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Arctic sea ice is constantly moving and covered with low-textured surfaces, making it difficult to generate reliable digital surface models (DSMs) from drone images. The movement of sea ice makes georeferencing of DSMs difficult, and the low-textured surfaces of sea ice cause the uncertainty of image matching. This paper proposes a robust method to generate high-quality DSMs for drifting sea ice. To overcome the challenges, the proposed method introduces four improvements to the object-space-based image-matching pipeline: relative georeferencing to recover the horizontality and scale of sea-ice DSMs using a terrestrial light detection and ranging (LiDAR) dataset, match inspection to verify the matched points using several matching constraints, adaptive search-window adjustment to ensure distinct texture information through simple texture analysis, and robust vertical positioning to reduce the matching uncertainty via matching-indicator modeling. Performance evaluations were conducted with drone and LiDAR datasets obtained from a sea-ice campaign using the Korean Icebreaker Research Vessel (IBRV) Araon in the summer of 2017. The experimental results indicated that the proposed method can achieve significant quality enhancements compared with the existing matching method and that all the considerations contributed significantly to the enhancements.

Surface roughness of sea ice is primary information for understanding sea ice dynamics and air–ice–ocean interactions. Synthetic aperture radar (SAR) is a powerful tool for investigating sea ice su...

The majority of biogeographic studies in Antarctic terrestrial ecosystems have focused on macroscopic eukaryote taxa. In contrast, microbial taxa have been almost neglected or examined without sufficient spatial coverage. Here, we examined the spatial distribution of soil bacterial communities and their relation to local environmental gradients in ice-free regions of the maritime Antarctic. Soils in this region were dominated by Actinobacteria and Proteobacteria, which are typically found in Antarctic soils. Notably, candidate divisions AD3 and WPS-2, which rarely occur in other biomes, were found in high abundance in acidic surface soils. Soil pH and total organic carbon (TOC) were the primary drivers of the bacterial community structure and various geochemical variables also played important roles in structuring bacterial community composition. Bacterial communities were significantly correlated to measured environmental variables, most of which are spatially structured at the local spatial scale (0.5–8 km). This suggests that spatial heterogeneity of environmental factors is an important driver of shifts in bacterial communities. Although various sets of environmental variables were related to bacterial communities, a large proportion of community variation remained unexplained. This indicates that bacterial communities in Antarctic soils may be governed by other biotic or abiotic factors which are not typically measured in other biome studies.

Although microorganisms are the very first colonizers of recently deglaciated soils even prior to plant colonization, the drivers and patterns of microbial community succession at early-successional stages remain poorly understood. The successional dynamics and assembly processes of bacterial and fungal communities were compared on a glacier foreland in the maritime Antarctic across the ~10-year soil-age gradient from bare soil to sparsely vegetated area. Bacterial communities shifted more rapidly than fungal communities in response to glacial retreat; species turnover (primarily the transition from glacier- to soil-favouring taxa) contributed greatly to bacterial beta diversity, but this pattern was less clear in fungi. Bacterial communities underwent more predictable (more deterministic) changes along the soil-age gradient, with compositional changes paralleling the direction of changes in soil physicochemical properties following deglaciation. In contrast, the compositional shift in fungal communities was less associated with changes in deglaciation-induced changes in soil geochemistry and most fungal taxa displayed mosaic abundance distribution across the landscape, suggesting that the successional dynamics of fungal communities are largely governed by stochastic processes. A co-occurrence network analysis revealed that biotic interactions between bacteria and fungi are very weak in early succession. Taken together, these results collectively suggest that bacterial and fungal communities in recently deglaciated soils are largely decoupled from each other during succession and exert very divergent trajectories of succession and assembly under different selective forces.

Sentinel-1 C-band synthetic aperture radar (SAR) images can be used to observe the drift of icebergs over the Southern Ocean with around 1–3 days of temporal resolution and 10–40 m of spatial resolution. The Google Earth Engine (GEE) cloud-based platform allows processing of a large quantity of Sentinel-1 images, saving time and computational resources. In this study, we process Sentinel-1 data via GEE to detect and track the drift of iceberg B43 during its lifespan of 3 years (2017–2020) in the Southern Ocean. First, to detect all candidate icebergs in Sentinel-1 images, we employ an object-based image segmentation (simple non-iterative clustering – SNIC) and a traditional backscatter threshold method. Next, we automatically choose and trace the location of the target iceberg by comparing the centroid distance histograms (CDHs) of all detected icebergs in subsequent days with the CDH of the reference target iceberg. Using this approach, we successfully track the iceberg B43 from the Amundsen Sea to the Ross Sea, and examine its changes in area, speed, and direction. Three periods with sudden losses of area (i.e. split-offs) coincide with periods of low sea ice concentration, warm air temperature, and high waves. This implies that these variables may be related to mechanisms causing the split-off of the iceberg. Since the iceberg is generally surrounded by compacted sea ice, its drift correlates in part with sea ice motion and wind velocity. Given that the bulk of the iceberg is under water (~30–60 m freeboard and ~150–400 m thickness), its motion is predominantly driven by the westward-flowing Antarctic Coastal Current (ACoC) which dominates the circulation of the region. Considering the complexity of modeling icebergs, there is a demand for a large iceberg database to better understand the behavior of icebergs and their interactions with surrounding environments. The GEE-based semi-automated iceberg tracking method presented here can be used for this purpose.

