India's Ministry of Science and Technology published the National Geospatial Policy, 2022, on in December last year.
The policy seeks to establish a Geospatial Knowledge Infrastructure (GKI) and related ecosystem by 2030. It would also support the use of Cities' Digital Twin.
Digital Twin
Image Credits: WEF
A city digital twin is a virtual replica of a city that integrates various data sources and provides a holistic view of its physical, social, and environmental aspects. It can play a crucial role in city governance by helping decision-makers, urban planners, and policymakers understand, analyze, and address complex urban challenges.
If a city is embarking on a large-scale urban planning initiative, such as developing a new district or revitalizing an existing area, a digital twin can provide a holistic view of the entire urban environment. It can help planners visualize the impact of proposed developments, simulate scenarios, and assess the long-term implications of different planning decisions.
In our earlier blog, we shared about how few cities like Amsterdam, Singapore are using Monitoring Platforms to better monitor and plan action on specific use cases. Those dashboards can be considered a reduced implementation of city-wide Digital Twin.
A Digitial Twin consumes data such as:
Geospatial data, including land use, zoning, and parcel information
Demographic data, such as population density, age distribution, and socioeconomic indicators
Transportation data, encompassing road networks, public transit, and bike lanes
Environmental data, including air quality, green spaces, and ecological features
The use case where Digital Model is used:
Interactive digital twin showcasing the city's physical and social aspects, including land use, infrastructure, and demographics
Simulation tools for scenario planning, enabling policymakers to test different urban development strategies
Integration of data layers to analyze the impact of proposed changes on traffic patterns, environmental quality, and social equity
Key performance indicators related to sustainable development goals, livability, and resilience
For all its glitters the technology approach is still maturing and there are many road blocks in its implementation:
Resource Constraints: Building and maintaining a digital twin requires significant investments. It puts great budgetary and human resource demand.
Technological Maturity: Digital twin technology is still evolving, and is yet to prove is effectiveness, departmental interoperability, and long-term sustainability.
Data Silos: City data is often scattered across various departments and systems, making integration difficult.
Governance and Regulatory Barriers: Legal and regulatory challenges related to data privacy, liability, and ownership can be complex and time-consuming.
Though, Digital Twin can assist in understanding the impacts of proposed interventions, evaluating infrastructure requirements, and promoting sustainable development.
However, it is crucial to recognize that the successful implementation of digital twins requires addressing systemic issues, fostering collaboration, and considering broader socio-economic factors in India's urban planning processes.
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