Agremo Analyses

Plant Count & Health Monitoring

Agremo is an advanced analytics solution which uses insights extracted from aerial imagery to improve agricultural processes.

Drone-based remote sensing can be used for a variety of purposes in agriculture, from counting plants, early stress detection, and even for yield prediction. Agremo analyses are divided into 2 basic groups: plant counting and health monitoring.

Plant Counting

Plant counting analyses provide information about the exact number of plants. The margin of error is around 2%.

Agremo has developed 3 types of algorithms which are used for plant counting analyses:

  • Template matching
  • Row plant counting
  • Vegetative cover

Each algorithm is associated with a particular variety of input data and plant growing conditions. All algorithms work with both visual imagery and multispectral imagery. Some algorithms require additional inputs, such as recommended sets.

Template Matching

The purpose of the template matching algorithm is to automatically count individual plants in the field from high-resolution drone imagery.

Template Matching is a high-level machine vision technique that identifies parts on an image that match a predefined template (plant). Agremo’s advanced template-matching algorithms have been designed to detect templates regardless of their orientation and local brightness.

The algorithm was developed and tested for perennial crops and vegetables such as bananas, almonds, mango, apples, lettuce, tomato, and many more.

To achieve the best possible results, avoid submitting images with overlaps between individual crops. Besides this, algorithms are unable to count plants during the leaf-off season.

Supported resolution2.5 cm/pixel or less
OutputsPDF report (with statistics), JPG result image, shapefile


Row Plant Counting

The row plant algorithm identifies plant rows, determines the gaps within each row, and uses this kind of information to perform the actual plant count.

The algorithm was developed and tested for field crops (corn, sugarcane, potatoes, etc.). The row plant counting algorithm is particularly useful to farmers and producers when used with high-resolution imagery of post-emergence crops in uniform rows.

The best results with this algorithm can be achieved with parallel and evenly distributed crop rows.


Supported resolution5 cm/pixel or less
Other requirementsDistance between plants
OutputsPDF report (with statistics), JPG result image, shapefile


Vegetative Cover (or Plants Cover)

The purpose of the vegetative cover algorithm is to automatically establish a percentage of vegetation (plants) within a 1-meter (0.5 m) radius of the image. Based on this, it is possible to compute the plant count per area. The result itself is calculated using three clusters: full vegetation 100%, moderate vegetation 50%, and no vegetation 0%.

The algorithm was developed and tested for crops with high density and for cases when individual crops or rows cannot be recognized. The algorithm has been shown to be very efficient for crops at various growth stages such as corn, wheat, canola, cotton, soybeans, sunflower, and many more.

Supported resolution5 cm/pixel or less
Other requirementsInformation on the recommended set
OutputsPDF report (with statistics), JPG result image, shapefile


Plant Health Monitoring

Health monitoring analyses with drone imagery make it possible to measure plant health, identify crop stress and damages from different factors, and thus rapidly eliminate threats on the field. The main purpose of these analyses is to allow users to explore and benefit from detailed agricultural data using modern and reliable technology.

There are two types of plant health monitoring analyses:

  • General stress and specific stress
  • General stress

Plant stress analyses identify the percentage and the exact location of areas with stress. In this context, “stress” refers to plants that have not emerged into healthy plants, areas without plants, areas with diseases, drought, or other yield-limiting factors. Essentially, you get a map with healthy plant areas and all problem-causing areas of your field.

By this definition, roads, rocks, or even non-arable land can be considered stress zones as well.

Supported resolution5 cm/pixel or less
OutputsPDF report (with statistics), JPG result image, shapefile

Specific Stress

To put a name on these problem areas, we recommend performing detailed analyses, based on the issue that has been detected (weed analyses, pest analysis, etc.).

These specific analyses identify the percentage and the exact location of problem areas caused by a specific stress type, such as pests, weeds, or disease.

