Q1: The vision for Viksit Bharat @ 2047 hinges on a robust Digital Public Infrastructure (DPI) and seamless multi-modal connectivity.

In this context, how does a comprehensive"Geospatial Infrastructure" serve as the non-negotiable backbone for India's economic expansion, and what shifts are necessary to transition from traditional mapping to a national spatial data framework that supports a developed nation status?

The role of geospatial technology today goes far beyond traditional mapping. Earlier, maps were static, department-driven, and used primarily for visualization. The future, however, requires a dynamic national spatial data framework that continuously integrates and updates information from satellites, drones, IoT sensors, utilities, transportation networks, land records, environmental systems, and enterprise applications. In a developed digital economy, geospatial systems must function as living operational platforms that support real-time monitoring, predictive analytics, simulation, and intelligent decision-making.

To achieve this transition, India must move from isolated mapping initiatives to a connected and interoperable spatial ecosystem. This requires standardized data models, open APIs, common interoperability frameworks, and trusted mechanisms for data sharing across government departments, states, cities, and enterprises. Spatial data should become easily accessible and consumable across sectors, much like digital payments or cloud services today. GIS must also become deeply integrated with enterprise systems so that organizations can move from reactive operations to predictive and autonomous decision-making.

Building a skilled geospatial workforce, encouraging innovation through startups and public-private partnerships, and investing in national-scale spatial infrastructure is essential for creating a globally competitive geospatial ecosystem.

Q2: Indian cities face complex challenges - from traffic congestion to climate risks - that require better visibility into urban systems. GIS-based digital twins offer a living, continuously updated 3D model of a city, connecting roads, buildings, utilities and sensors so planners can simulate and predict outcomes with confidence. How do you see digital twins transforming urban planning and infrastructure development in India?

As urbanization accelerates globally and across India, cities are under growing pressure to manage increasingly complex infrastructure systems and rapidly expanding populations. It is estimated that nearly 40% of India's population will reside in urban areas by 2030, intensifying the need for smarter, more adaptive approaches to urban planning and governance. Traditional planning methodologies, which are often static and reactive, are no longer sufficient to address the dynamic challenges of modern urban environments.

Urban local bodies are increasingly recognizing the transformative value of real-time digital intelligence in improving citizen services, enhancing operational efficiency, and enabling data-driven decision-making. By integrating live data streams from sensors and connected systems, cities can simulate "what-if" scenarios for infrastructure, mobility, utilities, environmental conditions, and urban development plans before implementing them in the real world. This enables more informed planning, proactive governance, and resilient urban growth.

GIS-enabled Living Digital Twins are emerging as a powerful foundation for the future of urban management. These digital replicas of physical cities continuously integrate real-time data from diverse sources such as traffic systems, SCADA networks, utility sensors, surveillance cameras, environmental and weather monitoring systems, and GPS-enabled public transportation. The result is a dynamic, continuously updated digital model of the city that supports predictive analysis, operational intelligence, and scenario-based planning.

Unlike static 3D city models, Living Digital Twins create a living digital ecosystem that mirrors real-world urban conditions in near real time. They enable city administrators, planners, and infrastructure agencies to visualize complex interdependencies, anticipate disruptions, optimize resource utilization, and improve emergency response and long-term planning outcomes.

At the core of this transformation is Esri's ArcGIS, which serves as the foundational platform for building and operationalizing digital twins. ArcGIS integrates disparate datasets and enterprise systems into a unified geospatial environment, creating a single source of truth across the entire project and infrastructure lifecycle. It strengthens data capture and integration, enables immersive real-time visualization, supports advanced analytics and AI-driven forecasting, and facilitates seamless information sharing and collaboration among stakeholders.

By combining GIS, real-time data, AI, and digital twin technologies, cities can transition from reactive management to predictive and intelligent urban operations, paving the way for more sustainable, resilient, and citizen-centric urban futures.

Q3: GeoAI - the combination of geospatial data and artificial intelligence - is enabling more intelligent decision-making across industries. For example, GeoAI can analyze satellite and drone imagery to monitor crop health, predict yields and optimize resources. How is Esri India enabling a GeoAI-led shift in critical sectors like sustainable agriculture and disaster management? Specifically, how is your platform helping stakeholders move from simply mapping problems to executing precision-based, real-time interventions?

With over 1.5 million users of Esri's technology in the country, we are continuously innovating to meet the evolving needs of Indian users across various sectors. We are largely focused on enabling a GeoAI-led shift across critical sectors. We have established a GIS & AI Competency Center in Noida and intend to invest more than INR 150 crores over the next 3-5 years in it. The intent is to develop cutting-edge GeoAI solutions that can significantly help in solving real-world challenges across sectors, from agriculture, transportation, urban planning, environmental monitoring to disaster management.

GIS and GeoAI are transforming disaster management by enabling real-time situational intelligence, predictive analysis, and precision-based response systems. Modern geospatial platforms can ingest live data streams from river gauges, rainfall grids, seismic sensors, weather feeds, satellite imagery, drones, and IoT networks to create a continuously updated operational picture. By integrating these feeds with AI-driven spatial analytics, systems can automatically detect anomalies, identify emerging risks, and trigger alerts before situations escalate. This significantly reduces the time lag between detection and response, which is often critical during floods, cyclones, landslides, and other disasters.

GeoAI also enables the creation of dynamic exposure and vulnerability maps by combining census data, building footprints, road connectivity, utility networks, and population density into live spatial risk layers. This allows responders not only to understand where a hazard is moving, but also which communities are most vulnerable based on age, accessibility, infrastructure quality, or population concentration. In large-scale disasters such as cyclones, GIS becomes critical because it can fuse multiple hazard layers, including storm surges, flooding, landslides, damaged power corridors, and blocked transportation routes into one integrated operational view. AI models can then identify cascading risks and predict compound impacts proactively.

In the recovery phase, GeoAI-driven satellite image analysis can rapidly assess damage by classifying affected structures, roads, and infrastructure within hours of an event. This dramatically improves the speed and accuracy of relief planning compared to traditional field surveys, which can take days or weeks.

GIS and GeoAI are helping agriculture transition from reactive and resource-intensive practices to predictive, precision-based, and sustainable farming systems. As food demand, climate pressures, and resource constraints continue to grow, spatial intelligence will become a critical foundation for building resilient and future-ready agricultural ecosystems.

The impact of GIS and GeoAI extends far beyond individual use cases or sectors. These technologies are enabling organizations across industries to move from reactive decision-making to precision-based, real-time interventions.

Q4: The National Geospatial Policy emphasizes creating an innovation-driven ecosystem and training a skilled geospatial workforce.In your view, what are the critical enablers needed to scale India's geospatial industry over the next decade? For instance, what policies, data standards, public-private partnerships or capacity-building initiatives are most important to ensure that businesses, startups and government agencies can fully leverage GIS, AI and digital twin technologies nationwide?

Conducive policies, data standards, strong talent development initiatives, and public-private partnerships are the most crucial requirements for building a robust geospatial ecosystem in the country.

Progressive policies such as the National Geospatial Policy, liberalized mapping guidelines, and large-scale digital infrastructure initiatives like PM Gati Shakti have made a significant difference in the development of the Indian geospatial ecosystem. However, to scale-up the adoption and use of advanced technologies like GeoAI, living digital twins, we need to take more concrete steps towards enabling seamless sharing of data among government departments, cities, utilities, and enterprises.