Accurate determination of surface reference data in digital photographs in ice-free surfaces of Maritime Antarctica

ShetlandsUAVmetry: unmanned aerial vehicle-based photogrammetric dataset for Antarctic environmental research

The study of the functioning and responses of Antarctica to the current climate change scenario is a priority and a challenge for the scientific community aiming to predict and mitigate impacts at a regional and global scale. Due to the difficulty of obtaining aerial data in such extreme, remote, and difficult-to-reach region of the planet, the development of remote sensing techniques with Unmanned Aerial Vehicles (UAVs) has revolutionized polar research. ShetlandsUAVmetry comprises original datasets collected by UAVs during the Spanish Antarctic Campaign 2021-2022 (January to March 2022), along with the photogrammetric products resulting from their processing. It includes data recorded during twenty-eight distinct UAV flights at various study sites on Deception and Livingston islands (South Shetland Islands, Antarctica) and consists of a total of 15,691 high-resolution optical RGB captures. In addition, this dataset is accompanied by additional associated files that facilitate its use and accessibility. It is publicly accessible and can be downloaded from the figshare data repository.

UAVs for Science in Antarctica

Remote sensing is a very powerful tool that has been used to identify, map and monitor Antarctic features and processes for nearly one century. Satellite remote sensing plays the main role for about the last five decades, as it is the only way to provide multitemporal views at continental scale. But the emergence of small consumer-grade unoccupied aerial vehicles (UAVs) over the past two decades has paved the way for data in unprecedented detail. This has been also verified by an increasing noticeable interest in Antarctica by the incorporation of UAVs in the field activities in diversified research topics. This paper presents a comprehensive review about the use of UAVs in scientific activities in Antarctica. It is based on the analysis of 190 scientific publications published in peer-reviewed journals and proceedings of conferences which are organised into six main application topics: Terrestrial, Ice and Snow, Fauna, Technology, Atmosphere and Others. The analysis encompasses a detailed overview of the activities, identifying advantages and difficulties, also evaluating future possibilities and challenges for expanding the use of UAV in the field activities. The relevance of using UAVs to support numerous and diverse scientific activities in Antarctica becomes very clear after analysing this set of scientific publications, as it is revolutionising the remote acquisition of new data with much higher detail, from inaccessible or difficult to access regions, in faster and cheaper ways. Many of the advances can be seen in the terrestrial areas (detailed 3D mapping; vegetation mapping, discrimination and health assessment; periglacial forms characterisation), ice and snow (more detailed topography, depth and features of ice-sheets, glaciers and sea-ice), fauna (counting penguins, seals and flying birds and detailed morphometrics) and in atmosphere studies (more detailed meteorological measurements and air-surface couplings). This review has also shown that despite the low environmental impact of UAV-based surveys, the increasing number of applications and use, may lead to impacts in the most sensitive Antarctic ecosystems. Hence, we call for an internationally coordinated effort to for planning and sharing UAV data in Antarctica, which would reduce environmental impacts, while extending research outcomes.

Vegetation Abundance and Health Mapping Over Southwestern Antarctica Based on WorldView-2 Data and a Modified Spectral Mixture Analysis

In polar regions, vegetation is especially sensitive to climate dynamics and thus can be used as an indicator of the global and regional environmental change. However, in Antarctica, there is very little information on vegetation distribution and growth status. To fill this gap, we evaluated the ability of both linear and nonlinear spectral mixture analysis (SMA) models, including a group of newly developed modified Nascimento’s models for Antarctic vegetated areas (MNM-AVs), in estimating the abundance of major Antarctic vegetation types, i.e., mosses and lichens. The study was conducted using WorldView-2 satellite data and field measurements over the Fildes Peninsula and its surroundings, which are representative vegetated areas in Antarctica. In MNM-AVs, we introduced secondary scattering components for vegetation and its background to account for the sparsity of vegetation cover and reassigned their coefficients. The new models achieved improved performances, among which MNM-AV3 achieved the lowest error for mosses (lichens) abundance estimation with RMSE = 0.202 (0.213). Compared with MNM-AVs, the linear model performed particularly poor for lichens (RMSE = 0.322), which is in contrast to the case of mosses (RMSE = 0.212), demonstrating that spectral signals of lichens are more prone to mix with their backgrounds. Abundance maps of mosses and lichens, as well as a map of moss health status for the entire study area, were then obtained based on MNM-AV3 with around 80% overall accuracy. Moss areas account for 0.7695 km2 in Fildes and 0.3259 km2 in Ardley Island; unhealthy mosses amounted to 40% (49%) of the area in the summer of 2018 (2019), indicating considerable environmental stress.

Monitoring recent changes of vegetation in Fildes Peninsula (King George Island, Antarctica) through satellite imagery guided by UAV surveys

Mapping accurately vegetation surfaces in space and time in the ice-free areas of Antarctica can provide important information to quantitatively describe the evolution of their ecosystems. Spaceborne remote sensing is the adequate way to map and evaluate multitemporal changes on the Antarctic vegetation at large but its nature of occurrence, in relatively small and sparse patches, makes the identification very challenging. The inclusion of an intermediate scale of observation between ground and satellite scales, provided by Unmanned Aerial Vehicles (UAV) imagery, is of great help not only for their effective classification, but also for discriminating their main communities (lichens and mosses). Thus, this paper quantifies accurately recent changes of the vegetated areas in Fildes Peninsula (King George Island, Antarctica) through a novel methodology based on the integration of multiplatform data (satellite and UAV). It consists of multiscale imagery (spatial resolution of 2 m and 2 cm) from the same period to create a robust classifier that, after intensive calibration, is adequately used in other dates, where field reference data is scarce or not available at all. The methodology is developed and tested with UAV and satellite data from 2017 showing overall accuracies of 96% and kappa equal to 0.94 with a SVM classifier. These high performances allow the extrapolation to a pair of previous dates, 2006 and 2013, when atmospherically clear very high-resolution satellite imagery are available. The classification allows verifying a loss of the total area of vegetation of 4.5% during the 11-year time period under analysis, which corresponds to a 10.3% reduction for Usnea sp. and 9.8% for moss formations. Nevertheless, the breakdown analysis by time period shows a distinct behaviour for each vegetation type which are evaluated and discussed, namely for Usnea sp. whose decline is likely to be related to changing snow conditions.

Detection and Delineation of Sorted Stone Circles in Antarctica

Sorted stone circles are natural surface patterns formed in periglacial environments. Their relation to permafrost conditions make them very helpful for better understanding the past climates where they were formed and have evolved and also for monitoring current underlying processes in case circles are active. These metric scale patterns that occur in clusters of tens to thousands of circular elements, can be more comprehensively characterized if automated methods are used. This paper addresses their identification and delineation through the development and testing of a set of automated approaches, namely, template matching, sliding band filter, and dynamic programming. All of these methods take advantage of the 3D shape of the structures conveyed by digital elevation models (DEM), built from ultra-high resolution imagery captured by unmanned aerial vehicles (UAV) surveys developed in Barton Peninsula, King George Island, Antarctica (62°S). The best detection results achieve scores above 85%, while the delineations are performed with errors as low as 7%.

Species-specific effects of passive warming in an Antarctic moss system

Polar systems are experiencing rapid climate change and the high sensitivity of these Arctic and Antarctic ecosystems make them especially vulnerable to accelerated ecological transformation. In Antarctica, warming results in a mosaic of ice-free terrestrial habitats dominated by a diverse assemblage of cryptogamic plants (i.e. mosses and lichens). Although these plants provide key habitat for a wide array of microorganisms and invertebrates, we have little understanding of the interaction between trophic levels in this terrestrial ecosystem and whether there are functional effects of plant species on higher trophic levels that may alter with warming. Here, we used open top chambers on Fildes Peninsula, King George Island, Antarctica, to examine the effects of passive warming and moss species on the abiotic environment and ultimately on higher trophic levels. For the dominant mosses, Polytrichastrum alpinum and Sanionia georgicouncinata, we found species-specific effects on the abiotic environment, including moss canopy temperature and soil moisture. In addition, we found distinct shifts in sexual expression in P. alpinum plants under warming compared to mosses without warming, and invertebrate communities in this moss species were strongly correlated with plant reproduction. Mosses under warming had substantially larger total invertebrate communities, and some invertebrate taxa were influenced differentially by moss species. However, warmed moss plants showed lower fungal biomass than control moss plants, and fungal biomass differed between moss species. Our results indicate that continued warming may impact the reproductive output of Antarctic moss species, potentially altering terrestrial ecosystems dynamics from the bottom up. Understanding these effects requires clarifying the foundational, mechanistic role that individual plant species play in mediating complex interactions in Antarctica's terrestrial food webs.

Evaluation of the use of very high resolution aerial imagery for accurate ice-wedge polygon mapping (Adventdalen, Svalbard)

The main objective of this paper is to verify the accuracy of delineating and characterizing ice-wedge polygonal networks with features exclusively extracted from remotely sensed images of very high resolution. This kind of mapping plays a key role for quantifying ice-wedge degradation in warming permafrost. The evaluation of mapping a network is performed in this study with two sets of aerial images that are compared to ground reference data determined by fieldwork on the same network, located in Adventdalen, Svalbard (78°N). One aerial dataset is obtained from a photogrammetric survey with RGB+NIR imagery of 20cm/pixel, the other from an UAV (Unmanned Aerial Vehicle) survey that acquired RGB images of 6cm/pixel of spatial resolution. Besides evaluating the degree of matching between the delineations, the morphometric and topological features computed for the differently mapped versions of the network are also confronted, to have a more solid basis of comparison. The results obtained are similar enough to admit that remotely sensed images of very high resolution are an adequate support to provide extensive characterizations and classifications of this kind of patterned ground.