Abstract – This Study aims to create a framework with an application for modeling a 3D smart city using the 3D cadaster to document, represent, and evaluate the city’s current situation. It covers relationships among different parties, using ISO 19152 as a framework and the International Property Measurement Standards (IPMS), with local regulations as a reference for measurement standards for different types of buildings. 3D Cadaster helps to analyze and represent statistical data through property surveys by using registered properties as a tool for representation and analysis.

The findings show that IPMS 1 is closest to local regulations and sufficient to build a consistent measurement method for properties that support a 3D model. The application can help urban planners and designers understand current city demands and challenges. It also supports trend-based city development by rendering live resident interactions as heat maps, lowering database update costs by linking property registration with statistics.

Keywords – Smart City Planning, Smart City Modeling, 3D Cadaster, 3D Data Modeling I.

INTRODUCTION

A. The Smart City Concept Development

Over the last two centuries, major technological changes have shaped how we define and understand the smart city. This reflects considerable development in the city context and in applied technologies that relate Information and Communication Technology to contemporary urbanism. Table I shows the development of the definition chronologically:

B. The research problems

The city of Zarqa faces several problems: the lack of a long-term cadaster system, the absence of 3D dimensions in the regulations, the separation of plots from buildings in database systems, and the need for up-to-date data to track the city’s development. This study focuses on modeling a 3D smart city based on a 3D cadaster, connecting the statistical data and representing the development of the existing cadaster and framework of the city of Zarqa to include the city’s 3D development, and creating mutual benefits for the public and private sectors in terms of data documentation, urban development, and real- estate property representation.

C. About the Study Area

The governorate of Zarqa is 20 kilometers northeast of Amman. It is an industrial city and the country’s third-largest city by population, covering 4761.3 sq km. The study area is the Zarqa Qasabah district, the city’s commercial and administrative center; it has the largest population among the districts, and the trend of city expansion toward the east provides a better opportunity to apply the 3D cadaster to the newly constructed project. Also, the variety of existing projects, residential, commercial, and industrial, enables the research to use all the IPMS available measurement standards.

II. LITERATURE REVIEW

A. The Limitations of 2D Cadaster

The 2D cadaster was the default method of property registration and city documentation for a long time, creating many registered properties in the database. But it became technologically limited as the city developed vertically, leading to multi-layered ownership in the same plot where layers overlap. The lack of detail in 2D systems and the use of multi- layering create confusion and fail to represent different city components, such as multi-layered roads and underground infrastructure networks [3]. 2D cadastral maps cannot visually describe property space, leading to conflicts between property owners because vertical spaces are inaccurately defined or left undefined [4]. Currently collected 2D data cannot address complex situations, such as city centers [5]. 3D maps can prevent construction in disaster-prone areas [6]. The 2D representation confuses readers about the current situation. Even duplicating existing roads in the area can create a false understanding when relying only on 2D drawings [7]. The current 2D platform no longer satisfies the real-estate owners and developers and needs to represent their properties more sufficiently [8].

B. 3D Cadaster Approaches and Considerations

3D cadaster can be used to create a 3D city; different approaches exist for data collection, data storage, representation, level of detail, and handling existing data. Other countries, such as Norway, Finland, and the Netherlands, took initial steps on regulations in the early 2000s at different application levels [3]. The accuracy of the 3D cadaster depends on the models’ data sources. In Turkey, data come from Photogrammetry and digitized drawings related to photogrammetry and individual units. In comparison, Australia uses data gathered by digitizing survey plans and the accuracy of unit sketches. Furthermore, in the Netherlands, sources include drawings of building footprints in cadastral maps and notarial deeds. In Sweden, the drawings are from property formation dossiers [9]. Stoter drew three possible solutions based on the existing 2D system, considering the existing data infrastructure, the legal considerations of the legal dimension, and the importance of paper issuing the ownership of the units: A complete 3D cadastral registration, a Hybrid solution, and 3D tags in the current cadastral registration system, summarized in Table II.

