How AI is improving agriculture sustainability in India

For India, agriculture is critical. Roughly half of its population depends on agriculture for its livelihood, and the country has the second largest arable land area in the world. As a lead producer of products like rice, wheat, cotton, sugar, and dairy, India’s agricultural system is essential not only to itself, but also to the rest of the world.

However, India’s agriculture system is facing serious challenges. More efficient crop yield is necessary to continue feeding India’s 1.4 billion people. Climate change disrupts our agricultural systems, and at the same time, unsustainable farming practices exacerbate climate change through significant greenhouse gas emissions, water usage and deforestation. Without change, food and environmental systems across the world are at risk.

Two teams at Google, AnthroKrishi and Google Partner Innovation, are leveraging AI to tackle this challenge, aligned with Google’s AI Principles. The teams’ goal is to progress agricultural sustainability, beginning with India. The team is working on a whole body of AI-powered technologies to organize and utilize India’s agricultural data, the most foundational of which is developing a unified “landscape understanding.”

Landscape understanding leverages satellite imagery and machine learning to draw boundaries between fields, the basic unit of agriculture and essential in creating meaningful insights. With field segments established, the model can determine the acreage of farm fields, forest and woodland areas, and can identify irrigation structures like farm wells and dug ponds to build tools for drought preparedness.