Mapping the digital groundwork for the Smart villages of India
At the national level, our development planning takes a top-down approach and satellites provide macro data for influencing policy decisions. The villages on these maps are smaller than the heads of the thumbtacks marking their locations. The maps fail to give details about local geography and, consequently, decision-makers are forced to take a call and launch major initiatives with little or no data. As a nation, our technological progress is incomplete until it percolates to the villages. Our team felt strongly about bringing the India of technological innovations to the villages of Bharat. We went to the villages, conducted ethnographic studies, and took the time to understand the administrative framework that goes into decision-making. We realised that there is a need for granular data about localised regions to aid the planning and development at a grassroot level.
The primary data extractable from these maps include the identification of the village boundary from the Orthomosaic, and photogrammetry can be used to measure the length of roads, area of lands, and volume of ponds. In addition, this allows for online sharing and collaboration for multiple officials who might not be present on the site. The primary information obtained through aerial data collection is moldable to provide more valuable insights about—
- Connectivity: Road networks and the identification of tar, cement concrete, kharanjha, and kaccha road.
- Infrastructure: Infrastructure and community assets like Anganwadi, school Building, Egovernance centre.
- Housing: distribution of Kaccha versus Pakka houses.
- Sanitation: Map individual toilets and areas prone to water logging in habitations.
- Energy: Analysis of rooftops for their potential to produce solar energy
- Asset Identification: Map the number of solar streetlights, electricity poles, Hand pumps, and outlets for drinking water.
- Agriculture/Green cover: The ratio of built-up area versus green areas are available, in addition to NDVI maps (specialised for crop health) and used to estimate yield or identify sources of crop stress.
Cumulatively, all this data forms a solid basis for redesigning a wholesome developmental policy on a micro level.
The first digital steps of Shivdaspur Grant ( UP )
What we learnt:
A small village in the northern parts of India with a total population of 758 individuals. Like most other villages in that part of the country, the primary problem faced by this village is lack of clean drinking water and unavailability of sanitation facilities. The village has a small pond in one corner and owing to flawed planning that did not account for ground elevation, the drainage water through the entire village accumulates in this pond. Thereby, making this pond and the areas around it unsanitary. This also led to this area of the village being less desirable to live and impacted the way less privileged communities were distributed across the village.
Our Impact:
The government had launched several schemes for rural development to build roads, houses (Lohia Gram Yojana), Toilets (Swaccha Bharat Yojana). Mapping with such granular detail allows officials a way to track the ground execution of contracts and provides a scientfic way to enforce transparency. Through the use of our technology we brought down the amount of money spent on land surveying by local authorities by almost 40–60% and the time dedicated to surveying was slashed by a tenth. These numbers would look even more favorable at scale, effectively making analysis of aerial data — a formidable tool for planning and development.
Ps: A few snapshots from our study-
