doi: 10.24191/myse.v9i3.18289
CITY INFORMATION MODELING AS A TOOL FOR PROBLEM IDENTIFICATION AND SOLUTION IN
URBAN SPACES DEVELOPMENT
Gregorius A Gegana A1*, Felia Srinaga1 & Julia Dewi1
*Corresponding author
1Universitas Pelita Harapan, Architecture Department, Tangerang, Indonesia
*[email protected], [email protected], [email protected]
Received: 16 December 2021 Accepted: 25 February 2022
Published: 30 June 2022
ABSTRACT
Abstract. Many of our decisions in urban planning depend on details of our immediate surroundings and require information about the specific place on Earth. In this digital collaboration era, problems and information about cities and regions can extend rapidly. Therefore, architects and urban designers need tools that can capture this information immediately to help in urban evaluation and design. Building Information Modeling (BIM) has changed the way architects and designers work and collaborate in building design. This swift collaboration workflow should be applied in urban and infrastructure design byutilising BIM tools that can harness the data from Geographic Information System (GIS), therefore conceiving the terms City Information Modeling. This paper discusses how the sutilisation of City Information Modeling tools has been explored and workflow as well as integration that can be improved further for evaluating urban space problems and solutions. The study is run through two courses held at the Department of Architecture Universitas Pelita Harapan that explor the tools to harness GIS data, sanalyse urban spatial, and collaborate in urban space planning. In these courses, students take study cases in two places:
Jakarta and Medan, which has an old city area that has a significant impact on overall city development. The research looks at workflow, sutilisation of the software through students’ learning outcomes, and students’ work.
© 2022 MySE, FSPU, UiTM Perak, All rights reserved
Keywords: City information modelling, Urban space development, Digital collaboration.
INTRODUCTION
A survey conducted in an urban area can contain much information; thus, it will be useful to conduct further urban analysis (Dofey & Pafka, 2018) (Schwalbach, 2009). Conducting urban analysis can reveal the overall picture and get detailed information about specific issues (Schwalbach, 2009). Many of our decisions depend on details of our immediate surroundings and require information about the specific place on Earth. This information is called “geographical” because it helps us distinguish one place from another and make decisions for that place (Bernhardsen, 2002). Many aspects in urban areas can be described by using maps as a practical tool to get information or as a medium for scontextualising the different results of analysis (Schwalbach, 2009). In this digital collaboration era, problems and information about cities and regions can extend rapidly. Therefore, the designer needs tools that can capture this information immediately to help in urban evaluation and design.
Geographic Information System (GIS) is a framework for gathering, managing, and sanalysing data about specific places on Earth. It analyses spatial location and sorganises layers of information into svisualisations using maps and 3D (ESRI, 2019). Input data for GIS come from satellite imageries, maps, Global Positioning System (GPS), survey data, and other instruments for attribute data (Elangovan, 2006). This real-world information is processed and stored so they can be presented later in simplified forms to suit specific needs (Bernhardsen, 2002). Previous studies have shown that integrating GIS has advantages in analysis and solutions for complicated decisions. Integrated GIS-based land suitability analysis can provide valuable guidance for future land-use changes and cost-effective solutions in cities (Hassan, 2017). Remote sensing and GIS are able to measure the vegetation thermal comfort parameter based on three characteristics to determine the internal and external factors of heritage trees (Yusof, Hussain, & Rusli, 2019).
Commonly, all geographical information was represented in a 2D graphic with a map. However, traditional drawing and map reduce the spatial description of 3D objects to 2D (Abdul-Rahman & Pilouk, 2008).
Next generation of GIS requires a new way of spatial data modelling, called 3D GIS. Some disciplines need 3D model representation to complete their job efficiently. As an architect, designer, or engineer we can use this 3D GIS information since we are working with 3D space all the time. Building Information Modeling (BIM) has changed the way people work and collaborate in building design, specifically in 3D collaboration. This swift collaboration workflow should also be applied in urban and infrastructure design by sutilising BIM tools that can harness the data from Geographic Information System (GIS), thus coining the terms City Information Modeling (CIM).
