The Power of City Information Modelling for Smarter Urban Monitoring

India is a rapidly urbanising nation with nearly 600 million population projected to reside in the towns and cities by 2036. Many urban challenges such as urban sprawl/ unplanned ex­pansion of cities, spontaneous growth of informal settlements, rising levels of pollution, ecological degradation, severe traffic congestion, housing shortages, inadequate infrastructure and inefficient land use patterns, are often a result of such urbanisation. Conventionally, stat­utory plans such as master plans (also referred to as development plans) are prepared in India to address spatial chal­lenges related with urbanisation and its consequences. Master plans are usually long-term plans prepared for a period of 20 years to guide the sustainable devel­opment of cities. However, addressing short-term and real-time changes in cit­ies remains a critical challenge.

Recent studies indicate that the ten­dency toward unauthorised construc­tions continues to be increasing in certain forms, even as governments repeatedly try to remove them. Key challenges in­clude unauthorised/ illegal constructions and encroachments, non-conforming to master plans and development control regulations (DCRs) or building byelaws. This in turn disrupts planned structure and the envisaged development of cit­ies, which is particularly evident along the urban roads, rivers, lakes, and in the vicinity of the heritage monuments. Iden­tifying and addressing such encroach­ments usually involves complex and time-consuming processes. In view of this, there is a need for an urban moni­toring system that can complement and support the effective implementation of master plans.

Emerging frameworks like City Infor­mation Modelling (CIM) enable real-time monitoring of complex urban systems. It is a digital framework encompassing geospatial systems, Artificial Intelligence (AI), Internet of Things (IoT), Digital Twin (DT), Spatial Data Infrastructure (SDI), and Data Analytics to generate a comprehensive model of a city. It inte­grates both spatial and non-spatial data; including demographic, socio-economic, environmental and infrastructural infor­mation from multiple sources. The con­cept of CIM is not new and has evolved (in three phases) in the past two decades. The first phase was the data digitisation of physical maps, land records and other relevant documents. The second phase was the integration of diverse data sets within Geographic Information Systems (GIS) platforms. Presently CIM is in its third phase, i.e., intelligent modelling phase and includes emerging technolo­gies such as AI, Machine Learning (ML), IoT, and DT. CIM can be integrated at various scales ranging from a building to an entire city for effective urban monitor­ing. It is therefore considered as one of the most powerful frameworks, as it enables optimisation of urban systems through continuous monitoring.

DT, an integral part of CIM, can continuously integrate real-time and spa­tio-temporal data by creating dynamic virtual replicas of the city for smarter ur­ban monitoring. Through this dynamic technology, the exact state of the city can be replicated at any given point of time. Based on this decision support system, urban planners can dynamically moni­tor critical metrics of urban sprawl and unplanned expansions. Such initiatives are being taken up under the Smart City Mission in India. Presently under this mission, Integrated Command and Con­trol Centers (ICCCs) serve as centralized hubs for data-driven decision making, and real-time monitoring of city services such as traffic, security, water supply, street lighting, waste collection, etc. As these technocratic services have proven to be effective, they can also be extended for monitoring the unplanned urban ex­pansions such as unauthorized, illegal constructions/ encroachments across the city, particularly along the roads, water bodies and monuments. For addressing these challenges, encroachments can be broadly categorized into the following three regulatory buffers i.e., point, line and polygon buffers.

POINT BUFFERS: PROTECTING MONU­MENTS & HERITAGE PRECINCTS

As per the Ancient Monuments and Ar­chaeological Sites and Remains (Amend­ment and Validation) (AMASR), Act 2010, prohibited area extends to a dis­tance of 100 metres in all directions of an ancient monument or an archeologi­cal site of national importance. No con­struction of new buildings, reconstruc­tion or excavation is permissible within this buffer to preserve the monument’s integrity and heritage value. However, a few exceptions can be applicable only with the prior approval of the central government. Further, regulated area ex­tends to a distance of 200 metres begin­ning at the limit of the prohibited area in all directions i.e., between 100 meters and 300 meters from the monument. In this area, controlled development is al­lowed under strict regulation with the prior permission of the National Monu­ments Authority.

Source: Author

CIM environment has a great poten­tial for continuous digital surveillance of monuments and heritage precincts. Each of the monuments or heritage precincts is georeferenced as a point feature using geospatial components of CIM. Thereaf­ter, circular buffers for both the prohib­ited (100 metres) and regulated areas (300 metres) from the location of the monu­ment are automatically generated in line with the AMASR Act. Real-time build­ing data derived from satellite imagery or aerial photography or Unmanned Aerial Vehicle (UAV)/ drone surveys are then overlapped onto these buffers. Further, encroachments are identified through the auto-intersection of buffers with any construction falling within the prohibited and regulated areas around the monu­ment or archeological site of heritage value. Finally, those buildings that are constructed beyond the permissible height or number of floors or buildings that are not in accordance with the permissible Floor Area Ratio (FAR)/ Floor Space In­dex (FSI) as per the applicable DCR are automatically identified. To reduce time consumption, a geospatial technique viz., Model Builder can be utilised to automate and run the above spatial analysis by con­necting multiple geospatial operations in a structured sequence.

LINE BUFFERS: MONITORING EN­CROACHMENTS ALONG THE ROADS

For a smooth urban mobility in Indian cities, strict compliance to the prescribed Right of Way (ROW) standards in line with the applicable provisions of DCRs, Master Plans, National Highways Au­thority of India (NHAI) guidelines, and relevant state planning laws is essential. In contrast, non-compliance with these standards or regulations often results in encroachments and may attract legal action from the concerned authorities. In general, road encroachments refer to the unauthorised occupation, use or obstruction of public road or its ROW. Such encroachments on roads and public pathways are a major obstacle to achiev­ing sustainable and efficient urban mo­bility. They are often instrumental in reducing the effective width of the car­riage ways thus contributing to traffic congestion, increased travel time, fuel consumption and road accident risk.

