Green revolution 2.0: Transforming farming and unlocking smarter yields through high-precision drone data
Emerging drone-based research now extends into soil-organic-carbon and nitrogen mapping as well as yield forecasting.
| Photo Credit:
KOMMURI SRINIVAS
As India moves towards another wave of technology-led agricultural transformation, drones are emerging as powerful enablers of precision, productivity and sustainability. Equipped with state-of-the-art multispectral, thermal and hyperspectral sensors, these intelligent aerial systems are reshaping how farmers and researchers monitor crops, manage inputs and make timely, data-driven decisions.
Modern drones now give farmers high-resolution visibility across large tracts of land. In minutes, they can map entire fields and capture granular information on crop vigor, soil moisture, pest incidence and nutrient levels. This impact increases multi-fold when the drone data is further processed through cloud-based analytics such as Flyght Cloud, and aerial intelligence translates into actionable insight, helping optimise irrigation, fertilizer use and pest control while improving yields and conserving resources.
Today’s drones go far beyond imaging. They act as sophisticated flying data platforms powered by AI and analytics, capable of detecting crop variations invisible to the human eye. Acting as a bridge between ground-based sensors and satellites, drones deliver centimetre-level accuracy, flexible deployment and cost-effective scalability. Flying at specific crop stages enables consistent monitoring of growth patterns and soil conditions, precision once limited to laboratory research.
Water stress in chickoo plantation
In one large-scale chickoo plantation, drones captured high-resolution multispectral imagery that revealed water-stressed zones, pest-infested patches and canopy density variations. These insights allowed farmers to fine-tune irrigation cycles, adjust nutrient application, and plan targeted interventions, raising yield and resource efficiency. The project demonstrated how drone-based intelligence can revolutionise perennial-crop management through early detection and informed decision-making. Recent research collaborations in India have further validated this potential. In pilot studies on onion and garlic cultivation, drones were deployed from transplanting to harvest, conducting hundreds of sorties and capturing terabytes of high-resolution imagery.
Multispectral and RGB sensors produced detailed maps of plant health, nutrient status and soil variation. By analyzing vegetation indices such as Normalized Difference Vegetation Index (NDVI), Normalised Difference Red Edge Index (NDRE), Chlorophyll Index (CHL), and Optimized Soil-Adjusted Vegetation Index (OSAVI), agronomists identified stress and irrigation needs at micro-level precision—enabling interventions that improved yield and resilience while cutting input waste.
Emerging drone-based research now extends into soil-organic-carbon and nitrogen mapping as well as yield forecasting. Data processed through machine-learning models, particularly Random Forest and Support Vector Machine algorithms, shows strong correlation with laboratory soil tests. Drones have accurately estimated soil-carbon and nitrogen levels across diverse field conditions, while yield-prediction models based on NDVI, NDRE and GNDVI have achieved around 65 per cent predictive accuracy. These capabilities open new possibilities for data-backed crop-insurance assessments and smarter farm-planning tools, helping agriculture move from broad estimates to site-specific intelligence.
Designing to act
Looking ahead, next-generation drones are being designed not only to sense but also to act. Future hybrid systems will detect nutrient deficiencies and directly apply inputs on the spot. Integrating drone data with LiDAR, hyperspectral and meteorological sensors will further enrich analysis, while cloud-based AI will automate soil-health tracking and crop diagnostics. Together, these innovations support India’s broader vision of digital and sustainable agriculture.
Despite clear benefits, scaling precision agriculture poses challenges. High-end sensors remain costly, and robust ground-truth data is needed to train AI models across India’s varied soils and crops. Terrain complexity, maintaining elevation and achieving consistent ground-sampling distance are operational hurdles noted by researchers at ICAR-NRRI and SKUAST.
Yet, with growing institutional support, improved payload integration, and the steady decline of hardware costs, the technology is rapidly becoming accessible to both smallholder and commercial farmers. The Flyght Cloud platform is helping bridge this gap. Raw drone imagery can be processed into vegetation-index maps within a few hours, allowing agronomists to visualise nutrient-stress zones and monitor crop progress through an intuitive web dashboard. This end-to-end ecosystem, hardware, sensors, and analytics, simplifies adoption for research institutes and farmer-producer organisations alike.
As climate variability and input costs rise, drone-based precision agriculture offers a reliable path to producing more with fewer resources. Early detection of crop stress strengthens farm resilience, enabling proactive responses to weather shifts or pest outbreaks. Precision application ensures that fertilizers, pesticides and water are used only where required – reducing runoff and environmental impact while lowering costs.
India’s next green revolution will depend on how effectively it leverages aerial data, AI, and cloud computing to modernise farming. Farming 2.0 is about working smarter, not harder, where drones become the new eyes of the farm, capturing data, generating insight, and guiding every decision. By turning each acre into a source of measurable intelligence, drones are set to make Indian agriculture more productive, resource-efficient, and climate-resilient for the decades ahead.
The author is Co-founder & CEO, ideaForge Technology Limited
Published on November 8, 2025