OBJECTIVE
The main objective of this research is to observe how the CIM tool can be explored for evaluating urban space problems and solutions primarily in architecture education purposes. The research involves six architecture students to do data collection and mapping using CIM. Therefore, the researchers can get faster insight and present better analysis and solutions.
The research looked at the advantages, setbacks, prerequisites, results, workflow, and integration with other GIS repositories and architectural BIM tools. Finally, it discussed further sthe utilisation and improvement that can be made using the software to sanalyse and provide the urban solution.
METHODOLOGY
The study is carried out through the courses held at the Department of Architecture Universitas Pelita Harapan (UPH) that explore the tools to harness GIS data, sanalyse urban spatial, and collaborate in urban space planning. The course is an elective course named Urban Simulation and Analysis which was held in collaboration with the mandatory course Urban Theory and History. The first course equips the students with technology pedagogy and tools, while the later course lays the fundamental theory in examining spatial urban issues. In these courses, the students choosetwo
places for the case study;Kota Tua (Jakarta) and Kesawan (Medan). The two cases were chosen since they have an old city area that significantly impacts overall city development. The project was carried out in two groups.
The main software used is Infraworks to model and simulate the urban spatial conditions. Infraworks is conceptual design software that lets architecture, engineering, and construction professionals model, analyse, and svisualise infrastructure design concepts within the context of the built and natural environment (Autodesk, 2021). It is used in conjunction with other BIM software: Civil 3D, Revit, Form It, and SketchUp to integrate further with architectural design and provide detail of buildings. This research also uses Recap to integrate survey data in the form of point-cloud geometry. Further, non-spatial data is generated in the software from the ArcGIS platform.
GEOGRAPHIC INFORMATION SYSTEM AND BUILDING INFORMATION MODELING
According to (Gurugnanam, 2009), there are four elements of GIS, i.e.:
•hardware: computer platform, input, and output devices
•software: data input and extraction modules
•data: spatial, attribute, global database
•liveware: human resources
The geographical dataset consists of spatial data and associated non- spatial attributes, creating information about that geographical location.
Spatial data refer to as “mappable” characteristics, such as location according to the geographic referencing system or address system, size, and shape. On the other hand, the attribute is a descriptive characteristic about that spatial data (Davis, 2001). Parallel to the BIM principle which has 3D geometry and property data (hence called “Information”), Infraworks as CIM software can pull out GIS data in the form of spatial (3D geometry), attribute (property) that is linked to the geometry, and global attribute data.
Figure 1. Automatic Model Generation for an Urban Area Kota Tua Jakarta.
As stated in the model description, this model contains information from OpenStreetMap, which is made available under the Open Database License (ODbl). Terrain data for the United States and its territories use USGS 10-meter DEMs from the National Elevation Dataset (NED). Between -60°
and +60° latitude, we use SRTMGL1 30m DEM data. Between +60° and +83°, we use ASTER GDEM v2 30m DEM data. ASTER GDEM is a product of METI and NASA. Land Processes Distributed Active Archive Centre (LP DAAC), 2001, ASTER Global Digital Elevation Model (GDEM). Version 2. NASA EOSDIS Land Processes DAAC,s USGS Earth Resources Observation and Science (EROS) Centre, Sioux Falls, South Dakota, accessed January 21, 2016.
Input data for GIS come from satellite imageries, maps, Global Positioning System (GPS), survey data, and other instruments for attribute data (Davis, 2001). Therefore, GIS dataset is communal data collected from various sources by many people. As the internet give rise, GIS data is stored in an online database service where people can access and contribute to the stored data in many ways. In this aspect, Infraworks as CIM software distinguishes itself from other BIM tools for architectural design. As in other BIM software, 3D geometry can be added manually by the user.
