Aug 2026· Drones· Vol 10, pp. 625· 0 citations· 47 references
Abstract
Abandoned, lost, or otherwise discarded fishing gear (ALDFG) is a persistent form of marine pollution requiring survey approaches capable of resolving individual items across large spatial extents. While uncrewed aerial vehicles (UAVs) can capture imagery at resolutions sufficient to resolve individual debris items, their use remains largely constrained to visual line-of-sight (VLOS) operations, limiting large-scale coastal monitoring. This case study develops and field-tests an operational framework for low-altitude beyond visual line-of-sight (BVLOS) UAV surveys, in which DEM-based communication viewshed modelling incorporating first Fresnel zone clearance is used to plan BVLOS missions. A lightweight fixed-wing UAV flown at 60 m AGL completed 20 missions across 210 km of remote northern Australian coastline. Communication viewshed modelling reliably guided mission planning with 90.5% of waypoints placed within predicted high-clearance zones maintaining moderate-to-strong command-and-control (C2) link quality in flight. Manual screening confirmed that the resulting imagery was of sufficient quality, with 291 derelict fishing nets detected. In a simulated VLOS operational scenario, 76.3% of these detections fell beyond VLOS range, and equivalent coverage would require an estimated 8.8-fold increase in mission count. These findings demonstrate that fixed-wing UAVs operating under low-altitude BVLOS conditions can support large-scale image acquisition in remote coastal areas, particularly when enabled by communication-aware mission planning.
Accurate bathymetric data are essential for the design and monitoring of coastal structures, but conventional multibeam surveys are costly and often impractical in shallow or confined areas. We evaluate a single-beam echosounder (SBES, ECT400) suspended beneath an unmanned aerial vehicle (UAV) as a rapid method with low logistical requirements for bathymetric monitoring of coastal infrastructure. Fieldwork was performed in an operational dry dock that was alternately drained and filled, enabling direct geometric validation against an ultra-high-resolution photogrammetric DEM (0.55 cm GSD). The co-registered dataset comprises N = 16,137 sonar returns to depths of ≈ 8 m. The UAV-mounted SBES produced a mean depth difference of 0.15 m (SD = 0.58 m) relative to the photogrammetric reference. From these residuals we estimate a 95% Minimum Detectable Change (MDC95) of ≈ 0.5 m when changes are assessed by aggregating repeated co-located passes. These results indicate that the UAV-SBES workflow is suitable as a Tier-1 screening tool for structural-health monitoring, effective for detecting metre- to decimetre-scale changes and triaging sites for targeted high-precision follow-up, but not for micrometre/mm-scale deformation monitoring. The method’s portability and vessel-free operation make it especially useful for frequent inspections in shallow, confined coastal settings.
Bethsaide Souza-Santos, M. Arza-García, J. Ortiz-Sanz et al.· Journal of Civil Structural...· 0 citations
This study evaluated a cost-effective UAV-based multi-sensor approach for characterizing river corridor conditions during and after moderate floods in two mountain river corridors in Northern Utah, USA: the Logan River and Blacksmith Fork River. These study reaches included urban, rural, and agricultural areas, hydraulic structures and bridges, and fish passage structures. A DJI Matrice 300 UAV was used with two separate payloads: an AgEagle Altum-PT multispectral camera and an R3 Pro V2 two-return LiDAR system. The workflow included UAV flight planning and data collection, post-processing of the multi-spectral and LiDAR sensor data, spatial resolution and accuracy assessment, and interpretation of the resultant data. The multi-spectral post-processing produced pansharpened orthomosaics with a spatial resolution of 0.0432 m, while the UAV LiDAR produced DSM/DTM products at 0.05 m resolution. LiDAR accuracy assessment showed vertical RMSE values of approximately 0.0602 m for the Blacksmith Fork and 0.0782 m for the Logan River. The results showed that multispectral imagery and 2-band LiDAR provided a cost-effective means for detailed remote sensing with each sensor providing complementary information for flood and river corridor assessment. Multispectral imagery supported interpretation of flood extent, vegetation condition, relative turbidity, and thermal patterns, while LiDAR captured terrain and surface features such as banks, levees, floodplain surfaces, channel modifications, and structures. The integrated datasets supported maximum flood extent mapping and flood-level estimation. These datasets can support reach-scale hydraulic modeling, catchment hydrology, river corridor ecology, floodplain conditions, and real-time monitoring of floods, in addition to quantification of flood hazards or post-flood impacts for municipalities and insurers.
