Everything has a speciﬁc spectral signature. In the same way humans can observe objects with visible light, satellites can observe crops with special spectral bands by looking closely at their invisible spectral signatures.
Each crop has unique spectral signatures that can be measured and quantified, which differ depending on their climatic zones.
Our research team’s unique insights into plant spectrometry allow us to quantify nitrogen needs, plant health, water stress - and many other variables.
Vultus uses multiple satellites from both the private and public sectors to gather satellite image scenes. Using multiple data sets varying in spatial and temporal resolution guarantees subweekly images of any field, anywhere in the world.
Our specialist remote sensing researchers use different wavelengths from the electromagnetic spectrum to monitor crops.
To deliver processed and analyzed satellite data, Vultus has built a cloud-based processing pipeline. The pipeline fetches raw satellite data. Then, geometric, radiometric and atmospheric calibration takes place. We use machine learning to detect clouds, successfully removing 99.4% of them. This ensures high quality and ability to compare data over time.
In addition to the optical remote sensing described above, we also use Synthetic Aperture Radar - a type of microwave remote sensing. Vultus uses C bands, which are sensitive to vegetation and enable us to generate hyper-accurate data about crop needs.
This microwave technology is unaffected by atmosphere effects and illumination - meaning we can penetrate clouds and generate data at nighttime. No matter the weather or time of day, Vultus can generate multiple images of the right fields each week.
Vultus’s specialist researchers are constantly improving and adding new features to our portfolio, deploying the latest in machine learning. Soon, using SAR, we will be able to remote sense biomass and give fungicide prescriptions.
Our patent-pending unique proprietary analysis gives nitrogen recommendations that are accurate down to 10 meters - and are downloadable to an ISOBUS enabled tractor.
The intra-field variations of the crops are measured using spectral, zone and spatial analyses. These are then compared with the current nitrogen spread, the latest international research in nitrogen distribution and historical data to give a variable-rate nitrogen application recommendation.
Our nitrogen recommendations are designed for wheat, barley, rapeseed, maize, millet, rye, bran, sorghum, and potatoes. Our research team is constantly studying and adding new crops.
Vultus uses multispectral analysis to calculate crop health throughout the growing season, with a data resolution of between 3 to 10 meters. Plant Health Analysis is suitable for all crops.
We use a range of different performance indicators, adjusting for crops, soil and growth stage to make sure we have the most accurate health assessments. In addition to our proprietary indices, we also leverage some widely used standard calculations. These include Normalized Difference Vegetation Index (NDVI), Modiﬁed Soil Adjusted Vegetation Index (MSAVI), Normalized Difference Red Edge Index (NDRE) and Red Green Blue (RGB) maps.
The research team is continually adding new performance indicators to make sure the crop health maps are hyper-accurate.
Using the same multispectral analysis, we calculate the Normalised Difference Water Index (NDWI). This helps to readjust irrigation plans, especially useful after extreme weather events - such as droughts or unseasonal rainfall.
Vultus uses a RESTful API that aids farming platforms in their usage of geospatial data. By using this API, our partners can gain access to the satellite services described above and easily integrate them into their platforms. The API service can be conﬁgured with or without our UI components.
Based on polygons of fields provided by the farmer, six different RESTful APIs are available - our Feature API, Nitrogen Recommendation API, Plant Health Analysis API, Water Stress API, Zoning API, and Fetch API. Postman and cURL are used for testing the RESTful API. The API uses open source standards like GeoJSON (RFC 7946), Oauth 2.0 (JWT, RFC 7519), and Open API 3.0 for easy integration into your system.
Our API documentation can be found here.