Atfarm provides regularly updated satellite imagery and biomass maps to help you monitor crop health and optimise fertiliser application.

You can choose from three types of biomass maps to view variability within your field:

• NDVI map
• Optimised map
• N-uptake map

Each biomass map applies a specific vegetation index to a cloud-free satellite image to measure crop health and growth. The result is a biomass map that shows variability in the field, which can be used to plan fertiliser applications and create Variable N-Rate Application maps.

NDVI map

The NDVI map provides a relative measure of vegetation health using the Normalized Difference Vegetation Index (NDVI). It helps visualise variations in biomass and nitrogen availability in the field.

NDVI measures how vegetation reflects red and near-infrared light and calculates a value between zero and one. This value indicates the presence or absence of green biomass, with darker green areas representing higher biomass and nitrogen availability. The map uses a fixed green colour scale to display these variations.

When to use the NDVI map

NDVI is most effective in early growth stages, when crop biomass is still developing. However, as the canopy closes and biomass increases, NDVI reaches saturation, making it harder to distinguish between high and low biomass areas.

For more accurate nitrogen application planning, regardless of growth stage, we recommend using the optimised map or N-uptake map, which provide better results throughout the season.

Optimised map

The optimised map allows you to examine in-field variability across all nitrogen application stages and create Variable N-Rate Application maps for precise fertilisation.

Why use the optimised map

Unlike traditional biomass indices, the optimised map is based on the Yara N-Sensor Index, which makes it more reliable for nitrogen application throughout the season.

The Yara N-Sensor Index can detect biomass differences during and after shooting. This is because it measures not only red and near-infrared radiation but also the spectral ranges in between. With this fine gradation and the inclusion of crop and regional data, the N-uptake can be accurately estimated, even in advanced growth stages where NDVI is no longer effective.

Read more about the Yara N-Sensor Index

Understanding the colour scale

The optimised map uses a relative colour scale based on the lowest and highest index values in a satellite image:

• Brown tones indicate low biomass/N-uptake
• Green shades show canopy evolution
• Blue and purple tones represent advanced canopy stages

With the optimised map, you can make informed fertilisation decisions throughout the entire growing season, ensuring optimal nitrogen management at every stage.

N-uptake map

The N-uptake map shows the daily absolute field average N-uptake in kg N/ha at different growth stages for certain crops. It helps identify nitrogen variability within a field and supports Variable N-Rate Applications.

You can use the N-uptake map to plan your first in-season dressing (BBCH 20) for cereals, as well as for second, third, and protein dressings.

How the N-uptake map works

This biomass map has been developed and validated using data from field trials and passive measurements with the Yara N-Sensor. The above-ground N-uptake is calculated for each pixel using the latest available cloud-free satellite image. It represents the total nitrogen absorbed by the crops up to the time the image was taken.

Understanding the colour scale

The legend follows a dynamic scale, meaning values may differ based on the field's nitrogen variability. The scale ranges from yellow to dark green:

• Yellow represents the lowest N-uptake (approximately -30 kg N/ha from the daily field average).
• Dark green represents the highest N-uptake (approximately +30 kg N/ha from the daily field average).
• This means the total variance within a field can reach up to 60 kg N/ha.

Crop availability and accuracy

The N-uptake map is available for several crops. Its accuracy is optimised for specific growth stages and may be less precise for unspecified growth stages.