Estimating the sea ice drift field is of importance in both scientific study and activities in the polar ocean. Ice motion is being tracked at large scale (10 km and larger) on a daily basis; however, a higher resolution product is desirable for more reliable monitoring of rapid changes in sea ice. The use of wide-swath SAR has been extensively studied; yet, recent high-resolution X-band SAR sensors have not been tested enough. We examine the feasibility of KOMPSAT-5 and COSMO-SkyMed for retrieving sea ice motion by using the dataset of the MOSAiC expedition. The ice drift match-ups extracted from consecutive SAR image pairs and buoys for more than seven months in the central Arctic were used for a performance evaluation and validation. In addition to individual tests for KOMPSAT-5 and COSMO-SkyMed, a cross-sensor combination of two sensors was tested to overcome the drawback, a relatively long revisit time of high-resolution SAR. The experimental results show that higher accuracies are achievable from both single- and cross-sensor configurations of high-resolution X-band SARs compared to wide-swath C-band SARs, and that sub-daily monitoring is feasible from the cross-sensor approach.

On-site high-resolution sea ice images from the imaging instruments on airplane, helicopter, ship and unmanned aerial vehicle (UAV) platforms have been used as the reference datasets for validation of the sea ice properties. Among the low altitude remote sensing platforms, helicopters usually carried onboard icebreakers for scientific research activities and logistics have been recognized as a reliable remote sensing platform from enhanced endurance and verified stability, and have flexibility for the attachment of multiple sensors. Although areal reference datasets, e.g., helicopter-borne high-resolution images, can be used to validate lower resolution sea ice information from the characteristics of enough coverage and fine spatial resolution, continuous drift of sea ice causes distorted locations of image acquisition along the drift; thus, becomes an obstacle for precise image mosaicking and matching with the sea ice information extracted from lower-resolution remote sensing imagery. This study presents methods for the cost-effective acquisition of helicopterborne high-resolution images over drifting Arctic sea ice using a simple configuration of imaging sensor and GPS logger, and for the compensation of the effect from sea ice drift from each imaging location using the drift trajectory of sea ice. After mosaicking the sea ice drift compensated high-resolution helicopter-borne images with structure-from-motion technique, the applicability of the mosaicked image was assessed by comparing with lower resolution satellite synthetic aperture radar image. The results suggest that the proposed methods can be applicable to the high-resolution images from other low altitude remote sensing platforms, e.g., UAVs, and can be used for precise comparison with various sea ice products from satellite remote sensing.

In recent decades, the glaciers on the Antarctic Peninsula have been rapidly retreating. Using satellite images taken during the austral summer from 1989 to 2016, we estimated the glacier pattern on King George Island in the Antarctic Peninsula, Antarctica, and found that glacier boundaries have gradually retreated. We have recorded the kelp gull nest sites in this glacier-retreat region during four breeding seasons (from 2012–2013 to 2015–2016). Satellite images and newly established kelp gull nests suggest that glacier retreat could lead to an enlarged breeding habitat for kelp gulls.

