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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.

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.

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.

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.

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.

This paper discusses the method of developing Campus Information System. The system can handle 3D spatial data within desktop and web environment. The method consists of texturing of building facades for 3D building models and modeling 3D Campus Information System. In this paper, some of these steps are carried out; modelling 3D buildings, toggling these models on the terrain and ortho-photo, integration with a geo-database, transferring to the CityServer3D environment by using CityGML format and designing the service, etc. In addition to this, a simple but novel method of texturing of building façades for 3D city modeling that is based on Dynamic Pulse Function (DPF) is used for synthetic and procedural texturing. DPF is very fast compared to other photo realistic texturing methods. Last but not least, it is aimed to present this project on web using web mapping services. This makes 3D analysis easy for decision makers.

Land acquisition and ownership for wealth creation has eluded most individuals in various regions of the Earth especially regions described as developing or less developed countries. Most European countries have developed multi-purpose cadastre (MPC) to streamline property ownership. Heterogeneity of space ownership is complex when it has to deal with space ownership above and below the surface. The concept of wealth can be measured as one’s interest in land. This research seeks to introduce a conceptual framework using tools readily available and can be adopted by most countries. Reviews of cadastre being practised in some countries are presented. Concepts within the Land Administration Domain Model (LADM) framework are also presented within the concepts of some standards such as CityGML. The concept for above and below volume parcels is presented. Land package by governments in African countries will help alleviate poverty and create wealth in many African countries. A graphical interface is developed for this concept. The need for a conceptual schema for land volume parcels and marine blocks for countries having borders with the sea or ocean is emphasised.

Recent synthetic aperture radar (SAR) sensors with a capability of providing data with varying spatial resolutions, polarizations, and incidence angles have attracted greater interest for forest biomass and carbon storage estimation. This study investigates the capability of RADARSAT-2 fine-beam dual-polarization (C-HV and C-HH) data for forest biomass estimation in complex subtropical forest, with different types of processing: 1) raw intensity data (both polarizations separately and as polarization ratio) and 2) texture parameters of both polarizations (separately, jointly, and as polarization ratio). Field data (diameter at breast height and height) were collected from 53 field plots and converted to biomass (dry weight) using a newly developed allometric model. Finally, biomass estimation models were developed between SAR signatures from different processing steps and field plot biomass using stepwise multiple regression. All biomass estimation models using radar intensity data (C-HV, C-HH, and ratio of C-HV and C-HH) proved ineffective, but texture parameters derived from intensity data showed potential. We were able to estimate forest biomass amounts up to 360 t/ha with a goodness of fit of 0.78 (adjusted r2) and an rmse of 28.68 t/ha using the combination of texture parameters of both polarizations (C-HV and C-HH). However, goodness of fit could be improved to 0.91 (adjusted r2) and an rmse of 26.95 t/ha for biomass levels up to 532 t/ha using the ratio of texture parameters of C-HV/C-HH. The result is very encouraging and indicates that the dual-polarization C-band SAR sensor has a potential for the estimation of forest biomass, particularly using the polarization ratio of texture measurements, and biomass estimation can be improved substantially beyond the previously stated saturation level for C-band SAR.

While the use of three-dimensional (3D) geographical information system (GIS) is becoming in rapid development and being used in various fields such as urban and regional planning, disaster management and planning, mobile navigation and etc., commercial and open source GIS software packages tend to offer 3D-GIS functionalities for their products. On the basis, GIS analysis functions are to provide information with respect to geographical location and by having 3D spatial data as an input, it will give advantages in providing horizontal position information. However, to analyze moving objects (temporal) in 3D seems not an easy task and not fully supported by current GIS platform packages. Previously in two-dimensional (2D) GIS practice, main issue addressed by researchers in managing temporal spatial objects is GIS packages were designed based on hardware and software constraints whereby it should be based on the temporal spatial objects ontology. Nowadays, the trend of managing temporal 3D data is via 3D spatial simulation or animation. This approach will not in assistance for GIS users in conducting spatial queries. Without having a suitable ontology and valid topological data structure for temporal 3D data, it will cause repetitive of temporal data (redundancy) and complications in executing spatial analysis in 3D environment. Therefore this paper focuses on the ontology for managing moving 3D spatial objects (i.e. air pollution, flood). The characteristics of moving objects were reviewed thoroughly by categorizing it based on its different appearances. Moreover, existing methods in managing temporal database were addressed and discussed for its practicalities. Another important aspect in managing temporal 3D objects is the implementation of topological data structures for 3D spatial objects were reviewed. In the last section of this paper it summarized the issues and further ideas towards implementing and managing temporal 3D spatial objects in GIS based on the Geoinformation Ontology (GeO).

Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.

