Unoccupied aerial vehicle (UAV) based structure-from-motion (SfM) photogrammetry surveys are becoming a standard tool for ecologists to measure plant structure and biomass in non-forest ecosystems. The reproducibility of SfM survey results under different operational conditions, namely wind speed, sun elevation and cloud condition, is poorly understood. It is also unclear to what extent commonly applied point-to-grid interpolation of derived point clouds affects inference of vegetation structure. These knowledge gaps limit the use of these methods for measuring and monitoring detection.

We captured 61 UAV SfM surveys at the same study area under a range of wind/sun/cloud conditions over a 24-day period during 2021 and used generalised linear mixed effects models to test how the structural reconstructions varied with environmental conditions.

Wind speed significantly influenced the canopy height reconstructions, with greater wind speeds reducing mean canopy height. Different plant species exhibited varying sensitivities to wind that are likely related to leaf attributes (size, structure, and density), growth form of the canopy, and physical properties such as limb flexibility. The movement of plants can reduce canopy height estimates derived from photogrammetric surveys, even under relatively low wind speeds. Reconstructed canopy heights were comparatively insensitive to solar elevation variations. Cloud conditions and illumination by direct sunlight had a weak, non-significant effect on reconstructed canopy height, with sunny conditions (generating shadows) resulting in a measurable but marginal reduction in mean canopy heights.

When comparing canopy heights of interpolated and discontinuous derived canopy height models the results highlighted that these were insensitive to interpolation in this specific setting.

We recommend measuring mean wind speeds throughout surveys where comparisons are to be made between different drone based SfM surveys of vegetation over either time or space. Care should be taken to ensure that the effects of wind are controlled for so that inferences are valid.

To provide a controlled and high-quality data set for analysing the potential effect of wind and solar illumination on the results of UAV-derived SfM, we designed an experiment to collected 61 surveys over the same study site under a range of naturally different wind/sun/cloud conditions during a 24-day period in 2021. The study site is situated at Boldventure, near Eworthy mid Devon (Latitude 50.741,Longitude ‑4.213). The site is bounded by taller trees forming the field margins on three sides enclosing a former pasture now being allowed to naturally regenerate to scrub and woodland. We surveyed an 80 m x 100 m area encompassing a tree and shrub encroached grassland with extensive patches of Gorse (Ulex europaeus), Eared Willow (Salix aurita), and Birch (Betula sp). The grassland is a rough pasture dominated by Tall Fescue (Festuca arundinacea) grass on a soil classified as slowly permeable seasonally wet acid loamy and clayey soil (LandIS, 2023).We employed the data collection protocol (v1.6.4) for measuring above-ground biomass with drone photogrammetry established by Cunliffe and Anderson (2019). A consistent flight plan was used for all 61 surveys. Image data were captured using a DJI Phantom 4 RTK drone equipped with a 20MP RGB camera (model FC6310R). Each survey consisted of two flights, the first flight with a nadir camera angle took place at 28 m above-ground level (agl) with a 10 m margin. The second flight acquired convergent images using a camera angle of 25 degrees from vertical and was flown at a height of 31 m agl with a 10 m margin. A forward and side overlap of 75 % was used for all image acquisition, together capturing at least 30 images for each part of the study area. In total ca. 328 images were acquired for each survey.

To precisely geolocate each drone image we used a DJI D-RTK2 mobile global navigation satellite system (GNSS) base station, set up over a known point geolocated using a survey-grade Leica GNSS. To verify the accuracy of the photogrammetric reconstruction and spatial alignment between the datasets, 10 Ground Control Markers were distributed across the survey plot and geo-located to ≤ 15 mm horizontally and 20 mm vertically with the Leica GNSS.

In order to gather data to assess the repeatability and reproducibility of photogrammetric reconstructions of plant height, a total of 61 surveys were flown on 12 days under different weather conditions over the period 15th August to 7th September 2021. The survey period was timed for peak biomass when there would be minimal change in the plant canopy heights (due to plant growth or senescence) and our approach assumes that there were no changes to plant structure during this period. To encompass a range of sun elevation conditions, surveys were flown at different times each day. Detailed observations were made of cloud cover, temperature, relative humidity, and wind speed for each survey (Table S1). Wind speed, temperature and humidity were measured using a data logging weather station set to log data every 20 seconds. In addition, the length of time during the survey that the study area was in direct sunlight (and shadows were present) was recorded by stopwatch and converted into a % of survey duration that was illuminated by direct sunlight (referred to as “sun percent”). Sky codes for qualitative classification of cloud related ambient light conditions were recorded (Table S2) after Assmann et al. (2018). The elevation of the sun for the time of the mid-point of each drone survey was calculated using suncalc.org (Hoffman 2023).