Methods of estimating the total amount of above-ground biomass (AGB) in crop fields are generally based on labourious, random, and destructive in situ sampling. This study proposes a methodology for estimating herbaceous crop biomass using conventional optical cameras and structure from motion (SfM) photogrammetry. The proposed method is based on the determination of volumes according to the difference between a digital terrain model (DTM) and digital surface model (DSM) of vegetative cover. A density factor was calibrated based on a subset of destructive random samples to relate the volume and biomass and efficiently quantify the total AGB. In all cases, RMSE Z values less than 0.23 m were obtained for the DTM-DSM coupling. Biomass field data confirmed the goodness of fit of the yield-biomass estimation (R2 = 0,88 and 1,12 kg/ha) mainly in plots with uniform vegetation coverage. Furthermore, the method was demonstrated to be scalable to multiple platform types and sensors.
Infrared thermography (IRT) techniques for building inspection are currently becoming increasingly popular as non-destructive methods that provide valuable information about surface temperature (ST) and ST contrast (delta-T). With the advent of unmanned aerial vehicle (UAV)-mounted thermal cameras, IRT technology is now endowed with improved flexibility from an aerial perspective for the study of building envelopes. A case study cellar in Northwest (NW) Spain is used to assess the capability and reliability of low-altitude passive IRT in evaluating a typical semi-buried building. The study comparatively assesses the use of a pole-mounted FLIR B335 camera and a drone-mounted FLIR Vue Pro R camera for this purpose. Both tested IRT systems demonstrate good effectiveness in detecting thermal anomalies (e.g., thermal bridges, air leakages, constructive singularities, and moisture in the walls of the cellar) but pose some difficulties in performing accurate ST measurements under real operating conditions. Working with UAVs gives great flexibility for the inspection, but the angle of view strongly influences the radiometric data captured and must be taken into account to avoid disturbances due to specular reflections.