Department of Geoinformatics, Cartography and Remote Sensing, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warsaw, Poland
Dr. Anna Zmarz
Department of Geoinformatics, Cartography and Remote Sensing, Chair of Geomatics and Information Systems, Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warsaw, Poland
Effective wildlife management and conservation require reliable assessments of animal abundance. However, no ungulate monitoring methods is entirely satisfying in terms of cost-effectiveness and accuracy. A new method combining unmanned aerial vehicles (drones) and thermal infrared (TIR) imaging may have great potential as a tool for ungulate surveys. Drones enable safe operations at low flying altitudes, and at night – a time that often offers the optimal conditions for wildlife monitoring. To assess the feasibility of the proposed method we used fixed-wing drones with TIR cameras to conduct test surveys in Drawieński National Park, Poland. We demonstrated that ungulate thermal signatures are visible both in leafless deciduous and in pine-dominated coniferous forests. Survey timing highly influenced the results – the best quality thermal images were obtained at sunrise, late evening, and at night. Our preliminary results indicated that thermal surveys from drones are a promising method for ungulate enumeration. We demonstrated that with ground resolution of ~10 cm it is possible to visibly distinguish large species (i.e. red deer) and achieve a good level of area coverage. The main challenges of the method are difficulties in species identification due to relatively low resolution of TIR cameras, regulations limiting drone operations to visual line of sight, and high dependence on weather.
An unmanned aerial vehicle (UAV) as an alternative to manned aircrafts is an excellent, less invasive, safe tool, especially in sensitive polar regions. Here we used a fixed-wing UAV to collect data on seabird and pinniped populations in hardly accessible Antarctic areas. The implementation of an auto-piloted UAV equipped with a digital camera (Canon EOS 700D, 35 mm f/2.0 lens) allowed us to collect high-quality material applicable to a quantitative analysis of the fauna populations. A successful photogrammetric mission, at an altitude of 550 m above sea level, was accomplished during one Beyond Visual Line of Sight flight above hard-to-access Penguin Island and Turret Point Oasis (King George Island). Obtained selected RGB images were processed to generate a panoramic image stitch with resolution of 0.07 m ground sampling distance. A total of 4290 (SD = 33.08) breeding individuals of two penguin species, Adélie (Pygoscelis adeliae) and chinstrap (Pygoscelis antarcticus), 426 (SD = 7.78) individuals of the southern elephant seal (Mirounga leonina) and 6 individuals of the Weddell seal (Leptonychotes weddellii) were identified in both study areas. Additionally, 222 (SD = 2.0) individuals of the southern giant petrel (Macronectes giganteus) and 76 (SD = 1.0) of the Antarctic shag (Phalacrocorax atriceps bransfieldensis) in the Turret Point area were recognized. The presented observations on the natural history of the investigated fauna together with the available literature may be useful in future research on population trends. A comparison with available historical data for both investigated areas suggests a decrease of 68.29% in both penguin species in the 1980–2016 period. The presented results confirmed that UAVs are useful for remote census work for Antarctic seabirds.
Recent developments in unmanned aerial vehicles (UAVs) have resulted in high-resolution digital elevation models (DEMs) of vulnerable coastal environments, including beach–foredune topography. If performed repetitively, they can offer an excellent tool to determine the spatial and temporal changes in the sediment budget, which may be required for proper land management. However, the quality of a UAV, slope parameters, and vegetation significantly influence DEM accuracy. The aim of this study is to compare precise GPS-RTK transects across a section of the South Baltic coast in Poland with those obtained from a DEM based on high-resolution and high-accuracy images obtained by a wind-resistant, high-quality fixed-wing UAV during beyond visual line of sight operation (BVLOS). Different land cover classes, slope inclination, and general curvature, as well as surface roughness, were taken into consideration as possible factors influencing the uncertainty. The study revealed that marram grass greatly affects the accuracy of the UAV-derived model and that the uncertainty of the UAV-derived DEM increases together with increasing slope inclination and, to a lesser degree, with increasing general slope curvature. We showed that sediment budget determinations with the use of a UAV-based DEM are correct only where grass cover is sparse, in our study, up to 20% of the area.
With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively.