What is precision agriculture with drones?
Precision agriculture is an approach that uses data to make decisions field by field, instead of treating the whole farm the same way. When combined with drones and computer vision, a flight is transformed into precise, georeferenced information: where plants are missing, which irrigation runs are failing, how many plants there really are.
The difference from "taking pictures with a drone" is in the processing. Computer vision analyzes the field's orthomosaic —the full image assembled from the flight—, detects patterns the eye can't review at that scale and returns an actionable result. What used to take days of scouting or manual analysis is now solved automatically and with greater precision.
Three field analyses with computer vision
A single platform handles three different analyses. The type of flight changes depending on which you need: gaps and plant counting use an RGB camera, while irrigation quality requires a flight with a thermal camera.
1. Gaps and replanting
It detects failures along the rows, assesses planting quality and automatically calculates the replanting units per zone: how much to replant and where to concentrate the operation. With a configurable threshold, you can filter rows by percentage of gaps and prioritize where the production impact is greatest. It's the classic case in crops like sugarcane, where every gap is lost yield.
2. Irrigation quality
This analysis requires a flight with a thermal camera, in addition to the RGB image of the plants. By cross-referencing vegetation and temperature, the platform classifies each hose run into two simple states —irrigating or potentially not irrigating— and paints them on the field map (green and red). At a glance you can see where the runs to verify in the field are concentrated. The analysis is enriched with the climate context (rainfall, solar radiation, evapotranspiration) to explain what the thermal image shows.
3. Plant counting
It takes a plant-by-plant inventory of the crop: automatic counting, actual vs. target density, detection of failures and georeferenced gaps, a replacement map and stand tracking season after season. In crops where every plant counts —like palm— it enables density, replacement and logistics decisions based on real data, not estimates.
More context: climate and satellite imagery
Beyond the flight, the platform incorporates satellite indices (NDVI, NDRE, NDWI, SAVI, among others) in scenes before and after the flight, to read the crop's evolution and vigor over time. Together with the climate, this enriches the diagnosis: it helps you know whether what the analysis shows is worsening or recovering, and to tell an irrigation problem apart from a nutritional one.
From data to recommendation: the Digital Agronomist
Data alone doesn't make decisions. That's why the result —already enriched with climate and satellite imagery— goes through the Digital Agronomist, an artificial intelligence agent built on Scuadra, Bromus's AI agent platform. It drafts an agronomic report per field: it doesn't stop at the number, it interprets it and proposes the next steps, always separating what's confirmed from what's potential. The final decision stays in the hands of the farm's agronomy team; the Digital Agronomist speeds up the path from data to action.
Why it beats traditional monitoring
Six advantages of precision agriculture with drones over field scouting and manual image review:
- More detection and precision: intelligent models that maximize yield per hectare.
- Less replanting time: fast, actionable results to plan sooner and reduce losses.
- Traceability across seasons: comparable data to evaluate performance, identify patterns and adjust practices.
- Lower operating costs: less ground scouting and fewer hours of manual analysis.
- Flexible pay-per-hectare: you pay only for the hectares actually analyzed, with no high fixed costs.
- Integration with external models: detections such as rocks or weeds can be added to broaden the analysis.
How Ranger Vision solves it
Ranger Vision is Bromus Software's precision agriculture platform. From a single drone flight it delivers all three analyses —gaps, irrigation quality and plant counting—, with proprietary processing models, verification by a specialist and a Digital Agronomist that interprets the results. Everything is managed from a web tool by season, with interactive maps and exportable layers ready for your operation.
And because it's part of the Bromus ecosystem, it draws on more than 20 years of experience in production industries and connects with the rest of the solutions —for example, Scuadra's AI agents working on your season data.
Try it free with your own data
Upload your photogrammetric material (photos or an orthomosaic of up to 20 hectares) and evaluate the results on the platform.
Try Ranger VisionFrequently asked questions
What is precision agriculture with drones?
It's an approach that uses computer vision to turn the images from a drone flight into concrete field-management decisions: where to replant, which irrigation runs are failing and how many plants there really are, with georeferenced, actionable results.
What analyses can you run with Ranger Vision?
Three main analyses: gap detection and replanting calculation, irrigation-quality assessment and plant counting, plus crop health with satellite indices. Gaps and counting use an RGB camera; irrigation quality requires a flight with a thermal camera.
How much does it cost?
The model is flexible pay-per-hectare: you pay only for the hectares actually analyzed, with no high fixed costs. There's also a free trial with your own data, of up to 20 hectares.
Does it work for any crop?
It applies to different crops. Gap detection and replanting are typical in sugarcane, and plant counting is key in crops where every plant counts, like palm. The platform adapts to new contexts.