However, by having GIS capability and connection to various GIS databases, the 3D geometry of an urban area can be generated automatically.This includes topography, buildings, roads, public transport route, and other infrastructures. The 3D geometry also comes with its attributes such as name, function, area, volume, length, elevation, etc. Therefore, designers can build the urban area quickly for preliminary data. The example of automatic model generation of an urban area can be seen in Figure 1.
Integration workflow
The automatic build of an urban area can give us a quick glimpse and general data of the area. However, the data still can and may need to be verified, tweaked, improved, and detailed through various means. One of them is through integration with other BIM software and GIS platform.
Aligned with the learning pedagogy of digital architecture technology in UPH, the study also semphasises the workflow and interoperability between software and platforms. In this study, the research tried to explore different aspects of workflow and interoperability, particularly:
•Exporting urban models and data to other BIM design software
•Adding 3D geometry building and 3D scanned survey data to an urban model
•Extracting data from online GIS repository
Exporting urban model and data to other BIM design software As an architect, we can sutilise an urban model and data from the CIM platform in the BIM building design process. GIS data and model generated from Infraworks is useful for:
1.Establishing existing site context in the form of 3D geometry of topography and elevation, as well as neighbourhood building and infrastructure 2.Working in collaboration with a shared coordinate system using GIS/GPS
coordinate system. This is crucial in master planning with several buildings and coordination in the site plan.
Figure 2. Urban model from Infraworks (left) can be Sutilised to Provide Site Context for Building Design and Master Planning in Revit (right) Source: courtesy of class (2016)
From Infraworks, 3D geometry and coordinate system are imported separately. Therefore, there are two different methods to bring them into BIM design software. Both elements cannot be read directly in Revit, we also need two additional software to translate them. In this case, we use Form It and Civil 3D to convert geometry and coordinate system, respectively.
Figure 2 shows the result example of sutilisation of urban model as site context and master planning in BIM software.
The main challenge in this interoperability is that GIS and BIM use
two different coordinate systems. GIS is based on a geographic coordinate system, such as latitude-longitude. On the other hand, although the location information is based on latitude-longitude, BIM uses a local/ projected coordinate system in its geometry, such as northing-easting. Therefore, the Infraworks model, Civil 3D, and Revit must be calibrated and ssynchronised based on the projected coordinate system. Civil 3D acts as the translator for this.
Figure 3. Workflow to Export Urban Model from CIM Software to BIM Software
Source: class materials
In geometry aspects, 3D geometry from Infraworks is exported as FBX format. This makes the geometry lose all its attribute information such as name, function, etc., as well as geographic coordinate. In BIM software, this geometry is just read as fixed geometry without information/parameter.
Furthermore, it needs to be adjusted manually for its position. However, as the purpose of this geometry is to provide site geometry context visually, such losing of information is acceptable. The overall workflow to export and sutilise 3D urban model and its coordinate system from CIM to BIM software is shown in Figure 3.
Adding 3D geometry building and 3D scanned survey data to urban model
In reverse of the previous workflow, we can add more detailed 3D geometry for the buildings from BIM or generic 3D software, replacing a 3D generic building generated from the automatic model builder.
Figure 4. Workflow to Import 3D Building Geometry or Point-cloud Data to Urban Model in Infraworks
Source: class materials
The workflow for this interoperability is relatively simple, as shown in Figure 4. After import, the building can be positioned manually or specifically by inputting its location coordinate such as latitude-longitude and elevation from the sea. Building geometry from BIM and point-cloud data of aerial drone scans usually have geographic coordinate information.
This coordinate also can be synced automatically. Attribute data such as building description and function can be added in its properties manually afterwards.
It is also possible to add point-cloud data resulting from field survey and 3D scan of building or terrain as shown in Figure 5 below.