The core requirement is to support plots in 3D, including the time dimension, representing different versions of the same spatial object, linked with 3D topography, and coupling the other units and their relationships in a 3D context [11]. Based on their details, the models are classified into five categories summarized in Table III.

C. Heat maps

A heat map is a graphical representation of a matrix of colors for individual values in the matrix [13]. Another definition describes it as a rectangular tiling of a data matrix with cluster trees appended to its margins [14]. Heat maps help planners understand and connect statistical results from other fields to develop cities. It supports cross- disciplinary aims by providing a broader understanding of the city [15]. It facilitates reading data using colors. It can be used in a 3D city to understand its vertical characteristics by including its 3D dimensions. The problem of transitioning 2D heat maps into 3D is height duplication, which leads to many errors; this can be solved by double-encoding the value in both color and height. [16].

D. International Property Measurement Standards (IPMS)

IPMS includes 3D property measurement, where indoor space contributes to creating a 3D cadaster based on physical characteristics [17]. IPMS provides a consistent framework for measuring property areas and reporting measurement outcomes across different property types. The standards establish common measurement definitions and rules to improve consistency, transparency, and comparability in property measurement [18]. The IPMS contains four main categories: retail, industrial, offices, and residential. It also includes other subcategories of measurement standards based on the purpose of measurement [19]. In this study, IPMS was selected as a reference framework to compare how local regulations measure property units with internationally recognized property measurement practices. The comparison focuses on how physical components such as external and internal walls, common areas, ducts, and voids are treated. The objective was not to replace the local legal regulations, but to examine the degree of correspondence between the local calculation rules and IPMS measurement definitions and to identify an appropriate measurement basis for the proposed 3D representation of property units.

E. Land Administration Domain Model (LADM)

To achieve the research aims, it is essential to manage all collected data and the relationship structure among all parties involved in the process using consistent standards. Efforts to develop a 3D property cadaster and Land Administration Domain Model (LADM) began in 1994, when FIG Working Group 7.1 published a document that provided key definitions and details beyond general terms of plots by illustrating fundamental property rights, restrictions, and responsibilities. Providing enough information about the land’s current situation and transparency about the plots’ condition are essential to developing the property registration process [20]. ISO 19152 defines the LADM components and covers its essential elements: three main packages and one sub-package related to parties, basic administrative units and RRR, spatial units, and spatial sources (sub-package). It also contains four basic classes: LA_Party, LA_RRR, LA_BAUnit, and LA_SpatialUnit. It integrates 2D and 3D parcels and boundaries.

F. Previous Studies

1. Regional Context – Case study of Dubai The Emirate of Dubai adopted a smart-city definition by offering e-services across the entire urban area and attracting private-sector investment through cost-efficient platforms [21]. The Dubai Land Department registers properties for different transaction processes through approved third parties that conduct property surveys and prepare submissions. For buildings with multiple components, the volumetric site plan requires a separate plan for each component boundary, with unit and common areas separated for management and documentation; towers use a volumetric representation that provides an isometric view of each component from different angles.
2. Local Context – The Greater Amman Municipality Based on the IMD Smart City Index (2025), the Greater Amman Municipality (GAM) ranking is 127 out of 146 [22]. GAM has developed applications and methods to address the city’s problems and challenges. Since 2019, the digitalization process has progressed rapidly during the COVID-19 pandemic; by reducing paper use in government, GAM has added a QR code to the digital version of approved drawings, which can be used later in other processes [23]. But in Zarqa, file submission is still in paper format. The title deed for the flats on the same plot includes no graphical representation or descriptive details to distinguish them from one another. The digitized information includes its number, location, area, owner, and price. However, it lacks graphical/technical presentation or sufficient descriptive analysis to describe the plot and its location in the building.

III. METHODOLOGY

A. Conceptual Framework

Based on the literature review, the current Study’s conceptual framework frames the research’s theoretical background and identifies the principal elements and variables. Developing a 3D smart city is vital to improving the cadastral system, providing feedback to planners for applied regulations, improving the real estate market environment, and leveraging the collected data. The regulations and framework structures were compared with international standards to improve the quality and quantity of the collected data. The created application connects and applies the framework, illustrates the recorded data, and generates heat maps and spreadsheets for the city context, tested and improved based on the participants’ review; the study framework is summarized in Fig 1.

