GNSS and unmanned aerial vehicles (UAVs) have revolutionized precise mapping in polar regions. For a team from Queensland University of Technology (QUT), UAVs enabled a flexible platform for deploying hyperspectral imaging (HSI) sensors and collecting high-resolution data, enhanced by GNSS with real-time kinematic (RTK) to ensure accurate geolocation for reliable vegetation analysis.
<p>The team turned to UAVs to meet the unique challenges of monitoring Antarctic vegetation. Harsh conditions, remoteness, limited access and climate variability make traditional field surveys time-consuming and costly. Worse, they risk disturbing sensitive vegetation, explain the researchers. </p> <p><strong>What Grows There. </strong>Antarctica’s terrestrial ecosystems are home to freeze-tolerant vegetation like mosses and lichens, which play a crucial role in biogeochemical cycles, soil insulation and supporting biodiversity. These organisms underpin the continent’s fragile ecosystems, increasingly threatened by climate change, extreme events, and human activitiees. </p> <p>While satellite imagery enables large-scale observations, its limited spectral and spatial resolution, alongside cloud interference, constrains fine-scale vegetation analysis. HSI captures a broad wavelength range, enabling discrimination of vegetation by their spectral signatures. Multispectral imaging (MSI) data, such as that from Sentinel-2, is also being explored.</p> <p>Each technology contributes uniquely: </p> <ul class="wp-block-list"> <li>GNSS RTK provides georeferencing</li> <li>Machine-learning techniques enable precise segmentation</li> <li>UAVs offer flexible spatial coverage and high-resolution datasets. </li> </ul> <p>However, unless these elements are integrated, mapping accuracy diminishes. Moreover, limited validation of spectral libraries and simulated imagery against field data restricts the reliability of remote sensing outcomes.</p> <p>The team’s study addresses current gaps by building on the UAV-based HSI workflow that incorporates ground-based HSI data and MSI. “We expand this approach by integrating UAV-captured HSI data to enhance remote sensing capabilities in polar environments,” researchers explain. The updated methodology combines UAVs, high-resolution red, green, blue (RGB) imagery, and ground and aerial HSI data with machine-learning-based semantic segmentation. </p> <p>The new workflow was evaluated in Antarctic specially protected area (ASPA) 135, Windmill Islands, East Antarctica, focusing on lichen detection and moss health mapping (Fig. 1).</p> <figure class="wp-block-image size-large"><a target="_blank" href="https://www.nature.com/articles/s41598-025-11535-4" target="_blank" rel="noopener"><img decoding="async" width="980" height="1024" src="https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-980x1024.webp" alt="Photo:" class="wp-image-111271" srcset="https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-980x1024.webp 980w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-287x300.webp 287w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-201x210.webp 201w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-768x802.webp 768w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-1470x1536.webp 1470w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1-1960x2048.webp 1960w, https://www.gpsworld.com/wp-content/uploads/2025/07/QUT-Antarctica-Fig1.webp 1994w" sizes="(max-width: 980px) 100vw, 980px" /></a><figcaption class="wp-element-caption">Location of ASPA 135 (6616’60” S, 11032’60” E) and studied vegetation. <strong>(a)</strong> Map of Antarctica showing Casey Station’s location using the Polar Stereographic Projection. <strong>(b)</strong> Map delineating ASPA 135 (purple) near Casey Station (top left). <strong>(c)</strong> Ground-level imagery of moss and lichen at ASPA 135, along with surrounding rock and ice formations. (Credit: QUT)<br><br>Read the full study, “Drone hyperspectral imaging and artificial intelligence for monitoring moss and lichen in Antarctica,” on the<a target="_blank" href="https://www.nature.com/articles/s41598-025-11535-4" target="_blank" rel="noopener"> Scientific Reports website</a>.<a target="_blank" href="https://www.nature.com/articles/s41598-025-11535-4/figures/1" target="_blank" rel="noopener"></a></figcaption></figure> <p></p> <p><p>The post <a target="_blank" rel="nofollow" href="https://www.gpsworld.com/drones-detect-moss-beds-and-changes-to-antarctica-climate/">Drones detect moss beds and changes to Antarctica climate</a> first appeared on <a target="_blank" rel="nofollow" href="https://www.gpsworld.com">GPS World</a>.</p></p>