Ishwar Joshi, I. Gowing, B. Crookston· Water· 0 citations
Wildfires in California increasingly threaten communities and ecosystems. However, comprehensive estimation of fire dynamics and fuel structure remains limited. Recent advances in Uncrewed Aerial Vehicle (UAV) technology and high-spatial-resolution mapping have provided increasingly important tools for estimating wildfire fuel-height loss across fuel types. This study used a one-year Uncrewed Aerial Vehicle (UAV) time series to quantify fuel-height loss and vegetation regrowth associated with a prescribed upslope canyon fire near Salinas, California, USA. Multispectral, infrared, and visible UAV imagery collected before, during, and after burning was used to generate orthomosaic, digital surface models (DSMs), fuel-type classifications, and surface-volume estimates. To enable reliable pre- and post-fire comparison, ground control points and tie points were used to train linear regression calibrations that corrected angular discrepancies and elevation offsets among time-series DSMs. Calibrated DSMs were then integrated with ecological field measurements to map fuel-height consumption and post-fire recovery at the individual-plant scale. UAV-derived fuel-height change was associated with in situ twig-diameter measurements, which provide field-based indicators of fire effects in chaparral vegetation, while the maximum recorded temperature explained only a small proportion of variation in fuel-height loss. This workflow can support integrated fire ecology and remote-sensing studies by providing repeatable measurements of post-fire changes in vegetation structure.
Xiangyu Ren, David Benterou, J. Allen et al.· Drones· 0 citations
This study assesses the capabilities of UAV-based Earth observation for analyzing marginalized communities, using Roma settlements in southeastern Slovakia as a case study. Marginalized populations are often underrepresented in official spatial datasets, resulting in a limited understanding of their living conditions, infrastructure needs, and environmental risks. To address this gap, we propose a multi-scalar, UAV-based observational approach that bridges the limitations of coarse satellite imagery and logistically constrained ground surveys. High-resolution RGB and thermal imagery were acquired across three settlements with varying spatial characteristics and processed using photogrammetric workflows to generate detailed orthophotos and spatial products. The results demonstrate that UAV data with centimeter-level spatial resolution enable precise mapping of settlement morphology, infrastructure, waste distribution, and thermal inequalities. Furthermore, UAV observations enable change detection and environmental risk assessment at scales that are not achievable with conventional remote sensing. However, the study also highlights critical operational and ethical challenges, including regulatory constraints, privacy concerns, and the need for community engagement. By integrating technical evaluation with socially sensitive research practices, this work proposes a methodological framework for responsible UAV deployment in marginalized contexts. The findings underscore the potential of UAV-based observation to improve spatial visibility and support evidence-based planning while emphasizing the importance of ethical implementation.
F. Dadrass Javan, L. Ihnacik, P. Blišťan et al.· Remote Sensing· 0 citations
As the use of uncrewed aerial vehicles (UAVs), ranging from small drones to large person‐transport vehicles, continues to expand, detailed wind and turbulence observations near surface in urban areas are crucial for safe flight planning. In summer 2021, a field campaign was conducted in the suburbs of Seoul, South Korea, using a UAV equipped with a sonic anemometer. Horizontal winds were measured at 1‐Hz up to 150 m above ground level. From 1‐Hz winds, turbulence is estimated in terms of the energy dissipation rate using inertial dissipation methods. Stronger turbulence was observed at lower altitudes near surface than at higher altitudes, likely due to surface shears and possibly buoyancy effects. Regionally, strong turbulence was found along riverside walk roads compared to building‐surrounded areas, likely due to flows blocked by buildings. Results highlight need for UAV flight planning that accounts for turbulence across altitudes and urban structures, supporting safer flight routing.
Soo‐Hyun Kim, Jung‐Hoon Kim, Jeonghoe Kim et al.· Geophysical Research Letters· 1 citation
Since the 1970s, numerous vessel and aerial surveys of marine birds, covering many thousands of square kilometers, have been conducted in the California Current System (CCS), providing insights into seabirds' horizontal (2D) diversity and abundance, including the identification of “hotspots.” Addressing knowledge gaps regarding seabird distribution patterns from a 3D (vertical) perspective, however, will be required if California (CA) is to use offshore wind (OSW) facilities to assist in reaching the state's 2045 renewable energy goals. Such an analysis will allow seabirds' vertical distribution to be considered when assessing potential OSW impacts, as collision vulnerability is greatest for birds flying at heights overlapping turbine rotor-swept zones (RSZ). This probability is determined by the interaction of species-specific morphology and flight-style with wind speed. Thus, predicting the proportion of seabirds moving at RSZ heights can be achieved by quantifying: (1) the likelihood that significant numbers of individuals of various species, of those present, will reach RSZ heights across the full spectrum of wind speeds, (2) species-specific density in 2D space, and (3) the windscape. To address these goals, we describe a novel 3D Seabird Collision Vulnerability Framework (3D Framework) that integrates historical at-sea observations with the offshore windscape to predict the densities of 44 species with sufficient sample sizes to support a 3D assessment of their expected distribution below versus within RSZ heights. The prediction region encompasses all offshore waters capable of supporting current OSW mooring technologies, which, in CA and southern Oregon, includes waters overlying the continental shelf and upper continental slope. This 3D Framework can be modified to incorporate new data and new locations as the OSW industry expands. This effort supports the broader goal of identifying sites within the CCS that optimize power generation while minimizing interactions with seabird species whose flight behavior makes them vulnerable to collision.
S. Schneider, Eli Wallach, C. Chamberlin et al.· Marine Ornithology· 1 citation· ⚡1