existing 3D marine cadastre model. The current 3D marine cadastral data model for example in Malaysia and in other countries is still at the conceptual level. This paper will also highlight the peculiarities of marine cadastre components and their interactions with stakeholders, and addresses the practice and appropriate method to make those cadastral objects appear in 4D (3D + t). This study is structured around theories and models that have already been developed by scholars to explain temporal variations in these objects and properties. The result of the study shall give an in-depth discovery of what is known about the proposed 4D model and proffer key areas of interest that further studies can investigate to integrate the time aspect leading to a new 4D marine cadastre data model.

Building information modelling (BIM) and geographical information systems (GIS) domains immensely contribute to a digital representation of architectural and environmental bodies respectively. BIM is endorsed in order to enhance the Architecture Engineering and Construction (AEC) industry process to save time, cost and speed up the project, and more so, to minimise the frequent requests of information by the stakeholders within the industry. On the other hand, the Geographic Information System (GIS) has been increasingly used to generate detailed 3D data, geolocation and spatial analysis. Both BIM and GIS provide 3D data for the development of 3D city models, digital twin, smart city, AEC etc. However, there are significant diverse between the two in terms of their characteristics, scope of interest and focus that makes it difficult to easily be achieved. The amalgamation of the two worlds provides a clear picture of a built environment based on data (geometry and semantics) integration, which reinforces the enhancement of the three-dimensional (3D) applications in general into the digital world. This paper presents a methodology that semantically integrates the two worlds through their standards that is the Industry Foundation Classes (IFC) which is an open standard, selected because it is the typical free standard to exchange data in the BIM world and City Geography Markup Language (CityGML) is the most leading 3D city model standard in 3D GIS. This is carried out by performing a semantic mapping between the two standards, converting the encoding that the two standards use from STEP in IFC(BIM) to XML in CityGML (3D GIS), by providing a basic implementation created using Python to combine the above tasks.

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.

This paper investigates the issues and challenges in using a 3D city model for monitoring flash flood risks in Salalah (Oman) designed using the City Geography Markup Language (CityGML) standards version 2.0. The investigation was made based on the fact that 2D and 2.5D GIS solutions cannot analyse flood complex problems inside the urban area. Hence, the study sought to reduce time and effort for the decision-makers by proposing a 3D city model for flood risk management. The study used geospatial tools and databases such as ArcGIS, Watershed Modelling System (WMS), FME, PostgreSQL-PostGIS, and 3D City Database (3DCityDB) to generate the 3D model and to test the capability of establishing a unified geospatial data structure including the 3D city objects, hydrological data, and geological data. The findings showed the importance of addressing flood risks data and arranging it in the 3D geodatabase. It was also revealed that establishing a 3D city model based on the CityGML standard requires homogenised definitions and standards for city objects (surface and subsurface) as well as hydrological data.

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.

Indoor surveying is currently based on laser scanning technology, which is time-consuming and costly. A construction model depends on complex calculations which need to manage a large number of measured points. This is suitable for the detailed geometrical models utilized for representation, yet excessively overstated when a simple model including walls, floors, roofs, entryways, and windows is required, such a basic model being a key for efficient network analysis such as shortest path finding. To reduce the time and cost of the indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. A comparison of neural network and a combined method of interval analysis and homotopy continuation in 3D interior building modelling for calibration of inaccurate surveying equipment is presented. We will present the interval valued homotopy model of the measurement of horizontal angles by the magnetometer component of the rangefinder. This model blends interval analysis and homotopy continuation. The results prove that homotopies give the best results both in terms of RMSE and the L∞ metric.

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.

Nowadays, municipalities intend to have 3D city models for facility management, disaster management and architectural planning. Indoor models can be reconstructed from construction plans but sometimes, they are not available or very often, they differ from ‘as-built’ plans. In this case, the buildings and their rooms must be surveyed. One of the most utilized methods of indoor surveying is laser scanning. The laser scanning method allows taking accurate and detailed measurements. However, Terrestrial Laser Scanner is costly and time consuming. 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 proposed approache use relatively cheap equipment: a light Laser Rangefinder which appear to be feasible, but it needs to be tested to see if the observation accuracy is sufficient for the 3D building modelling. 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 horizontal angle sensor was calibrated using a least square adjustment algorithm, a polynomial kernel, interval analysis and homotopy continuation.

