Science behind
The GeoPard engine consists of spatial and large-scale data analyses, remote sensing, vegetation indices, math, statistics, machine learning, data clearance, operations on large and complex data sets, and more.

This is challenging, but it allows us to propose valuable services for you.

While the application handles all the automation, novel technologies, sophisticated algorithms, the user interface is intuitive, easy to use, and interpret.
Remote sensing and multispectral analysis
Space technology and imagery are widely used as a foundational data source for precision ag solutions. The multispectral analysis shows the level of absorption or reflection based on detected wavelengths to provide details on plant vigor - visualizing the crops that are flourishing or struggling. It allows for field monitoring and condition assessment in near-real time; define and delineate management zones.

Historical satellite images can be analyzed to identify areas with higher and lower yield potential and consistent problematic areas for scouting. Maps created from such analytics can be used for variable rate crop protection application, fertilization, seeding, soil sampling, yield planning, trial sites selection, land assessment, and more.
Imagery interpretation
All satellite imagery is corrected and optimized for viewing and analysis. Selecting different imagery views allows users to understand their field better by recognizing well developed areas and areas with crop emergence anomaly. These on-the-fly views include:
Natural color
True color composites with red, green, and blue, what you would see from a plane.
Infrared color
Combination of non-visible (near-infrared) and visible (red, green) parts of the spectrum. It increases interpretability of the data: vegetation is in shades of red with highly vegetated areas in bright red, and soil ranges from dark to light green or grey.
EVI2
Enhanced vegetation index, is preferable to NDVI for fields with high canopy density where NDVI may saturate. This view can be used to analyze crops in all growth stages.
LAI
Leaf area index, dimensionless quantity that characterizes plant canopies. Distribution from bare soil to dense canopy. It ranges from the bare ground (index value 0) to the dense canopy (index value is 3.5 and higher for the peak of growing season) and shown in red to green colors.
NDVI
Good crop health indication, representing green vegetation distribution. Though there are limitations when using this view at the start of the growing season (influenced by soil) and at the peak of vegetation (saturation). It is shown from red to green on the map.
GNDVI
Green normalized difference vegetation index. It is more sensitive to chlorophyll difference than NDVI and recommended for crops in early to mid-growth stages. Distribution is from red to green on the map.
GCI
Green Chlorophyll Index. This index is used to evaluate leaf chlorophyll content and applicable for a wide range of plant species. It helps to measure the plant health as chlorophyll content decreases in stressed plants. Distribution is from light green to dark green on the map.


SAVI
Soil adjusted vegetation index minimizes the influences of soil brightness. Most useful at the beginning of the season when plants are separated or in rows and when the soil is clearly visible and to the mid-growth stage when plants are still not touching.
OSAVI
Optimized soil adjusted vegetation index. It is best used in areas with relatively sparse vegetation and for crops in early to mid-growth stages. It is shown using a red to green legend.
NDWI
Normalized Difference Water Index. It is used to differentiate water from the dry land and for water body mapping. It is shown in shades of blue on the map.
Current and multiyear management zones interpretation
Zones are delineated based on imagery, indices, and data processing algorithms.

Different factors can cause field variability zones. Depending on your field you can find areas recognizable as "very sandy", "deep compaction", "proper compaction", "small areas of salinity", "more yield every year", "irrigation problems", "fertility issues", "pest damage", "high or low PH", "lack of moisture"...

The variability factor (VF) reveals the level of heterogeneity in the field. The higher value for multi-year management zones means the greater return on investment from variable rate technology (VRT).
Prescription maps
Field prescription (Rx) files for spraying, seeding, and fertilization are precision agriculture agronomic decisions to optimize inputs, increase yield, and reduce risks.