An lntegrated GIS-based Digital Public lnfrastructure for Land Governance

Land governance in lndia involves multiple institutions maintaining land-related information in fragmented and disconnected systems. Core datasets such as cadastral maps, Record of Rights (RoR), registration records, land use information, Master Plan, Building Permission, Restrictions, property taxation records, utility infrastructure, and other land-related databases are often managed Independently by different departments and agencies with limited interoperability. This results in duplication of effort, inconsistencies in records, delays in obtaining ownership information, lack of transparency in transactions, and inconvenience to citizens seeking land-related services.

The growing scale of urbanization, increasing land transactions, demand for efficient governance, and the need for transparent and citizen-centric public service delivery require a modern digital approach to land administration. With advances in GIS technologies, Digital Public lnfrastructure (DPl), cloud computing, interoperable APls, Al/ML analytics, and geospatial standards, there is an opportunity to transform land governance through a unified digital ecosystem.Land Stack is envisaged as an integrated GIS-based digital platform that brings together all land-related datasets, workflows, and services into a single interoperable framework. Built upon georeferenced cadastral maps and linked with record of rights(land ownership records), Land Stack can serve as foundational digital infrastructure for efficient land governance, informed decision making, improved service delivery.The proposed platform should support both rural and urban contexts and enable seamless coordination across departments, institutions, and citizen interfaces.

Detailed

The Department of Land Resources has initiated the development and deployment of Land Stack in pilot locations of Chandigarh and Tamil Nadu, launched on 31 December

Therefore, the challenge is to conceptualize and develop a scalable prototype of Land Stack capable of integrating diverse land-related datasets, workflows, and services into a common interoperable State-level framework.

The proposed Land stack solution should organize information into three broad categories of spatial layers. The base layer should comprise georeferenced cadastral maps, parcel boundaries, and unique parcel identifiers such as ULPIN.

This foundational layer should provide the spatial framework upon which all governance and service-related datasets can be integrated.The essential layers should include core governance datasets linked to each parcel,such as Record of Rights (RoR), registration data, master plans, building permissions and approvals, encumbrance and mortgage records, land use and zoning information.These layers should collectively define ownership, rights,restrictions, liabilities, and permissible land use associated with each parcel.Beyond this, additional or use-case layers should extend the platform's governance and citizen service capabilities by integrating datasets such as utility infrastructure, property taxation records, valuation references, infrastructure networks,environmental or restriction zones, and other service linkages. Each land parcel should be uniquely identifiable and linked with multiple layers of governance and administrative information, with ULPIN serving as the suggested common identifier.The prototype should demonstrate integration of multiple land-related domains through parcel-level GlS visualization and data exploration tools. The system should support interoperability between departmental systems through open APls, standardized metadata structures, secure authentication mechanisms, role-based access controls, audit trails, and scalable digital architecture. Citizen-facing capabilities such as parcel search, ownership verification, transaction status tracking, service requests, and access to land-related information should also be incorporated.

Participants are encouraged to integrate innovative technologies including Artificial lntelligence (Al), Machine Learning (ML), satellite imagery-based change detection, predictive analytics, workflow automation, and decision-support dashboards to improve transparency, operational efficiency, and governance outcomes.The overall solution should be modular, scalable, configurable for different administrative contexts, and capable of serving as a replicable national framework for integrated digital land governance.

The expected outcome is a functional prototype demonstrating the concept of Land stack as an integrated Gls-based Digital Public lnfrastructure for land governance.The solution should provide a unified digital platform capable of integrating multiple land-related datasets around a parcel-centric spatial framework and enabling seamless interaction between governance institutions, land administration agencles, and citizens. The prototype should demonstrate GIS-based parcel visualization,integration of mock or sample land-related datasets, role-based administrative dashboards, citizen-facing service interfaces, and interoperable workflows between land records, registration, dispute, planning, and fiscal systems.

The proposed solution should showcase efficient parcel-level information access, real-time or simulated workflow integration, cross-departmental data interoperability, analytics-driven governance insights, and transparent citizen service delivery mechanisms.lnnovative solutions that leverage Al/ML, geospatial intelligence, predictive analytics,workflow automation, API-based integration, mobile accessibility, and secure cloud- native architecture will be preferred.

The final prototype should demonstrate how fragmented land governance systems can be transformed into a unified, scalable, transparent, and citizen-centric Land Stack platform capable of improving land administration, enabling citizens to take informed decisions, accelerating transactions, strengthening planning, and enabling data-driven governance.

Further, participants are expected to prepare a Standard Technical Document containing details of API standards, interoperability standards, data schemas, system architecture, GIS standards, security frameworks, UI/UX guidelines, color schemas, and deployment and scalability considerations.