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.

Recently in our country, the construction of buildings become more complex and it seems that strata objects database becomes more important in registering the real world as people now own and use multilevel of spaces. Furthermore, strata title was increasingly important and need to be well-managed. LADM is a standard model for land administration and it allows integrated 2D and 3D representation of spatial units. LADM also known as ISO 19152. The aim of this paper is to develop a strata objects database using LADM. This paper discusses the current 2D geospatial database and needs for 3D geospatial database in future. This paper also attempts to develop a strata objects database using a standard data model (LADM) and to analyze the developed strata objects database using LADM data model. The current cadastre system in Malaysia includes the strata title is discussed in this paper. The problems in the 2D geospatial database were listed and the needs for 3D geospatial database in future also is discussed. The processes to design a strata objects database are conceptual, logical and physical database design. The strata objects database will allow us to find the information on both non-spatial and spatial strata title information thus shows the location of the strata unit. This development of strata objects database may help to handle the strata title and information.

Geomarketing is a discipline which uses geographic information in the process of planning and implementation of marketing activities. It can be used in any aspect of the marketing such as price, promotion or geo targeting. The analysis of geomarketing data use a huge data pool such as location residential areas, topography, it also analyzes demographic information such as age, genre, annual income and lifestyle. This information can help users to develop successful promotional campaigns in order to achieve marketing goals. One of the common activities in geomarketing is market segmentation. The segmentation clusters the data into several groups based on its geographic criteria. To refine the search operation during analysis, we proposed an approach to cluster the data using a clustering algorithm. However, with the huge data pool, overlap among clusters may happen and leads to inefficient analysis. Moreover, geomarketing is usually active in urban areas and requires clusters to be organized in a three-dimensional (3D) way (i.e. multi-level shop lots, residential apartments). This is a constraint with the current Geographic Information System (GIS) framework. To avoid this issue, we proposed a combination of market segmentation based on geographic criteria and clustering algorithm for 3D geomarketing data management. The proposed approach is capable in minimizing the overlap region during market segmentation. In this paper, geomarketing in urban area is used as a case study. Based on the case study, several locations of customers and stores in 3D are used in the test. The experiments demonstrated in this paper substantiated that the proposed approach is capable of minimizing overlapping segmentation and reducing repetitive data entries. The structure is also tested for retrieving the spatial records from the database. For marketing purposes, certain radius of point is used to analyzing marketing targets. Based on the presented tests in this paper, we strongly believe that the structure is capable in handling and managing huge pool of geomarketing data. For future outlook, this paper also discusses the possibilities of expanding the structure.

Considering various fields of applications for building surveying and various demands, geometry representation of a building is the most crucial aspect of a building survey. The interiors of the buildings need to be described along with the relative locations of the rooms, corridors, doors and exits in many kinds of emergency response, such as fire, bombs, smoke, and pollution. Topological representation is a challenging task within the Geography Information Science (GIS) environment, as the data structures required to express these relationships are particularly difficult to develop. Even within the Computer Aided Design (CAD) community, the structures for expressing the relationships between adjacent building parts are complex and often incomplete. In this paper, an integration of 3D topological indoor building modeling in Dual Half Edge (DHE) data structure and outdoor navigation network from Open Street Map (OSM) is presented.

Locating and analysing the location of new stores or outlets is one of the common issues facing retailers and franchisers. This is due to assure that new opening stores are at their strategic location to attract the highest possible number of customers. Spatial information is used to manage, maintain and analyse these store locations. However, since the business of franchising and chain stores in urban areas runs within high rise multi-level buildings, a three-dimensional (3D) method is prominently required in order to locate and identify the surrounding information such as at which level of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN) analysis. It uses a point location and identifies the surrounding neighbours. However, with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results are presented in this paper. Another advantage of this structure is that it also offers a minimal overlap and coverage among nodes which can reduce repetitive data entry.

