The outbreak of a pest in a crop constitutes a rapidly spreading biological catastrophe, where accurate damage assessment is critical for insurers and farmers. Traditional manual sampling methods are slow and subjective. This article details how to apply 3D technologies, combining photogrammetry with drones and digital twin simulation, to quantify losses, generate objective expert reports, and anticipate secondary outbreaks, transforming the response to this type of disaster.
Technical Workflow: Photogrammetry and Plot Modeling 🌾
The process begins with aerial capture using drones equipped with multispectral sensors. A programmed flight is conducted at an altitude of 50 meters with an 80% frontal overlap to generate a high-resolution orthomosaic. Photogrammetry software processes the images to create a dense point cloud and a digital surface model (DSM). Using vegetation indices such as NDVI (Normalized Difference Vegetation Index), affected areas are segmented, calculating the damaged leaf area. For volumetric assessment, a 3D mesh of the healthy crop (reference digital twin) is generated and compared with the post-pest model, obtaining the exact loss of biomass in cubic meters, a fundamental data point for the loss report.
Propagation Simulation and the Predictive Digital Twin 🧠
Beyond quantifying current damage, 3D technology allows modeling the evolution of the catastrophe. By integrating historical data on wind, humidity, and temperature into the terrain's digital twin, pest dispersion vectors can be simulated. This allows experts to identify high-risk areas before the damage is visible, optimizing selective spraying. The final result is an interactive visual report for insurers, where each loss is georeferenced in a 3D model, reducing disputes and accelerating compensation, demonstrating that digital prevention is the best defense against a biological catastrophe.
How can a 3D model generated by drone photogrammetry accurately differentiate structural damage caused by a pest from other meteorological phenomena or nutritional deficiencies in a crop?
(PS: Simulating catastrophes is fun until the computer crashes and you are the catastrophe.)