The Australian method of relying on survey drawings is most efficient for the local context because the municipality has already approved it, and a site survey is required to verify the drawings. Highlighting ownership boundaries in 2D and 3D volumetric models in Dubai preserves the rights of all parties. This research provides a detailed 3D volumetric representation for all building types and integrates them into a single simulation model.

B. Property Measurement Standards

The Instructions for procedures and conditions for secretion, registration, and numbering of units and organizing their real estate sheets No.4 for the year 2022 clearly illustrate the unit’s volumetric distribution and the numbering of units and buildings, which depends on counterclockwise numbering for buildings on the same plot. The instructions also support the 3D representation of recorded data for building flats, as per Fig 2.

Fig 2 Units and floor numbering. Source: The Instructions for procedures and conditions for secretion, registration, and numbering of units and organizing their real estate sheets No.4 for the year 2022. This study examined three types of registered projects (residential, industrial, and commercial). The IPMS standard will address gaps in property-distribution laws by selecting projects from each type, analyzing the rules applied to registered units, and summarizing the calculation methods to match them with the nearest IPMS standards.

The AutoCAD drawings and approved drawings are the reference drawings for the calculations. Each building will have three models: the first contains detailed units at LOD3 based on the unit’s area, and the second and third are LOD2 based on the building boundary and legal boundaries, which is better for heat map creation.

C. Property Registration Framework

The survey department registers floors and flats through a registered surveyor. The research combines submission files from various parties, engineering consultants, and surveyors into a new digital submission format, including newly registered building data that falls under the Surveying and Representation sub-package of ISO 19152. The submission format is currently not digital and mainly relies on paper-based procedures or PDF files (special cases). It does not include Unit site plans that clearly illustrate unit details and their location in the building, common area, and parking plans and allocation. Requirements differ between the municipality and the survey department, so the approved drawing may miss details required by one or both departments. The project calculations fall into four main categories: common area, parking sheet, parking summary, and a unit Excel sheet that includes unit area by component and total unit area, allocated parking, ownership percentage, and common area.

2D geo-referenced coordinates represent the project to update and enhance existing records by adding the building boundary to the current database in other departments, and by a 3D model on the geo-referenced coordinates in LOD3 to build a new database based on 3D geo-referenced data that shows the project’s exterior architectural features, with no restriction on the 3D format of the model to simplify the process of transformation. Floor area computation is a CAD drawing containing the polylines used for calculations, and Common area plans highlight the common areas on each floor of the project as summarized in Table V. The transformation of deliverables from surveyors to the survey department and their conversion into digital format, in compliance with ISO 19152, is valid; however, it needs to be rearranged and classified into the equivalent place in the survey sub-package, and additional folders need to be added for submission.

To establish the relationship framework between the parties, the government is the server and client admin that owns all unit data and can access it at all levels; the other parties will be clients. Engineering consultants will be divided into survey and engineering consultants based on their different roles in this process; both will have access only to the plots assigned to them, and unit and plot owners will be able to interact only with their own plots. Table VI Parties and Access levels per ISO 19152. No. Party Access Client/Server 1 Government Full access Server and Client 2 Consultants Assigned plot Client 3 Owner Individuals Owned plots/units Client 4 Tanent Rented plots/units Client 5 Visitor View only Visitor

D. Simulation Method

The Hybrid model used in city modeling is based on 2D plot modeling and 3D building representation. The 2D plot is extruded in LOD1, whereas the building modeling is based on the legal spaces of the units. The level of detail includes the exterior architectural details of the units as per LOD3; another building model, based on a simple floor shape in LOD, is shown in Fig. 3.