The growth of urban areas has resulted in massive urban datasets and difficulties handling and managing issues related to urban areas. Huge and massive datasets can degrade data retrieval and information analysis performance. In addition, the urban environment is very difficult to manage because it involves various types of data, such as multiple types of zoning themes in the case of urban mixed-use development. Thus, a special technique for efficient handling and management of urban data is necessary. This paper proposes a structure called Classified and Clustered Data Constellation (CCDC) for urban data management. CCDC operates on the basis of two filters: classification and clustering. To boost up the performance of information retrieval, CCDC offers a minimal percentage of overlap among nodes and coverage area to avoid repetitive data entry and multipath query. The results of tests conducted on several urban mixed-use development datasets using CCDC verify that it efficiently retrieves their semantic and spatial information. Further, comparisons conducted between CCDC and existing clustering and data constellation techniques, from the aspect of preservation of minimal overlap and coverage, confirm that the proposed structure is capable of preserving the minimum overlap and coverage area among nodes. Our overall results indicate that CCDC is efficient in handling and managing urban data, especially urban mixed-use development applications.

Every country has land policy and land planning systems to improve social, physical, spatial and economic imbalance. Land policies provide the framework, direction and continuity of decisions made for the function of land in the implementation of national development plans which involve local, state and regional plans. In Malaysia, land policies are implemented within a broader framework, which is supervised by the government. Some land policies were implemented based on the National Land Code (NLC). The National Land Code, 1965 came into force on 1st January 1966 to administer all land matters in Peninsular Malaysia and the Federal Territory of Labuan while Sabah and Sarawak continued to use the Sabah Land Ordinance 1930 and Sarawak Land Code 1958 respectively. The purpose of the NLC is to ensure the uniformity of land policy and land law with respect to land tenure, registration, transfer, charges, leases, easements and other interests and rights to land. Rapid development and various needs for securing proprietors’ interests have put a lot of demands on land administration. A new three-dimensional (3D) cadastral system was proposed to cater for above and below surface cadastral objects and to enable the registration of real properties that are not limited to the land surface. The 3D approach for cadastral and land registration systems can provide a better means to manage modern cadastral objects. There are two organisations within Peninsular Malaysia responsible for managing and maintaining the land administration system, namely, the Department of Survey and Mapping Malaysia (DSMM) and the District Land Offices which are responsible for the cadastral survey and ownership rights respectively. Both organisations have their own information systems called eLand in District Land Offices and eCadastre in DSMM. There are three arguments to further improve the land administration system towards e-Government services – government guarantee of indefeasibility of title to private land; information integration for good governance of land administration; systematic and accurate recording for land taxation purposes as a source of important state revenue. Those arguments clearly demonstrated the need for the Land Administration Domain Model (LADM). The LADM is an international standard for land administration purposes. Malaysia does not have a standard model for land administration. Standardisation of land administration within a country should meet the international standard, this will hasten land transactions between international entities. This paper attempts to outline Malaysian land policy in relation to the framework of the National Land Policy and LADM standard as a reference model for Malaysian land administration.

This paper describes the development of geospatial-based disaster management system for an agency at regional level. Important aspects of the system such as spatial data, geospatial database, interface and specific modules for the disaster management system form major discussions of this paper. The Pengerang Disaster Management System (PDMS) is being developed for a local authority in one of the Malaysian states who’s been given a task to monitor the surrounding environmental aspects. The local authority manages one of the largest oil and gas refinery plant in South East Asia region in collaboration with national oil company, PETRONAS. The PDMS, is a one-stop centre (dashboard) for managing the operations with other agencies or stakeholders such as police, marine, army, medical team, fire and rescue units. We anticipate many aspects of disaster management could trigger from this pilot project and thus provide some interesting ideas for a local authority in managing man-made disaster such as fire, other oil and gas related incidents. Some features of the developed system such as online map publishing services, data flow and other geospatial analysis during the event will be discussed in this paper. Near-future work and a big picture of the disaster management approach (with an emphasis to oil and gas incident and scenario) also will be highlighted.

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.

Solar energy modelling is increasingly popular, important, and economic significant in solving energy crisis for big cities. It is a clean and renewable resource of energy that can be utilized to accommodate individual or group of buildings electrical power as well as for indoor heating. Implementing photovoltaic system (PV) in urban areas is one of the best options to solve power crisis over expansion of urban and the growth of population. However, as the spaces for solar panel installation in cities are getting limited nowadays, the available strategic options are only at the rooftop and façade of the building. Thus, accurate information and selecting building with the highest potential solar energy amount collected is essential in energy planning, environmental conservation, and sustainable development of the city. Estimating the solar energy/radiation from rooftop and facade are indeed having a limitation - the shadows from other neighbouring buildings. The implementation of this solar estimation project for Istanbul uses CityGML LoD2-LoD3. The model and analyses were carried out using Unity 3D Game engine with development of several customized tools and functionalities. The results show the estimation of potential solar energy received for the whole area per day, week, month and year thus decision for installing the solar panel could be made. We strongly believe the Unity game engine platform could be utilized for near future 3D mapping visualization purposes.

