Google has introduced 2 India-first artificial intelligence models focused on agriculture through Google DeepMind’s AnthroKrishi team. The models, Agricultural Landscape Understanding (ALU) and Agricultural Monitoring and Event Detection (AMED), are designed to generate detailed, field-level agricultural intelligence.
ALU is built to process spatial and farm-related data to identify agricultural land patterns. It can support field-level mapping, land analysis and digital agriculture applications while providing granular data through application programming interfaces (APIs).
AMED is designed to track changes in agriculture and identify event-based signals. When used with ALU, it can help monitor crop conditions, changes in land use and farm-related events at scale.
Together, ALU and AMED form part of Google’s India-first agricultural intelligence framework. Data generated by the models has also been integrated into Google Earth as a visual data layer.
Following testing with partners in the Asia-Pacific region, Google has expanded the models to Kenya, Uganda, Ghana, Rwanda, Nigeria and Zambia.
The technology is already being used across several agricultural applications. CarbonFarm has combined the ALU API with Gemini to support low-carbon rice cultivation, with a target of covering 2 million hectares by 2030.
TerraStack, an IIT Bombay-incubated startup, has used the APIs to map more than 140 million hectares of farmland.
Karnataka’s Water Resources Department has used the data for water management across 2.6 million hectares of irrigated land. In Telangana, the Agricultural Data Exchange (ADeX) is using the models for digital agriculture services.
ALU and AMED have applications across precision agriculture, land-record modernisation, irrigation planning and crop monitoring.
The AI systems use geospatial data, remote sensing inputs and automated event detection to support agricultural decision-making.
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