Uc boyutlu (3B) kent modellerinin farkli alanlardaki kullanimi gun gectikce onem kazanmaktadir. Gelisen teknoloji ile birlikte gercege cok yakin, semantik veri ile butunlestirilmis ve etkilesimli 3B kent modelleri olusturulabilmektedir. Gorsel ve veritabani tasarimi yapilmis 3B kent modelleri konum analizi, pazarlama, acil durum, afet yonetimi, tesis planlamasi gibi bircok alanda kendine kullanim alani bulmaktadir. Bu makalede 3B kent modeli olusturulurken, amaca yonelik gorsellestirme yapilmasinin onemine deginilmistir. Calismanin amaci, Kampus/Kent Bilgi Sistemleri kapsaminda 3B gorsel modellemeye yonelik ihtiyaclarin ortaya konmasi ve bu modellerin internet ortaminda sunulmasidir. Kampus/Kent bilgi sistemleri karar verme, muhendislik uygulamalari, projelendirme gibi bircok alanda imkan saglamaktir. Calisma kapsaminda dijital fotograflar ile ozel doku kaplama teknikleri kullanilarak Karabuk Universitesi'nin sanal olarak uc boyutlu modeli olusturulmustur. Veri toplama ve isleme kismi 3B bilgi sistemleri olusturulurken en onemli asamalardandir. Bu calismada sanal kampus modelinin uretiminde kampus yerlesim plani, sayisal arazi modeli ve 3B bina modellerinden olusan farkli tipte veriler kullanilmistir.

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.

Road roughness is the deviation of a road surface from a designed surface grade that influences safety conditions for road users. Mobile laser scanning (MLS) systems provide a rapid, continuous and cost-effective way of collecting highly accurate and dense 3D point-cloud data along a route corridor. In this paper an algorithm for the automated estimation of road roughness from MLS data is presented, where a surface grid is fitted to the lidar points associated with the road surface. The elevation difference between the lidar points and their surface grid equivalents provides residual values in height which can be used to estimate roughness along the road surface. Tests validated the new road-roughness algorithm by successfully estimating surface conditions on multiple road sections. These findings contribute to a more comprehensive approach to surveying road networks. Resume La rugosite d'une route est la deviation de la surface de la route par rapport a la surface concue, qui influence les conditions de securite pour les usagers de la route. Le balayage laser mobile (MLS) offre un moyen rapide, continu et rentable pour recueillir des nuages de points 3D tres precis et denses le long d'une route. Cet article presente un algorithme pour l'estimation automatique de la rugosite de la route a partir de donnees MLS, ou une grille est ajustee sur les points lidar censes representer la surface de la route. La difference entre les altitudes des points lidar et de leurs equivalents dans la grille fournit des valeurs residuelles de hauteur qui peuvent etre utilisees pour estimer la rugosite a la surface de la route. Des tests ont valide ce nouvel algorithme en estimant les caracteristiques de la surface sur de multiples sections de route. Ces resultats contribuent a une approche plus globale du releve topographique des reseaux routiers. Zusammenfassung Die Rauhigkeit einer Strassenoberflache ist die qualitative Abweichung der tatsachlichen Oberflache von der geplanten Oberflache. Eine solche Abweichung beeinflust die Sicherheitsbedingungen fur Strasennutzer. Mit Mobile Laserscanning Systemen (MLS) konnen schnell, kontinuierlich und auf kostengunstige Weise hochgenaue und dichte 3D-Punktwolken entlang eines Strasenkorridors erfasst werden. Dieses Paper stellt einen Algorithmus zur automatischen Bestimmung der Oberflachenrauhigkeit in MLS Daten vor. Ein Oberflachenraster wird an die Punkte der Strasenoberflache angepasst. Die Residuen zwischen Lidarpunkten und den entsprechenden Hohen des angepasten Gitters konnen zur Schatzung der Rauhigkeit verwendet werden. In Tests mit verschiedenen Strasenabschnitten wurde der neue Algorithmus hinsichtlich der Schatzung der Oberflachenbeschaffenheit validiert. Auf Basis dieser Ergebnisse kann ein noch umfassender Ansatz zur Erfassung von ganzen Strasennetzen angegangen werden. Resumen La rugosidad de una carretera es la desviacion de la superficie disenada que afecta las condiciones de seguridad de los usuarios de la carretera. Los sistemas de laser moviles proporcionan una manera rapida, continua y barata de recolectar nubes de puntos 3-D densas y de gran precision a lo largo de un corredor. En este articulo se presenta un algoritmo para la estimacion automatica de la rugosidad de la carretera, donde una malla se ajusta a los puntos lidar asociados con la superficie de la carretera. La diferencia entre la elevacion de los puntos lidar y los equivalentes en la malla proporcionan residuos en altura usados para estimar la rugosidad de la superficie a lo largo de la carretera. Las comprobaciones validan el nuevo algoritmo de rugosidad de la carretera al estimar con exito las condiciones de la carretera en diversas secciones de carretera. Estos resultados contribuyen a un enfoque mas amplio de la medida de las caracteristicas de redes de carreteras. 摘要 路面平整度是衡量道路表面和设计表面之差的等级,对道路使用者的安全条件的度量。移动激光扫描(MLS)系统提供了一种快速获取低成本、高精确和高密度的沿着路线走廊的连续三维点云数据的方式。本文提出从MLS数据自动估计路面平整度的算法,该算法利用一个路面格网来拟合激光点云,两者之间在高程上的残差值可以被用来衡量路面平整度。试验充分验证了本文所提出的新算法针对多路段路面平整度处理的可靠性,本文的这些发现为路网测量提供了一种更全面的手段。

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...

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.