The Odisha Land Rights Act: Technology for all

Drones do not just map households faster, cheaper and accurately, but the maps provide a strong visual template of engagement for communities

The Odisha Land Rights to Slum Dwellers Act, 2017, intended to provide titles to over 200,000 households, is a landmark legislation for many reasons. It is a multi-stakeholder endeavour that leverages unique capacities for effective implementation, adopts a community-centric lens and leverages technology as an integral tool to drive efficiency and fidelity. Moreover, the impact of the Act does not end only at land rights, but also extends to providing slum dwellers with livable habitats that will play an important role in driving social and economic mobility.

The objective of this article is to focus on technology, particularly unmanned aerial vehicles or drones that have been used in the implementation process. Drones have been used for geospatial mapping by expert organizations, such as the Spatial Planning and Analysis Research Centre, Transerve and Surbana Jurong, with technical and strategic direction from Omidyar Network. The geospatial mapping by drones yields aerial images of the slums. Maps are created by collating aerial images. These maps are used to identify slum households eligible for land rights and draw up house and plot boundaries. They are also shared with non-governmental organizations to carry out the verification process—including determining eligibility for title and measuring area that will be settled, according to the provisions in the legislation.

This is the first large-scale documented use of drones in mapping informal settlements towards the delivery of land rights in India. Our learnings on the ground and experience of stakeholders demonstrate that geospatial technology can be a significant lever in delivering land and property rights in multiple ways.

First, high-resolution geospatial technology improves the fidelity of the mapping process. The drone maps generated have high resolution and can tell apart two distinct points as close as 2 cm easily. To put this in perspective, an equivalent image from Google Maps has a resolution of 50-60 cm in India. While Google Maps are useful for general mapping purposes, for dense, haphazard, urban, informal settlements with porous boundaries, higher resolution images are necessary to accurately map boundaries, and reduce errors and chances of potential conflict. Similar resolution can also be achieved through other traditional surveying means such as Differential Global Positioning System (DGPS), which is an enhancement to GPS, or Total Station Survey (TSS), another alternative system of mapping land. However, drones are a much faster and cheaper alternative.

Second, the use of drones improves the efficiency of the process. In Odisha, over 100,000 households were mapped in less than two months. In general, drones can map 1.5 square km of land in six and a half hours, compared with a standard DGPS survey that would take about 32.5 hours and cost more than double for the same area. The efficiency brought in by the use of drones has proved to be a key enabler in Odisha, which wants to complete the project in 18 months. It is an incredible feat considering that titling programmes involving far fewer beneficiaries can take 5-10 years.

Third, technology promotes inclusivity for all and not exclusivity for a few. This is especially important since the legislation by design intends to incorporate communities at the centre of the process. Drones do not just map households faster, cheaper and accurately, but the maps generated provide a strong visual template of engagement for communities. In Odisha, we have seen active community-wide engagement, particularly with women being involved in land allocation discussions. This visual template adds a strong element of credibility to the process. The community’s involvement and alignment will be critical in reducing chances of future conflicts. This is particularly important given that over two-thirds of civil cases are related to property and land, of which boundary conflicts remain a big proportion.

The Odisha model also has some important lessons for the use of geospatial technology. As the drone image data gets processed, we hope that further use-cases for urban planning, architecture, as well as research will be explored, given the richness and breadth of data available.

For instance, an analysis of the urban form in Bengaluru by Duke University pointed to 2,000 settlements, while official records count only 600. This was made possible through machine-learning algorithms over satellite imagery and geospatial data. There are multiple such research and planning use-cases. On the policy front, it is important that the government continue to leverage the power of such geospatial technologies with an eye to the future, etching out specific use-cases such as mapping informal settlements and public administration.

Nationally, current flagship schemes, such as the Digital India Land Records Modernization Programme, have made impressive strides in digitization of land records, but the surveying component remains largely unmet.

As Odisha leads the way in becoming the first state to validate the need for future-forward technologies, such as drones and geospatial tools, in delivery and implementation of large-scale systemic programmes such as land rights, policymakers in India must take note of the lessons learnt and work towards a technology-enabled, citizen-centric delivery of economic growth through critical assets such as land and property.