E. Heat Map Generation

Population density depends on the inhabitants of individual units. The data can be gathered from those who rent/buy those units. Once their data is included for the unit and registered in the system, the total number of residents on each floor and plot can be known with high accuracy, along with the vertical distribution across the city. This improves population statistics, keeps them up to date, and supports more appropriate development in selected neighborhoods. The properties’ status can indicate the results of strategies that planners and developers applied successfully by knowing the occupancy ratio in specifically targeted developments and successful building types, and generate a heat map for the rent/sell prices for the properties that help to develop better models for real-estate development and create feasible units for the residents. The relationship between different land uses can be mapped as a heat map and linked to density and the real estate market by combining services with their neighborhoods and analyzing whether current services meet the demands of the study area’s population.

IV. ANALYSIS

A. The Unit Calculations Between Local and IPMS Standards

Local regulations do not clearly define the boundaries or subdivision of unit components. Also, there is no difference in the calculation method between different types of properties, the registered projects, and the common practice of surveyors, Table VII highlights the differences between different calculation methods.

The comparison between the local and IPMS standards for a residential building shows that IPMS 1 is the closest standard to the local regulation for this building type, with less than 2% differences for each unit area. For industrial buildings registered as whole buildings for the owner or multiple owners, the unit calculations in the local regulation and IPMS 1 are equal. For offices and retail, IPMS 1 was the closest standard for both types; the difference is that ducts within the unit are calculated per local regulations. According to the selected projects, the maximum difference in area between local regulations and IPMS 1 does not exceed 2% (between 0% and 1.88%). But Table VIII highlights the differences in 3 buildings in detail (mixed-use, residential, and industrial). Table VIII Summarize the comparison for the 3 buildings across the 4 types of area measurements, including the total unit area calculated under each standard.

B. Developing the Submission Framework Structure of the Municipality

The preparation of a survey folder in digital format, to be used for heat map generation and digitalizing the real estate process, making it usable and feasible for all parties; the types of submission folders that surveyors prepare are: CAD drawings, Excel spreadsheets, PDFs, and 3D models; files can be arranged as Fig 4. The surveyor provides the source of as-built drawings in the submission. After checking the existing approved CAD drawings from the system and being assigned by the owner, the surveyor prepares the georeferenced and Unit site plan according to the site conditions. The surveyor provides the polylines used for calculations in floor sheets; the calculations for common areas, parking, and units are combined in one Excel sheet to distribute common areas and unit ownership. To verify that the BUA of units is complete, surveyors create only PDF files of unit site plans, which provide a graphical representation of the units to meet clients’ needs for 2D property representation.

The 3D model of the surveyed project contains three sub- models. The first is the model built at LOD3, showing the exterior architectural details of the unit, used for city representation in the 3D model, which gives aesthetic value to the 3D city, satisfies the real estate owners by integrating a 3D model layout showing the building features, and protects the privacy of the boundaries of the legal spaces in case of other clients who use the system (other building owners, visitors, consultants who are not assigned); the floor model is built at LOD1 level to prevent distortion of the spreadsheet’s creation of a 3D heatmap, and individual units are based on the legal space boundaries, as shown in Fig 5 which is the arrangement of the surveyed data and documents constructed based on the Table V. Blender was selected as the 3D modeling and preprocessing environment because it is open-source and provides a flexible, cost-effective solution for creating and preparing 3D building models.

The proposed methodology is not intended to be dependent on a single proprietary modeling software. Therefore, models produced in Blender or other compatible modeling environments can be incorporated into the workflow, provided that their geometry, coordinate reference system, and relevant semantic attributes are appropriately structured.

C. Integrating the Surveyed Data into Unity Engine (Buildings)

Unity was selected primarily as the application, visualization, and simulation environment. Its flexibility allows the proposed system to integrate survey data, statistical information, documents, images, and interactive 3D visualization within a hierarchical city model. This makes it suitable for developing an interactive environment in which information can be associated with buildings, plots, and city- level objects and subsequently extended with additional classes and attributes according to the requirements of the proposed methodology. Unity also integrates with GIS and mapping platforms, including ArcGIS Maps SDK and Google Maps-related services, to support spatial information and geographic context. Elements will be parented according to the city’s hierarchical structure, starting with the most significant level: directorates, villages, basins, and plots. The previously rendered and calculated residential complex is used as a sample for unit registration and digitalization in Unity Engine. Fig 6 Shows the application of hierarchical structure, details of arranging the registered project, and arranging the three models under the plot.

