Gamaya leverages a combination of technologies from remote sensing to machine learning and agronomy to develop customized digital agronomy solutions to address our customers and partners needs.
Gamaya makes hyperspectral imaging
a cost-effective and accessible solution for farming operations around the world. Our proprietary lightweight hyperspectral camera can be attached easily to drones, aircraft and other remote sensing devices to measure the visible, near- and infrared light portions of the electromagnetic spectrum, thereby providing more profound insights about plants and fields than has ever been possible.
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Benefits of hyperspectral:
Most advanced and information-rich technology to provide early detection of complex problems such as diseases, stresses, and nutrient deficiency
Capability to characterize a wide range of chemical and biological traits of plants
The technology allows catching all kinds of variability (crop varieties, weather, soil types, growing conditions)
High-flexibility to target very specific and challenged problems that can't be addressed using existing technology
Recognizing that not all crop problems need HSI to identify them, Gamaya is also building capabilities to develop and launch RGB and multi-spectral imaging products, enabling it to provide a suite of imagery-related products to clients and partners in multiple crops and regions.
Gamaya’s vision is that ultimately it will develop all products using its drone-mounted HSI technology to capture maximum insights from the crop, then commercialize the products by correlating the HSI signal to satellite imagery.
A fusion between multispectral satellite imagery and drone-based HSI imaging data provides
the benefits of both satellites and drones, scalability and high resolution, that is required
to characterize different crop properties. This makes Gamaya unique in the industry, and provide tremendous value to growers –
the precision of HSI, with the scalability of satellites.
Plants with different physiology and characteristics reflect light differently. Spectral imaging and HSI in particular, and its ability to capture reflectance in a much more detailed and precise way, allows us to detect problems such as diseases, nutrient deficiencies, and other challenging crop issues.
We have developed machine learning and computer vision algorithms that power our AI models to deal effectively with the vast amount and complexity of the data that is ingested. Our software translates raw data into actionable information by using machine learning and AI.
This way, we are able to provide robust analysis and crop management advice for all kinds of challenges presented by the diverse conditions of agricultural crops. Our detailed crop models and a database of the spectral signatures of different crop-affecting factors create local crop intelligence that scales globally.