Source-agnostic image acquisition
We acquire images from a variety of sources systematically to ensure a daily flow of data to our customers. Once acquired, images are automatically downloaded into our proprietary processing system, which runs 24 hours a day.
Adjusting for the atmosphere
Haze, smoke and moisture all affect the solar radiation reflected from a plant so corrections must be made to get the most accurate reading from the sensors.
Correcting all the angles
The angle of the sun and the angle of the sensors impact the quality of the data and must be corrected for accuracy and comparison across time and source.
Cross calibration to standardize data
Proprietary software paired with industry leading algorithms ensure consistency across the various imagery sources while capturing every useful pixel.
Cloud and shadow masking
Some clouds are obvious – some are not – but all clouds interfere with quality data. We identify the clouds and their shadows to ensure the data we deliver is clean and clear.
Quality assurance throughout
From beginning to end, we have quality assurance check-points to verify that every pixel that goes into our database is of the highest quality so you can be confident in the decisions you make based on our data.
Storage and delivery
Shortly after acquisition, we’re able to store images by the pixel providing instantaneous access to a variety of maps and indices delivered through user applications.
Geosys acquires imagery from Landsat 8 and Sentinel 2, which are both government run missions that provide free access. Additionally, we source imagery from a wide array of private satellite companies and have contracts with any relevant to agriculture providing scientific grade data. We build an acquisition program based on our customers’ needs by aligning our resources accordingly. This is a very different approach from our competitors who generally utilize one private source in addition to one or both government satellites – presumably because it is very complicated to accurately calibrate multiple sources and can become a time-consuming process without a proper system. Few providers intercalibrate the data and simply show imagery “as is.” Our proprietary processing system is source agnostic, so we can seamlessly take in imagery from any source for calibration, and it’s almost fully automated, so maps are available shortly after image acquisition.
First and foremost, we consider both sources to be valuable options for agriculture. Each has strengths and weaknesses but can be used together to deliver better results. As of today, we have not seen a scalable drone data source able to meet our scientific and quality standards – but we hope to find one soon. The ultimate difference can be boiled down to three main points:
Resolution – in general, drones can deliver at a higher spatial resolution. But higher isn’t always better, as it’s dependent on the need and the use. For example, most commercial variable rate applicators cannot treat zones smaller than 5 meters. You can learn more about resolution here.
Coverage – Satellites can cover larger areas much faster but it’s more complicated to target a specific spot, which makes satellites better equipped for monitoring large areas and drones better equipped for precise scouting.
Resources – Running a drone requires extra resources, be it time or money. Additionally, because it takes a drone multiple passes to cover a field – creating different view angles and acquisition conditions – extra work needs to be done to stitch together imagery to get the full picture. Satellites are constantly acquiring imagery and systems like ours provide easy access.
Our primary focus is large row crops, pastures and sugar cane. If you have needs for other crops, contact us to discuss capabilities and options.
There are many factors affecting yield and many ways to measure them, but the best information comes from the plants themselves — think of them as tens of thousands of sensors per hectare. Geosys uses satellite imagery to give you an accurate and unbiased view of crop’s potential by analyzing sun light reflectance. Higher potential crops absorb more of some light wavelengths and reflect more light from other wavelengths. Geosys uses reflectance to calculate crops health indices, such as NDVI, EVI, CVI and GNDVI – one of the many layers of data in our proprietary products and the custom solutions we create for our clients. You can learn more about how satellites measure plant health here.