CIM can effectively monitor en­croachments along roads by integrating geospatial layers, real-time data, and reg­ulatory norms into a single unified plat­form. Road networks are first mapped as line features. Setback buffers such as statutory ROWs are generated as per the applicable regulatory norms. The buffers thus generated are continuously overlaid with satellite imagery, mobile mapping, UAV surveys or closed-circuit television (CCTV) feeds. Encroachments such as any temporary or permanent construc­tion, illegal parking, street vendors, con­struction debris, etc., in the road setback buffer can be identified through auto­mated spatial analysis. Geospatial ar­tificial (GeoAI) intelligence can provide many features for such automated spatial analysis. The dynamic nature of CIM enables real-time and spatio-temporal monitoring of the roads and can help in flagging recurring violations. Addition­ally, 3D visualisation replicas through digital twins can trace vertical intrusions such as hoardings, sign boards, over handing structures, etc. Such monitor­ing can allow the planning authorities to prioritise critical corridors and plan for targeted clearance drives based on real usage patterns.

POLYGON BUFFERS: SAFEGUARDING WATER BODIES AND ECO-SENSITIVE ZONES

In India, Wetlands (Conservation and Management) Rules, 2017 is a notified framework under the provisions of the Environment (Protection) Act, 1986 for the conservation and management of wetlands. These rules also guide and support the State Governments / Union Territory (UT) administrations to conserve, manage, and maintain the ecological character of wetlands while promoting their wise use. In contrast, the protection and regula­tion of water bodies such as lakes is primarily the responsibility of state governments, implemented through state-level planning, regulatory, and administrative authorities. The Lake Protection Committee of Hyderabad Metropolitan Development Author­ity (HMDA) is one such example. It notifies the Full Tank Level (FTL) boundaries and buffer zones of lakes or water bodies falling within its region, to maintain recreational or green buffer zones, while restricting any building activity. A buffer of 30 metres is mandated for lakes larger than 10 hectares, while a buffer of 9 me­tres is prescribed for lakes smaller than 10 hectares.

Urban lakes are digitally mapped as polygon features within CIM. Buffer zones are created around the lakes in line with the applicable eco-sensitive zones or lake protection regulations as mentioned above. Such buffers are critical to main­tain hydrological balance and to prevent pollution of the lake thereby protecting its biodiversity. These buffers are fur­ther overlapped with landuse data and building footprints, allowing the CIM to detect and flag the encroachments such as construction, dumping or land rec­lamation in the prescribed lake buffer. Additionally, CIM framework can also virtually simulate such encroachments, demonstrating how reduction in the buffer can increase flood risk disrupting the natural drainage. As a dynamic sys­tem, CIM can monitor spatio-temporal encroachments through real-time data feeds rather than merely capturing static violations. This in turn can enable timely intervention before any occurrence of irreversible damage.

RECOMMENDATIONS

Encroachments along roads, water bod­ies, and heritage monuments often pose a threat to sustainable urban develop­ment. They most frequently lead to inef­ficient land uses, mobility constraints, environmental degradation, and loss of cultural assets. In order to address such issues, the following integrated approach of CIM is recommended for a smarter urban monitoring:

1. CIM integration with Master Plans: Master plans should be integrated with the GeoAI enabled Digital Twins. Various landuse zones and infrastruc­ture networks coupled with regulatory layers should be generated and auto­mated with CIM environment. Such an environment enables continuous data updation through real-time data feeds and data validation against real-world developments. Besides, master plans should incorporate a feedback loop mechanism, where detected violations and spatial changes automatically can update the planning database.
2. CIM integration with Regula­tions: Relevant and applicable regula­tory provisions should be encoded as machine-readable rules to allow auto­mated detection of violations. Such pro­visions may include permissible setbacks, FSI/ FAR, RoW, buffer zones for roads, water bodies, and heritage structures from Master Plans, DCRs, Town and Country Planning Acts, Urban and Re­gional Development Plans Formulation and Implementation (URDPFI) guide­lines, and any other orders / guidelines by concerned government authorities from time-to-time.
3. CIM integration with DT: For ensuring continuous monitor­ing of urban expansion and landuse changes, CIM platforms should be integrated with digital twins. This may include multi-source real-time data streams such as satellite imag­ery, aerial photography, UAV sur­veys, CCTV networks, IoT sensors, etc., enabling generation of 3D digi­tal replicas of the real world.
4. CIM integration with SDI: A centralised SDI should be created to integrate relevant datasets from the urban local bodies, planning authorities, and other concerned departments. This will enable easy access to available data within CIM environment, thereby contrib­uting to significant time savings, im­proved data consistency, and reduced data duplication.

CONCLUSION

Integration of CIM with the master plans, regulatory provisions, digital twin technology, GeoAI and spatial data in­frastructure can significantly strengthen urban monitoring. Such integration can transform traditional systems into dy­namic and data-driven decision systems. Also, planning authorities can consider­ably improve identification, monitoring, and management of illegal constructions through systematic and automated pro­cesses. By adopting above steps within a CIM environment, any new construc­tion falling within the restricted buffer in and around heritage monuments, water bodies or roads can be instantly flagged as being in contravention. Be­yond conventional 2D mapping, CIM also enables advanced 3D visualisation allowing urban planners to evaluate not only horizontal encroachments but also vertical violations. This power of CIM can transform the urban monitoring of cities from periodic inspections into smarter digital monitoring, improving transparency, and long-term urban sus­tainability.

*The writer is Professor and Head, Centre for Geoinformatics, School of Planning and Architecture, Bhopal.