Supported resolution5 cm/pixel or less
Other requirementsGround truth information
OutputsPDF report (with statistics), JPG result image, shapefile


Plant Stress Analysis (General Stress)

Disease Analysis (Specific Stress)

Weed Analysis (Specific Stress)

The agriculture industry goes hand in hand with technological innovations. New technologies are used to drive results while minimizing costs and time effort. One way to achieve this is by making use of advanced data, which can be provided by drones. In doing so, complex workflows become easier and more efficient.

We know that every agricultural business is different. This is why enterprise users can build customized analyses with our IT and agriculture experts assisting them. If this sounds interesting, get in touch via [email protected] and schedule a free consultation today.

What Our Clients Say About Us

  • Agremo's AI solution turns DJI's drone imagery into actionable insights, and its recipe maps make our AGRAS drone a truly intelligent and precise spraying tool." The integration of the Agremo platform between Agremo and the DJI drone is a turnkey solution for precision agriculture.

    DJI Agriculture

    Smart Farming Team

  • As markets become more defined and customer expectations are increasingly specific, Black Gold believes that we must develop greater awareness of how our crops function. Agremo provides a new window into understanding what is happening in our fields at a more granular level and how to move the needle in the best direction.

    Bryan Bowen

    Director of Agronomy at Black Gold Farms

  • Agremo helps us better understand and adjust to changes throughout the growing season. The flexibility and agility the Agremo team has shown through their platform enable us to adjust and meet changing demands due to weather or pest developments as the season progresses. In addition, the Agremo team consistently listens to feedback to ensure that everything works as described for our specific use cases.

    John Glick

    CIO at Cochranville Ag Service

  • After introducing mapping and crop analysis reports to farmers, they could see their field from another perspective. Agremo is helping us bring essential information to farmers which were impossible to get until recently.

    Ramón Pagán

    Mapping Expert and President @ Caribe Drones // Puerto Rico

  • Agremo’s map is more specific. Competitors break their maps into half-acre grids, but Agremo colors the whole thing exactly how it is. Visually, it’s night and day. A lot of farmers are visual.

    Corey Nohl

    Drone Operator and Farmer @ Above All Aerial // MN, USA

  • With Agremo reports, farmers they can increase productivity, reduce major problems by having early warnings during the early stages of the crops preventing major losses. Bottom line, increase ROI while minimizing losses.

    Miguel Ángel Salgado

    General Manager & Mapping Expert @ Ansar Drone // Mexico

  • The best thing about the plant population reports is the accuracy, which is splendid and it is very important! Great service at eye level with the customer!

    Sune Enevoldsen

    Field Manager and Drone Operator @ Noble Nordmann // Denmark

  • The biggest benefit for farmers who use drones and Agremo reports is that they increase their yields, reduce costs or improve their productivity. In the end, all these benefits are lead to extra profits.

    Ciprian Iorga

    General Manager @ La Orizont // Romania

  • We introduced new farming methods to farmers in Africa, who recognized that Agremo and drones can provide them with quicker, more convenient, efficient and accurate way of gathering decision making information.

    Derrick Annan

    CEO @ Aeroshutter // Ghana

  • With Agremo, we doubled our productivity, and our forestry clients are happy with the Agremo reports necessary for the inventory system as well as a stem map with tree distribution.

    Curt Rogers

    Co-owner @ TimberDrone // USA

  • Of the few vendors who advertised drone imagery analytics, Agremo provided a vastly superior capability. It is extremely important to base any remote sensing assessment in solid ground truth. Agremo clearly excelled over their competitors.

    Konrad Kern

    Image Scientist @ Falcon Aerial Data // USA

  • Agremo Stand Count analysis shows how successful seeding was and how many plants farmers will be able to harvest. Withal, it can help to apply different sowing standards in different parts of the plot, in order to achieve the highest yields.

    Zdravko Hojka

    Agroservice and Product Manager (Maize and Oil Crops), KWS SAAT AG

  • Since we ran our first report with Agremo, both our company and our customers continue to be impressed with the accuracy of the reports compared to our ground truthing. We have leveraged many Agremo reports but find the most value in crop health, weed and stand count analyses. We continue to leverage the Agremo intelligence as a proven way to improve our customers’ bottom line.

    Jeff Buyck

    VP of Precision Ag C&B


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