Simple Summary Remotely piloted aircraft systems (RPAS) have been successfully applied in wildlife monitoring with imaging sensors to improve or to supplement conventional field observations. To effectively utilize this technique, we reviewed previous studies related to wildlife detection with RPAS. First, this study provides an overview of the applications of RPAS for wild animal studies from the perspective of individual detection and population surveys as well as behavioral studies. In terms of the RPAS payload, applying thermal-imaging sensors was determined to be advantageous in detecting homeothermic animals due to the thermal contrast with background habitat using case studies detecting southern elephant seal (Mirounga leonina) using RGB and thermal imaging sensors in King George Island, maritime Antarctica. Abstract In wildlife biology, it is important to conduct efficient observations and quantitative monitoring of wild animals. Conventional wildlife monitoring mainly relies on direct field observations by the naked eyes or through binoculars, on-site image acquisition at fixed spots, and sampling or capturing under severe areal constraints. Recently, remotely piloted aircraft systems (RPAS), also called drones or unmanned aerial vehicles (UAV), were successfully applied to detect wildlife with imaging sensors, such as RGB and thermal-imaging sensors, with superior detection capabilities to those of human observation. Here, we review studies with RPAS which has been increasingly used in wildlife detection and explain how an RPAS-based high-resolution RGB image can be applied to wild animal studies from the perspective of individual detection and population surveys as well as behavioral studies. The applicability of thermal-imaging sensors was also assessed with further information extractable from image analyses. In addition, RPAS-based case studies of acquisition of high-resolution RGB images for the purpose of detecting southern elephant seals (Mirounga leonina) and shape property extraction using thermal-imaging sensor in King George Island, maritime Antarctica is presented as applications in an extreme environment. The case studies suggest that currently available cost-effective small-sized RPAS, which are capable of flexible operation and mounting miniaturized imaging sensors, and are easily maneuverable even from an inflatable boat, can be an effective and supportive technique for both the visual interpretation and quantitative analysis of wild animals in low-accessible extreme or maritime environments.

The outer Ross Sea continental shelf has experienced large variations in ice sheet extent over the Pleistocene that are theorized to be largely driven by changes in the westward-flowing Antarctic Slope Current (ASC) at the continental shelf break. This current regulates southward incursions of warm modified Circumpolar Water, and it is thought to have triggered past marine ice sheet retreat. Additionally, expansions of grounded ice sheets on the continental shelf have fundamentally altered the Ross Sea water mass formation processes, influencing surface water salinity, sea ice cover, nutrient utilization, deep-water ventilation, and primary productivity. Here, we report the geochemical, physical properties, grain size, bulk δ15N, and diatom records during the late Pleistocene from two sediment cores from the Iselin Bank on the outermost continental shelf in the Ross Sea. These core sites were not overridden by grounded ice sheets during the late Pleistocene glacial-interglacial cycles, allowing for a continuous archive of glacimarine environments that were influenced by the ASC. Interglacial periods are typically characterized by high surface water productivity and nutrient utilization, with Chaetoceros resting spores indicating nutrient limitation under open ocean conditions, and glacial periods are typically characterized by low surface water productivity and nutrient utilization, with sea ice diatoms and planktonic foraminifers indicating light limitation under extensive sea ice/ice margin proximal conditions. A grain size analysis indicates coarse-skewed distributions and winnowing in the Iselin Bank region during cold periods. The winnowing may be related to enhanced ASC flow instead of density driven shelf water outflow.

Backscattering coefficients of Sentinel-1 synthetic aperture radar (SAR) data of drifting multi-year sea ice in the western Beaufort Sea during the transition period between the end of melting and onset of freeze-up are analyzed, in terms of the incidence angle dependence and temporal variation. The mobile sea ice surface is tracked down in a 1 km by 1 km region centered at a GPS tracker, which was installed during a field campaign in August 2019. A total of 24 Sentinel-1 images spanning 17 days are used and the incidence angle dependence in HH- and HV-polarization are −0.24 dB/deg and −0.10 dB/deg, respectively. Hummocks and recently frozen melt ponds seem to cause the mixture behavior of surface and volume scattering. The normalized backscattering coefficients in HH polarization gradually increased in time at a rate of 0.15 dB/day, whereas the HV-polarization was relatively flat. The air temperature from the ERA5 hourly reanalysis data has a strong negative relation with the increasing trend of the normalized backscattering coefficients in HH-polarization. The result of this study is expected to complement other previous studies which focused on winter or summer seasons in other regions of the Arctic Ocean.

Completely decomposed granite (CDG) with different structures shows different patterns in deformation and failure as brittle fracture or as plastic creep in triaxial test. It is necessary to monitor and to compare the fabric changes due to stress in real time during test. By means of the computerized tomography (CT) technique for monitoring deformation and failure of soils in real time without suspending the mechanical test and disturbing samples, a newly designed triaxial test machine was used to test CDG from Hong Kong in a procedure of saturation, consolidation and undrained condition. It was found that CT data (images and values) depicts the failure patterns as brittle fracture or as plastic creep at 3-D in real time. The results were concordant with stress–strain curves and observation of the appearance of samples before and after tests.

