Earlier this year, the Indian government issued new guidelines allowing private entities to easily use, create, and access land data instead of going through long clearance protocols. The newly available data includes location information about physical structures, boundaries, natural phenomena, weather patterns, and more, gathered through ground-based survey techniques, photogrammetry using drones, lidar, radar, and so on.
On paper, this means a green light for small- and medium-sized companies to collect and use this data to build commercial applications and services related to mapping. It is also a relief to alternative or participatory mapping communities, such as counter-mapping initiatives (in which local, indigenous populations make their own maps in their own contexts), which have so far lurked in a gray area of legality. For the development and academic sectors, too, it heralds greater access to maps and related data for research.
But a more in-depth analysis raises troubling questions. Who owns this data? Where does it end up? Who is going to be using it? For what?
Before the recent deregulation, mapmaking in India was considered a sensitive activity that needed to be closely monitored, and was handled solely by the government’s surveying department. As a result, OpenStreetMap volunteers, for example, operated under fear of prosecution. Digital cartographer Arun Ganesh, who was once an OpenStreetMapper, acknowledges the freedoms afforded by the new rules. But he also worries that it could enable free data capture.
The new guidelines come with tantalizing promises of progress. Jatin Singh, writing for Fortune India, says it will now be possible to overlay cadastral maps (which provide information about the extent, value, and ownership of land parcels) with crop data and data on assets such as cattle, automobiles, power lines, and more. This data will act as collateral for bank loans for more than 100 million farmers, including, theoretically, those outside the formal credit system. Small farmers who previously weren’t considered creditworthy would then be able to get loans against their land. For banks, this would enable quick, hassle-free loan disbursement as well as fraud detection; this form of virtual collateral may eventually even be accepted for other kinds of lending. “The opening up of maps is going to end leakages and allow banks to underwrite more effectively,” Singh claims. “The cost of credit in rural India should now come down.”
Singh, founder of Skymet Weather Services, is an industry stakeholder. Counter-mapping and open-mapping people, however, see the situation differently. The new guidelines are “a continuation of the policies of the present regime in India to open up all national spaces and resources for capital for the benefit of major corporate houses,” Yemuna Sunny, a social geographer and educator, says. “Their investments in the sector, and the sale of map outputs … will also prove every corner of the country … has the potential for resource exploitation. But this spells danger for communities who are in the margins of the economy, and not part of the capitalist economy in a classical sense.”
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The geospatial data regulations are part of a bigger picture. They're the latest in a series of reforms—land reforms, proposed farm laws, amendments to the Forest Act, new drone regulations and land digitalization schemes—that are all positioned as being beneficial to individuals, but which make it easier for private corporations to enter these sectors.
In the past decade or so, successive governments have promised prosperity via “digital governance” in order to coerce more and more Indians into giving up their data—personal and otherwise—ostensibly for their own good. Schemes like Aadhaar, a unique biometric-based ID; AgriStack, a collection of technologies and digital databases about farmers and farming; the Health ID; and others have resulted in massive, digital databases. Though specialized for different things, when these databases are interlinked, they form a powerful digital superstructure—with unchecked scope creep, no data protection laws, and sketchy regulations on the use and access to that data. With geospatial data now up for grabs, there is no clarity on how this might be integrated or correlated with the other existing databases.
So while these companies can extract land data and use it to make money, the marginalized folks who live in these areas and earn their living from the land are pushed further to the peripheries. The further the private sector advances into indigenous lands and into the lands of small farmers, the more the former’s control over the land and its resources grow. This is happening, for example, in the southern state of Andhra Pradesh, where the government’s plan to lease out inland waterways to private companies risks the livelihoods of local fishers.
Another example of how this plays out, explains Srikanth L. of the consumer collective Cashless Consumer in a tweet thread, comes from the Survey of Villages and Mapping with Improvised Technology in Village Areas (Svamitva), which aims to chart land parcels in rural, inhabited areas using drones.
Svamitva grants whomever is currently living in a particular rural area an official title to their property, which would serve, Singh writes, as collateral for loans. (Landownership in India can be complicated because of systems created during colonial rule, along with legal gaps and poor administrative record-keeping.) Srikanth, however, is skeptical. “That’s not to say that this can’t happen,” says Srikanth. “It will happen, but not for everybody—maybe for the early adopters.” This is because rural borrowers tend to be outside the formal banking system, sometimes even unaware of waivers and credit schemes they might be eligible for, and depend largely on informal credit.
Yet while the promised collateral system will likely not work out, Svamitva could become the umbrella under which the infrastructure for drone surveillance is brought in. The Indian government is set to fund a network of continuously operating reference stations (CORS)—a kind of “highway” for drones to fly autonomously and do their surveying—to support Svamitva. Srikanth believes that the Svamitva scheme uses the “low-hanging fruit” of surveying residential rural land to venture into drone technology. Surveying residential land is “slightly less political than to, say, go after agricultural land,” he says, and when technologies like drone-based deliveries, imaging, and photography become possible, CORS ends up being a key infrastructure that the state has invested in. That these geospatial data regulations come alongside recent corporatization and privatization in mining, defense manufacturing, civil aviation, space exploration, and more is probably not a coincidence. Private companies will be lining up to provide the back-end technologies. For geospatial data collection, too, somebody will have to provide the back-end technology—operate the drones, map the data, issue property cards, and so on.
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The recent guidelines assure open access and stipulate that geospatial data created with public money be available at a fair and transparent price. It doesn’t, however, define “fair” or “transparent.” Ultimately, the guidelines fall short of the promise of open data.
Researchers and analysts like Raj Bhagat Palanichamy, who works at the World Resources Institute India, feel that the situation is “status quo.” While the opening-up helps commercial stakeholders by creating new revenue opportunities, the academic and research sectors continue to face the same bottlenecks as before. In reality, the pricing hasn’t changed, and it remains prohibitively expensive. Despite the promise of easier clearances, the processes for applying for access to the data haven’t changed either, even for publicly funded data.
Data that is not sensitive and collected using public funds need to be open, with a centralized framework for using and creating that data, Palanichamy says. There are three areas where the guidelines need more work: a clearer commitment to open data, consultations with all stakeholders, and standardizations regarding pricing and access for data from government agencies. Also, for geospatial data to be meaningful, it has to be more than just location information. For example, during the deadly second wave of Covid-19, local- or state-level information on the number of hospital beds, number of ventilators, and oxygen supply could have made a real difference.
Today, when data is both commodity and currency, this digital land-grab can only be stopped by intentionally putting the people back into the equation.
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