THE DRONE COLLAB JOURNAL
Explore practical photogrammetry, GNSS, IMU, GIS and remote sensing methods. Technical explanations, worked examples and field checks for the people turning aerial photographs into usable maps.
Drone-derived crown and height observations can describe forest structure, while biomass estimation requires an appropriate empirical or physical relationship and field reference data.
Canopy height is commonly represented by subtracting a terrain surface from an upper-canopy surface.
Restoration survival monitoring should start with planting records, species and dates.
Canopy gaps describe openings in the upper forest surface and their spatial pattern.
The minimum mapping unit defines the smallest object or area the project will report consistently.
Change detection compares observations made at different times, so it inherits the uncertainty of both datasets.
A map can achieve high overall accuracy while missing most rare targets because common background dominates the evaluation.
Thermal cameras estimate radiometric properties that processing converts into apparent temperature under assumptions.
A crop time series needs consistent geographic support and a reliable calendar of planting, management and observations.
Pixel classification labels local image measurements, while object-based work groups pixels into crowns, beds, patches or other units.
Drone classification evaluation should reflect where the map will be used.
Satellite imagery can provide broad spatial context and repeat observations, while drones can examine selected areas in finer detail.
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