Figure 5. 3D Scan Result in Recap (left) and Placed on Urban Model as Point Cloud data in Infraworks (right)
Source: class materials
Extracting Data from Online GIS Repository
Infraworks has the capability to connect directly to ESRI ArcGIS, one of the biggest GIS platforms and data repositories. Inside Infraworks, we can use an ArcGIS connector to connect with the ArcGIS repository and search the data we want. Data from ArcGIS will be translated and presented in Infraworks as the feature (3D geometry) such as pinpoint, area, and building. It also comes with additional attribute data such as address and type if specified in ArcGIS. The example of connecting and translating ArcGIS data to a 3D urban model in Infraworks is shown in Figure 6 below.
Figure 6. ArcGIS Connector (left) and Translated into Feature in Infraworks (right)
Source: class materials
The main obstacle in this pipeline is the data availability itself.
According to (Gurugnanam, 2020), live ware, i.e., human resources is one of GIS elements. Furthermore, (Elangovan, 2006) states that GIS dataset is communal data collected from various sources by many people.
Consequently, what is the data that is available in ArcGIS depends on who and how many people create the data of urban/ regional area inside the repository in ArcGIS. We cannot extract the data that is not available, particularly in public domain. In developing country and city such as Jakarta, it is still difficult to find complete data about urban infrastructure and analysis that is open to public.
RESULTS
The student worked in a group of 3 people. The first group took a case study in the Jakarta Kota Tua area, while the second group took Kesawan area in Medan. Both are old city areas which have different characteristics.
The area in Kota Tua they took includes some blocks of buildings covering about 16.4 ha, including the Kali Besar river, and roads across the river.
On the other hand, Kesawan area covered about 40.1 ha, spanning along the main road with two nodes at each end. The characteristic differences between the two cases, led to different analysis approaches.
Kota Tua Jakarta is an old area with many historical building built in colonial period. As a historical area, some building in Kota Tua is strictly preserved but still maintain its function for business purposes. Kota Tua as preserved area has become an attraction for tourists. Furthermore, the tourist activities and the business make the uniqueness of this area. Kesawan, also known as old town area, is a business district with an exciting arcade on the building facade. This arcade creates a strong path along the street thus it made this street an important element to examine further.
Table 1. Summary of Kota Tua and Kesawan Area
Kota Tua Kesawan
Development area 16.4 ha 40.1 ha
Location Jl Kali Besar
West Jakarta Jl H.M Yamin
Medan, North Sumatera
Coordinate -6.1,106.8 3.5,98.6
Boundaries North: highway West: river road South: road/ flyover East: office buildings
North: arterial road West: river South: road East: railroad Notable Landmarks Kali Besar River
Kota Station Museum Fatahillah Museum Wayang Museum BI
Museum Bank Mandiri Tjipta Niaga Building
Tip Top Restaurant Tjong A fie Mansion London Sumatera Bldg.
Old buildings along the main road
Area attribute Pedestrian/ tourist area Business district Four lanes road (daytime) Pedestrian/ market (night) Source: Author
Figure 7. Development area of Jakarta Kota Tua (left) and Medan Kesawan (right)
Source: Google MyMap
The final output of the study required students to use all technical knowledge they acquired about the capabilities of Infraworks and related software/ platforms in BIM/ CIM workflow. There are 2 phases of the study that they need to attempt sutilising the urban model:
1.The students had to sanalyse and svisualise the data about the existing conditions of the urban area. This analysis was done based on their Urban Theory and History knowledge.
2.The students had to develop an idea or concept of urban development and design based on the previous analysis.
In both phases, it was essential to show and explain quantitative aspects of the urban area through the model, such as area; road length, lane width, profile, and class; street furniture; infrastructure; buildings count, function, and changes; and open space area. The model of road, open area, and buildings had to be detailed to show users’ experience. The first automatic model initiation is a brief area model with generic building blocks and conceptual roads. To make it accurate, they had to:
1.Verify the model with actual conditions. Due to the pandemic, the verification can only be conducted virtually through Google Street view. The Drone 3D scanning and point cloud data also could not be added due to the situation. Fortunately, the area is in the city they have lived until now. Therefore, they know the area very well.