The advantages of three dimensional (3D) city models can be seen in various applications including photogrammetry, urban and regional planning, computer games, etc.. They expand the visualization and analysis capabilities of Geographic Information Systems on cities, and they can be developed using web standards. However, these 3D city models consume much more storage compared to two dimensional (2D) spatial data. They involve extra geometrical and topological information together with semantic data. Without a proper spatial data clustering method and its corresponding spatial data access method, retrieving portions of and especially searching these 3D city models, will not be done optimally. Even though current developments are based on an open data model allotted by the Open Geospatial Consortium (OGC) called CityGML, its XML-based structure makes it challenging to cluster the 3D urban objects. In this research, we propose an opponent data constellation technique of space-filling curves (3D Hilbert curves) for 3D city model data representation. Unlike previous methods, that try to project 3D or n-dimensional data down to 2D or 3D using Principal Component Analysis (PCA) or Hilbert mappings, in this research, we extend the Hilbert space-filling curve to one higher dimension for 3D city model data implementations. The query performance was tested using a CityGML dataset of 1,000 building blocks and the results are presented in this paper. The advantages of implementing space-filling curves in 3D city modeling will improve data retrieval time by means of optimized 3D adjacency, nearest neighbor information and 3D indexing. The Hilbert mapping, which maps a subinterval of the [0, 1] interval to the corresponding portion of the d-dimensional Hilbert’s curve, preserves the Lebesgue measure and is Lipschitz continuous. Depending on the applications, several alternatives are possible in order to cluster spatial data together in the third dimension compared to its clustering in 2D.

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.

This paper describes the design of 3D modelling and topological data structure for cadastre objects based on Land Administration Domain Model (LADM) specifications. Tetrahedral Network (TEN) is selected as a 3D topological data structure for this project. Data modelling is based on the LADM standard and it is used five classes (i.e. point, boundary face string, boundary face, tetrahedron and spatial unit). This research aims to enhance the current cadastral system by incorporating 3D topology model based on LADM standard.

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.

Studying at Universiti Teknologi Malaysia (UTM) will ensure academic and technological excellence. The Faculty of Geoinformation and Real Estate (FGHT), established in 1972, focus on education and research for undergraduate as well as postgraduate programs in the related disciplines such as geomatic engineering, geoinformatics, remote sensing, property management and land administration & development. FGHT strives to be a leading academic center in geoinformation and real estate in Southeast Asia. Graduates and alumni form major strong professional societies and work force in the related industries. Many of our graduates end up with good jobs not just in Malaysia but also in other countries (Asian, Middle East, Africa and Europe). The strong team and knowledgeable academic members in this faculty provide excellent ingredients for the success of the programs (i.e. with the relevant and up-to-date curriculum and syllabus). FGHT is continuously working to provide and offer first-class geoinformation and real estate education and research in the country and be at a par with other leading institutions in other parts of the globe. The Department of Geoinformation at FGHT runs a Bachelor of Engineering in Geomatic and a Bachelor of Science in Geoinformatics. At the postgraduate levels, namely M.Sc. and PhD programs, the offered disciplines are Geomatic Engineering, Geoinformatics and Remote Sensing. In the following, the state of the art of FGHT’s postgraduate education in Geoinformation is presented, including a comparison with other universities in Malaysia, program content and curriculum information, alumni statistics as well as future strategies.

This paper reviews the current Geographic Information System (Longley et al.) implementation and status in the Kingdom of Saudi Arabia (KSA). Based on the review, several problems were identified and discussed. The characteristic of these problems show that the country needs a national geospatial centre. As a new initiative for a national geospatial centre, a study is being conducted especially on best practice from other countries, availability of national committee for standards and policies on data sharing, and the best proposed organization structure inside the administration for the KSA. The study also covers the degree of readiness and awareness among the main GIS stakeholders within the country as well as private parties. At the end of this paper, strategic steps for the national geospatial management centre were proposed as the initial output of the study.

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.