Measuring plant biomass remotely using drones in arid landscapes

Abstract

Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. We estimated the biomass of individual shrub‐sized plants, using a low‐cost unmanned aerial system (drone), enabling rapid data collection and non‐destructive sampling. We compared volume measurement (a surrogate for biomass) and sampling time, from the simple dimension measurements and drone, to accurate laboratory‐derived biomass weights. We focused on three Australian plant species which are ecologically important to their terrestrial and floodplain ecosystems: porcupine grass Triodia scariosa , Queensland bluebush Chenopodium auricomum , and lignum Duma florulenta . Estimated volume from the drone was more accurate than simple dimension measurements for porcupine grass and Queensland bluebush, compared to estimates from laboratory analyses but, not for lignum. The latter had a sparse canopy, with thin branches, few vestigial leaves and a similar color to the ground. Data collection and analysis consistently required more time for the drone method than the simple dimension measurements, but this would improve with automation. The drone method promises considerable potential for some plant species, allowing data to be collected over large spatial scales and, in time series, increasing opportunities to answer complex ecological and evolutionary questions and monitor the state of ecosystems and plant populations.

Tracking landscape scale vegetation change in the arid zone by integrating ground, drone and satellite data

“…They are also increasingly accessible and affordable, with the versatility of flexible timing and repeat surveys but an increasing need to demonstrate their effectiveness in scientific methods. Drones can capture high‐resolution data (centimetres per pixel), useful for identifying individual leaves on trees, and leaf litter on the ground (McCann et al., 2022). Drones are now referred to as “the third generation source of remote sensing data”, after crewed aircraft and satellites (Simic Milas et al., 2018).…”