2.Make necessary adjustments to the initial model. The empty spatial model
big city in Indonesia that is well known and reachable by GIS data contributors such as Google Streetcar and satellite. Therefore, the additional rework was minimal. However, the building blocks that show important landmarks had to be remodelled in other 3D/ BIM software.
Figure 8. Some of the Landmark Building in the Area need to be Remodelled in Detail in other 3D/ BIM software. Landmark in Kota Tua
Jakarta Area (left) and Medan Kesawan Area (right) Source: courtesy of class (2018)
Kota Tua Jakarta
The urban dimensions can be scategorised as morphology, perception, social, functional, and temporal (Carmona, 2003) As shownin Figure 9, the group semphasised blocks analysis by looking at these dimensions, particularly street block, pattern, building structure, building function and landmark, positive and negative urban space, building height and housing, and roads class/ function. Some of these data, such as building function, need to be identified manually and inputted as attribute data inside properties of building model before can be visualised. Conversely, the data that is based on geometric reading such as building height and road width can be svisualised automatically.
The concept design they tried to develop aims to enhance pedestrian quality, respond to DKI governor regulation about MRT Kota Tua, add programs along the river, and bring adaptive reuse to the building. The design took the road segment on the riverside and converted it to a fully pedestrian plaza with market activity and an MRT exit, as shown in Figure 10. However, the adaptive reuse concept for the building could not be shown in the urban model as it takes place entirely inside the building and does
not connect to the plaza outside.
Figure 9. Building Blocks Map Svisualisation based on Morphology Dimension of Street Block and Pattern, Building Structure, Functional Dimension and Landmark, Visual Dimension Urban Space, Housing and
Building Height, and Roads Class/ Function Source: courtesy of class (2018)
Figure 10. Design Concept of the Area Along River becomes Pedestrian Plaza Connecting the MRT exit to Kota Tua Area
source: courtesy of class (2018)
Kesawan Medan
The old city Kesawan area in Medan is spanning along the main road Jl H M Yamin. The group focused the study on road activity and its relation to the old buildings and landmarks. As can be seen on Figure 11, the road activity changes during daytime and night-time. In the daytime, the road with 4 lanes, as shown in Figure 12, is fully occupied by smotorised vehicles. All lanes are one way, but the most left lane is used for parking. In the night-time, the roads are closed for the night market and pedestrian activity. This road activity information needs to be inputted manually as attribute data inside the road model. The function and old buildings category are shown in Figure 13. These old buildings’ façade makes a unique experience, continuous along the road, and the group intended to preserve this.
Figure 11. Landmark Buildings Location (top-left) and Area Boundary by River and Railroad (top- right). Changes of Street Activity from Daytime
which is Dominated by Smotorised Vehicle (bottom-left) to Night-time which is Dominated by Pedestrian and Night Market (bottom-right) Source: courtesy of class (2018)
Figure 12. Road Visualisation, Section, and Station/ Profile Analysis Source: courtesy of class (2018)
Figure 13. Building Blocks Svisualisation based on Function Analysis (top) and Old Buildings Category (bottom)
Source: courtesy of class (2018)
As shown in Figure 14, the design concept is also heavily focused on road design. The group tried to change the activity that happens now by changing the lane and section of the road. Instead of having four vehicle lanes, they converted 2 vehicle lanes into one wide pedestrian lane while still having two other vehicle lanes for cars and motorcycles serving the area.
Thus, changing the class and function of the road. This wide pedestrian lane is packed with street furniture, vegetation, and activities. Combining with continuous old buildings’ façade, this can give an even better experience for the pedestrian in enjoying the old city not just during the night-time, but also during the daytime.
Figure 14. Concept Design of the Main Road to Accommodate more Pedestrian Activity in Daytime and Night-time as well (top) and Road
Planning, Section, and Profile (bottom) Source: courtesy of class (2018)
Assessment
Both groups sutilised the CIM software and workflow for different design purposes and analysis. The sKota Tua group emphasised building blocks morphology, function, and devised the design concept for plaza area and adaptive reuse of old building interior. On the other hand, the group of
Kesawan highlighted the road activity, experience, and focused the design to convert the road into more pedestrian-friendly while not eliminating vehicular access.
