Flexible estimation of biodiversity with short-range multispectral imaging in a temperate grassland

O_LIImage sensing technologies are rapidly increasing the cost-effectiveness of biodiversity monitoring efforts. Species differences in the reflectance of electromagnetic radiation have recently been highlighted as a promising target to estimate plant biodiversity using multispectral image data. C_LIO_LIHowever, these efforts are currently hampered by logistical difficulties in broad-scale implementation and their use in characterizing biodiversity at different spatial scales. C_LIO_LIHere, we investigate the utility of multispectral imaging technology from commercially available unmanned aerial vehicles (UAVs, or drones) in estimating biodiversity metrics at short-range (<10 m image recording height) in a temperate calcareous grassland ecosystem in Oxfordshire, UK. We calculate a suite of moments (coefficient of variation, standard deviation, skew, kurtosis) for the distribution of radiance from multispectral images at five wavelength bands (Blue 450{+/-}16 nm; Green 560{+/-}16 nm; Red 650{+/-}16 nm; Red Edge 730{+/-}16 nm; Near Infrared 840{+/-}16 nm) and test their effectiveness at estimating ground-truthed biodiversity metrics from in-situ botanical surveys for 37 - 1 m x 1 m quadrats. C_LIO_LIWe find positive associations between the average coefficient of variation in spectral radiance and both the Shannon-Weiner and Simpsons biodiversity indices. Furthermore, we find that the average coefficient of variation in spectral radiance is consistent and highly repeatable, across sampling days and recording heights. Positive associations with biodiversity indices hold irrespective of the image recording height (2-8 m), but we report reductions in estimates of spectral diversity with increases to UAV recording height. UAV imaging reduced sampling time by 16-fold relative to in-situ botanical surveys. C_LIO_LISynthesis - We demonstrate the utility of multispectral radiance moments as an indicator of grassland biodiversity metrics at high spatial resolution using a widely available UAV monitoring system at a coarse spectral resolution. The use of UAV technology with multispectral sensors has far-reaching potential to provide cost-effective and high-resolution monitoring of biodiversity in complex environments. C_LI