The system allows the government to summarize data through visual feedback and export it in CSV format by floor level and plot number, population, and average price, color- coded by floor based on the total number of inhabitants for each unit on that floor. To address distortion in the Excel sheet and 3D data, use standard floor numbering. This removes height differences between buildings and includes different building types, such as towers and individual houses, without distorting the data output because all registered units belong to a specific floor. The application can represent the statistical data without distortion by storing it in the legal space attribute for each unit and transferring it to the floor attribute, which is unified across buildings in different plots and unaffected by height.

D. Integrating the Surveyed Data into Unity Engine (Urban scale)

The study area is in Zarqa Qasabah, as mentioned in the introduction, and consists of 1571 plots with a total land area of 1.45 sq km. Using Blender to model the study area in LOD1, where the height of the plots indicates the height of existing buildings over them. Fig 7 Show 3D rendered images for the modeled study area.

Creating separate plot models adds individual scripts to test the connectivity of Study Area elements, separating the analysis for each plot to provide precise results. Because existing data are limited, the plot is the smallest unit for heat map generation in the study area. Each plot identifies surrounding transportation points (bus stops), parks, and schools and automatically selects the closest transportation node as a reference point by calculating the distance between their geometric centers.

E. Updating the Existing Models of the City Model

Updating all existing buildings in the city at once is not practical in terms of time and resources. In addition, the government will need massive resources for the digitalization process from the start. The currently available digital physical data of the plots is the plot boundaries only, which is sufficient to generate the 3D heatmap of the study area and analyze the 3D structure of the city by extruding the plots at LOD1 level for the occupied plots and creating empty child objects to indicate the interior units, which allow the registration of different data for the smallest unit in the system. 3D city modeling can better represent Department of Statistics data in a virtual environment parallel to the physical environment, reducing the costs of updating the data. It also automatically connects different statistics, allowing the planner to move across scales based on the latest data. Furthermore, this modeling technique saves planners the time and cost of gathering data manually and integrating efforts from different fields, supporting their goals of planning better cities and improving existing ones. For building or plot updates in the 3D structure, this can be done at runtime by replacing old elements with new ones without affecting data for other plots and buildings. However, when adding new features to generate statistical or heat maps, the Unity scene must be restarted; it won’t affect previous data because it is saved automatically during runtime.

F. Applying the Application in the Study Area

In the selected study area in New Zarqa, the major problem is a lack of open areas that serve residents. Fig 8 Shows a lack of open spaces for residents. Only one open public space is in the east of the study area (Abdul Hameed Shoman Library Zarqa – previously known as Arab Bank Park). To allocate another open space for residents, the service plot for the government allocated to be an open public space is highlighted in Fig 9.

Fig 10 Shows the results of the land use change solution by switching the land use of the two areas to parks. The objective is to evaluate how the proposed open spaces could benefit from the surroundings.

We used a 500-meter threshold to identify plots affected by land-use change, calculated from centroid to centroid; for computational efficiency in large- scale areas, the analysis used squared Euclidean distance between plot centroids. We compared the calculated value with the squared 500 m threshold to determine whether the plot fell within 500 m. This approach produces the same threshold classification while avoiding square root operations.

Fig 9 Selected plots to change land use to address the lack of open spaces. Source (DWG and Land use map): GIS Department of Zarqa; modeled and coded in Unity Engine.