In the analysis phase, both groups were able to svisualise the data in urban model very well; whether it is building blocks, landmarks, urban space morphology; or road function, section, and activity. In this phase, using CIM software can accelerate the creation of initial city mapping in 3D for buildings, land contour, water bodies, and infrastructures such as road and rail. However, there are some limitations, As the model was built automatically, most of the components, such as roads, were built by using the default template and existing map data. Therefore, the road lanes and width might not come correctly. In some area that is not reachable by GIS data contributors, some of the building block was not generated or not correctly generated especially for the landmarks. The solutions for these problems were relatively easy. The road lanes and width can be changed from its parameters. Building blocks, landmarks, and its façade textures can also be added manually or imported from other software.
In the design phase, only design in open areas such as plazas and roads could be documented well. Thus, the concept that involves building the interior and its relationship with an outdoor area such as adaptive reuse, could not be communicated. This is understandable because the GIS and CIM mainly accentuate on the urban model. The building model itself was mainly modeled as generic blocks with façade material for graphic memory performance. To further highlight the correlation with building interior, especially on the ground floor, the building model had to be modelled in detail in BIM software and integrated into the urban model. However, floor plans and sections of the building could not be shown directly in Infraworks.
In this matter, integrating the CIM model from Infraworks into BIM software for architectural design is essential to present floor plan and section and its relationship with outdoor/ urban area.
BIM is a workflow for modeling the building with its integrated information and resulting BIM model that can be enriched and used for various purposes. Integrating it with technology such as IoT, VR/AR, and AI;the BIM model can evolve into a digital twin for the building. Similarly, CIM is also a workflow for modelling the city with its integrated information,
resulting in the CIM model. This model information can be further enriched, resulting in a digital twin for the whole city. Digital twins of smart cities can enable better planning of construction as well as constant improvements in municipalities (NVIDIA, 2021).
CONCLUSION
This paper has presented how the CIM tool was explored to evaluate urban space problems and solutions. The initial model automation is very useful for quickly giving insights about spatial geometry and its attributes. Beyond an initial point, the urban model resulted in need to be verified and integrated with a more detailed model from BIM to provide detail geometry and experience visualisation. Some spatial and attribute data could be grabbed from the online GIS repository and added to the model. Otherwise, it can also be inputted manually in geometry properties. sDigitalisation should be seen as a workflow and system; thus, it is not just a tool to create a model or drawing. Therefore, it is important to semphasise the workflow and interoperability between software for various purposes.
Utilisation of CIM software can help both in the analysis and design phase. In the analysis phase, it can svisualise and present the data and analysis based on embedded attribute data in geometry. In the design phase, it can help the modeling itself and svisualise the design concept or idea.
This is one example of how technology can help to sanalyse urban problems through modelling the urban area. Nonetheless, the use of CIM software that we have explored is still limited to data presentation and visualisation.
There are simulation features such as vehicle traffic, human movement, and flood simulation that have yet to be explored. Further potential of CIM is integrating all urban information into the model and using the game engine, it can be made interactive and publicly available online, resulting in a digital twin for a city. Future research can take these aspects into account.
ACKNOWLEDGEMENT
The authors truly appreciate the contributors for the data, especially our students at UPH Architecture, namely: Bobby Wijaya, Elben Erjanto,
Michele Melody, Ersalina Trisnawati, Wilbert Tanaka, and Jessica Ivana.
We also thankful to all reviewer that already give some inputs and to the Center of Research and Community Development services (CRCD) Universitas Pelita Harapan (UPH) that funding part of this research.
FUNDING
There is no funding for this research.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
AUTHOR CONTRIBUTIONS
All authors contributed to the design of the research, the questionnaire, and the write-up. The on-line survey, data cleaning and tabulation was undertaken by researcher. All authors have read and approved the final manuscript.
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