Short‐range multispectral imaging is an inexpensive, fast, and accurate approach to estimate biodiversity in a temperate calcareous grassland

Abstract

Image sensing technologies are rapidly increasing the cost‐effectiveness of biodiversity monitoring efforts. Species differences in the reflectance of electromagnetic radiation can be used as a surrogate estimate plant biodiversity using multispectral image data. However, these efforts are often hampered by logistical difficulties in broad‐scale implementation. Here, we investigate the utility of multispectral imaging technology from commercially available unmanned aerial vehicles (UAVs, or drones) in estimating biodiversity metrics at a fine spatial resolution (0.1–0.5 cm pixel resolution) in a temperate calcareous grassland in Oxfordshire, UK. We calculate a suite of moments (coefficient of variation, standard deviation, skewness, and 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 × 1 m quadrats. We find positive associations between the average coefficient of variation in spectral radiance and both the Shannon–Weiner and Simpson's biodiversity indices. Furthermore, 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 a factor of 16 relative to in situ botanical surveys. We demonstrate the utility of multispectral radiance moments as an indicator of biodiversity in this temperate calcareous grassland at a fine spatial resolution using a widely available UAV monitoring system with 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.

A video-rate hyperspectral camera for monitoring plant health and biodiversity

“…It is also seen that the 670 nm trough for this sample is not as deep as for the control and drought samples, which may indicate reduced chlorophyll absorption, consistent with the known effects o f t his t reatment a t t he e xamined site. 44,45 It is also interesting to consider the differences i n r eflectance in th e ne ar-infrared re gion of th e spectrum. High reflectivity i n t he 7 00 -1 100 n m r ange i s c aused b y i ntercellular l ight s cattering.…”

Multispectral data mining: A focus on remote sensing satellite images

“…Change detection using MSI is particularly important for applications related to environmental monitoring, for example, surface water and flood detection (Albertini et al, 2022), shoreline indicators (McAllister et al, 2022), coral reefs mapping (Nguyen et al, 2021), and biodiversity monitoring (Kuenzer et al, 2014; Schulte to Bühne & Pettorelli, 2018). The latter pertains to specific regions, such as forests (Kacic & Kuenzer, 2022), grasslands (Jackson et al, 2022).…”

“…There is potential in improving the change detection results by using spectral signatures given by MSI for solid waste landfill detection and monitoring (Papale et al, 2023). Given the stability of MSI in longitudinal data acquisition, it has higher potential in environmental monitoring using spectral data, for example, animal sensing using their grazing patterns (Kuenzer et al, 2014), flora biodiversity monitoring (Jackson et al, 2022; Kacic & Kuenzer, 2022), and so on. The usability of MSI‐SAR fused can be expanded for biodiversity monitoring, which involves differentiation of ecosystems, vegetation mapping, and geomorphological mapping (Schulte to Bühne & Pettorelli, 2018).…”

An unmanned aerial vehicle pipeline to estimate body volume at scale for ecological monitoring

“…Disturbance to study organisms can also be minimised by considering species-specific hearing sensitivity and operating UAVs at higher altitudes without sacrificing on high resolution data (Duporge et al, 2021). Using UAVs is cheaper and quicker than traditional monitoring methods (Jackson et al, 2022) and can be applied over large spatial scales (Bogdan et al, 2021). To date, though, UAVs have been used for 2D size estimates of individual animals, including at the population scale (Gray et al, 2019; de Kock et al, 2021; Infantes et al, 2022).…”