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TiNAI: How Tamil Nadu Is Using Digital Twins and AI to Transform Land-Use Planning

TiNAI is India’s first state-led platform that combines GIS data, Digital Twin visualisation and an AI interface to support clear and evidence-based land-use planning.
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In government offices across India, data often exists in silos—maps in one department, reports in another, research papers stored away and rarely revisited. Decisions about land, water, cities, climate, and energy are frequently made with only pieces of the full picture. Tamil Nadu is now trying to change that story.

TiNAI—the Tamil Nadu Land Use Information System—is India’s first state-led platform that brings together land-use data, research findings, Digital Twin visualisation, and an AI-assisted interface into one public decision-support system. Designed for planners, administrators, and researchers, TiNAI aims to make complex spatial information easier to understand and use for real planning.

Anchored under the Tamil Nadu State Planning Commission and developed by the Tamil Nadu State Land Use Research Board (TNSLURB), the platform was recently launched by the Hon’ble Deputy Chief Minister. It marks a major step towards evidence-based governance.

THE PROBLEM: TOO MUCH DATA, TOO LITTLE CONNECTION

Land-use planning depends on many sectors—forests, water, agriculture, climate, urban growth, energy, and disaster management. Over the years, Tamil Nadu has generated a large amount of high-quality research and spatial data in all these areas.

But most of this information remained scattered across departments and institutions. Research outputs were shared through static reports, often difficult to compare across regions or time periods. This made it hard to see how one decision affects another sector.

The result was a clear gap between research and policy. Valuable evidence existed, but it was not always used in day-to-day planning.

THE IDEA: ONE PLATFORM, MANY SECTORS

TiNAI was created to solve this very problem. It brings different datasets into a single spatial framework, allowing users to see connections instead of isolated numbers.

At its core, TiNAI is a public-sector decision-support platform. It does not replace cadastral or land-record systems. Instead, it helps governments ask better questions—about where to invest, how to manage resources, and what trade-offs exist.

We set out to connect research from across sectors into a single spatial platform that anyone—not just GIS experts—can understand. By using Digital Twins and AI to break data silos and democratise evidence, TiNAI lays the foundation for truly informed decisions that lead to sustainable development,” says Ms. Sudha Ramen, IFS, Member Secretary, Tamil Nadu State Planning Commission.

HOW TiNAI WORKS: TWO CONNECTED SYSTEMS

TiNAI is built around two tightly linked functional units.

The first is the GEOSPATIAL PLATFORM. This offers interactive maps, dashboards, and analytical tools across land-use domains. Users can compare districts, blocks, regions, and time periods to spot trends and patterns.

The second is the DIGITAL TWIN AND AI INTERFACE. This creates a layered spatial environment where users explore Key Performance Indicators (KPIs) through visuals and guided AI-based queries. Instead of reading long reports, users can ask focused questions and get clear insights.

This kind of integration is being used for land-use planning for the first time in India.

STRONG ANALYTICAL FOUNDATION

Behind the simple interface is a powerful analytical base. TiNAI integrates:

More than 50 analytical tools

Over 100 spatial and thematic parameters

Around 160 qualitative spatial data layers

75+ Key Performance Indicators organised in a semantic framework

These datasets power both the Digital Twin environment and the AI interface, allowing systematic analysis across sectors, locations, and timeframes.

NINE THEMATIC MODULES, ONE VIEW

TiNAI covers nine major land-use areas:

Land Use & Land Cover, Forests, Water Resources, Climate Change, Disaster Risk, Agriculture, Urban & Peri-Urban Areas, Coastal & Marine Systems, and Energy & Industries.

All modules sit on the same spatial base. This means urban growth can be viewed alongside water stress, climate risk, or energy demand—encouraging joined-up thinking rather than sector-by-sector decisions.

TOOLS THAT MAKE DATA MEANINGFUL

Some tools in the current version stand out for their practical value.

Heat stress mapping shows thermal stress alongside rainfall and temperature data, helping users understand climate patterns instead of viewing heat in isolation.

Urban growth analysis visualises expansion trends and projections up to 2035. This supports discussions on infrastructure demand, land pressure, and long-term resilience.

Land suitability tools for solar and wind energy combine land characteristics, environmental limits, and spatial constraints, helping planners see where clean energy development makes sense.

BUILT FOR PLANNERS, NOT JUST EXPERTS

Inspired by global platforms like Global Forest Watch, TiNAI avoids the complexity that often keeps non-specialists away from GIS portals. Information is presented through dashboards, graphs, tables, and AI-assisted summaries.

This makes the platform usable for administrators, policy teams, and researchers alike—without needing advanced technical skills.

THE ROAD AHEAD: TiNAI 2.0

The current version is only the beginning. TiNAI 2.0 will bring more tools, richer datasets, and a stronger AI interface. The platform is open to collaboration with academic institutions, research bodies, and global partners.

With support from organisations such as ISRO’s National Remote Sensing Centre, IIT Madras, WRI India, and several national and international institutions, TiNAI reflects a collective effort.

In a time when data is abundant but clarity is rare, TiNAI shows how technology—when guided by purpose—can turn information into insight, and insight into better decisions.


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