V. APPLICATION TESTING AND FEEDBACK

A. Sample Picking and Assigned Tasks to Individuals

Track users’ experience by observing their behavior to explore the problems they may face during use. A survey measured users’ satisfaction with the application, and we considered their comments and recommendations for future development. The tasks given to users fall into two main sections: government tasks and client tasks. In both roles, the users will be able to extract different data about the properties and interact with the city elements, summarized in Table IX. The total number of participants was 50 people from various backgrounds;

66% were male, and 34% were female. The 20 to 29 age group was the largest, at 50%, and the 30 to 39 age group ranked second at 30%. In addition, 48% of the test group had a bachelor’s degree (the largest group), 22% had a master’s degree, 60% of participants were tenants, and 40% were owners;

The educational background for the participants and their numbers are:

• accounting (3),
• architecture engineering (19),
• business administration (4),
• civil engineering (3),
• electrical engineering (1),
• IT (2),
• land survey (2),
• law (1),
• mechanical engineering (5),
• students- architecture (4),
• survey engineering (6).

Participation in the application evaluation was voluntary. Participants were informed about the purpose of the evaluation and were invited to try the developed system on independent devices. They voluntarily agreed to participate. No written informed consent was obtained, and no personally identifiable or sensitive personal data were collected.

Table IX List of governmental and client tasks, along with average estimated time (in minutes) and success rate for each task.

B. User Experience and Results

Table X Shows users evaluated the tasks separately and provided short answers about difficulties and recommendations for improving the application. The user feedback survey included open-ended questions about satisfaction with each function and task output, and about improving the software’s characteristics. The goal was to make it usable for users from different backgrounds, help planners use the recorded data, and expand the availability of recorded data for planning at different scales. Most users were delighted with task completion in terms of viewing and achieving it; their recommendations to improve the user experience reflected their work background. Such as: improve user control by implementing two ways of movement by using arrows and touch screens to match with the tablet devices or touch screens; similarly, add zoom-in and zoom-out scrolls, add indicators for the public building and major places in the area to easily identify the desired place, and add a mini map showing the location of the user.

Table X The evaluation of users for each given task in the government and client user experience (Extremely dissatisfied:1 to Extremely Satisfied: 5).

VI. DISCUSSION AND CONCLUSION

Current laws and regulations support the concept of a 3D environment conceptually, but lack solid references and regulations. The problems of creating a 3D smart city are technical, with a lack of a digital format for building documentation and a legal registration form. The current submission deliverables can be reframed and digitized as a survey sub-package. Therefore, using the IPMS 1 standard to develop the local regulations and support 3D legal spaces will create a solid reference calculation method. Replacing the plot model in LOD1 with the building and plot model in LOD3 through the registration process. This creates a connection between buildings, the plots database, and an integrated data infrastructure.

A 3D city model creates a parallel environment to the physical city and can represent different statistical data in 3D. This helps planners understand the city’s function in the vertical dimension and link the effects of land-use planning policies to socio-economic impacts, based on up-to-date data, saving time and reducing the cost of additional survey studies. 3D city model can be an open-source database to provide transparent data sources in the city and raise awareness of the importance of different land uses, transportation routes, and provided services by selecting the appropriate living and working place based on the individual needs of people and providing up-to-date statistics and 3D accurate models for further studies. Lowering the cost of 3D transformation and database updating by making it part of property registration, because the property and its statistical status will be updated automatically during the property transaction process. The created application and framework can achieve multiple definitions of smart cities in the literature. Pierce, Freed, and Townsend define it as connecting public services with dynamic city data, driving innovation in public services, and improving long-range planning [2].

Digital City by Ishida and Isbister. It creates 3D interactive plots and buildings and automatically matches each plot and building to the nearest service by shortest distance, aligning with Komninos’ definition of an Intelligent City. The application can connect plots and buildings to the nearest bus route node, creating a connection between them and aligning with Graham and Marvin’s definition of a Cipher City [1].

Furthermore, a standardized data organization format connects different governorates and departments, supports regional planning policies, and uses local regulations and IPMS standards to ensure stable, transparent outcomes regardless of project type. The application can include more city data by registering services and utility buildings in the smart city model and understanding their relationships. Moreover, by understanding these relationships, planners can identify shortages that may occur due to population density changes over time and real estate market development, enabling more accurate decisions and plans. The current scripts support studying the integration of transportation networks with different utilities and population statistics representation.

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