Ocean Color products have been used to understand marine ecosystem. In high latitude region, ice melting optically influences the ocean color products. In this study, we assessed optical properties in fjord around Svalbard Arctic sea, and estimated distribution of chlorophyll-a and suspended sediment by using high resolution satellite data, Landsat-8 Operational Land Imager (OLI). To estimate chlorophyll-a and suspended sediment concentrations, various regression models were tested with different band ratio. The regression models were not shown high correlation because of temporal difference between satellite data and in-situ data. However, model-derived distribution of ocean color products from OLI showed a possibility that fjord and coastal areas around Arctic Sea can be monitored with high resolution satellite data. To understand climate change pattern around Arctic Sea, we need to understand ice meting influences on marine ecosystem change. Results of this study will be used to high resolution monitoring of ice melting and its influences on the marine ecosystem change at high latitude. KOPRI (Korea Polar Research Institute) has been operated the Dasan station on Svalbard since 2002, and study was conducted using Arctic station.

The freeze–thaw action of water inside rocks’ pores, cracks, and joints plays a dominant role in physical rock weathering where the temperature fluctuates across 0 °C. To understand this process in cold regions, artificial weathering was simulated in the laboratory. Diorite, basalt, and tuff were used as specimen, and were maintained in saturated conditions to accelerate the effect of freeze–thaw weathering. X-ray computed tomography (CT) images and scanning electron microscope (SEM) photographs were obtained to investigate changes in the inner microstructure along with repeated freeze–thaw cycles. In addition, physical properties were measured during the cycles. Particle detachment, crack initiation, and propagation and porosity increase due to volumetric expansion of water inside rocks were detected using X-ray CT and SEM. The decrease in P-wave and S-wave velocities, and in weight loss were also observed. Tuff specimens, which have low tensile strength, high porosity, and loose structure, were deteriorated rapidly, while diorite specimens on the other hand, which have high tensile strength, low porosity, and compact structure, showed relatively slight changes. The frost susceptibility of basalt specimens was found to be intermediate between tuff and diorite. The developed process for cycling and freezing set up can be useful to test the various stones in terms of frost susceptibility.

Satellite remote sensing can be used effectively with a wide coverage and repeatability in large-scale Arctic sea-ice analysis. To produce reliable sea-ice information, satellite remote-sensing methods should be established and validated using accurate field data, but obtaining field data on Arctic sea-ice is very difficult due to limited accessibility. In this situation, digital surface models derived from aerial images can be a good alternative to topographical field data. However, to achieve this, we should discuss an additional issue, i.e., that low-textured surfaces on sea-ice can reduce the matching accuracy of aerial images. The matching performance is dependent on the matching cost and search window size used. Therefore, in order to generate high-quality sea-ice surface models, we first need to examine the influence of matching costs and search window sizes on the matching performance on low-textured sea-ice surfaces. For this reason, in this study, we evaluate the performance of matching costs in relation to changes of the search window size, using acquired aerial images of Arctic sea-ice. The evaluation concerns three factors. The first is the robustness of matching to low-textured surfaces. Matching costs for generating sea-ice surface models should have a high discriminatory power on low-textured surfaces, even with small search windows. To evaluate this, we analyze the accuracy, uncertainty, and optimal window size in terms of template matching. The second is the robustness of positioning to low-textured surfaces. One of the purposes of image matching is to determine the positions of object points that constitute digital surface models. From this point of view, we analyze the accuracy and uncertainty in terms of positioning object points. The last is the processing speed. Since the computation complexity is also an important performance indicator, we analyze the elapsed time for each of the processing steps. The evaluation results showed that the image domain costs were more effective for low-textured surfaces than the frequency domain costs. In terms of matching robustness, the image domain costs showed a better performance, even with smaller search windows. In terms of positioning robustness, the image domain costs also performed better because of the lower uncertainty. Lastly, in terms of processing speed, the PC (phase correlation) of the frequency domain showed the best performance, but the image domain costs, except MI (mutual information), were not far behind. From the evaluation results, we concluded that, among the compared matching costs, ZNCC (zero-mean normalized cross-correlation) is the most effective for sea-ice surface model generation. In addition, we found that it is necessary to adjust search window sizes properly, according to the number of textures required for reliable image matching on sea-ice surfaces, and that various uncertainties due to low-textured surfaces should be considered to determine the positions of object points.

The paradigm of Geographic Information Systems is shifting toward the development of National Spatial Data Infrastructure (NSDI) because of the national value of spatial data. The Korean Government started the National Geographic Information System project in 1995 and began to develop NSDI in 2008. Because of the importance of underground spatial data, as well as the high cost and difficulty of obtaining such data, it is important to standardize underground geospatial data. It is expected that underground spatial data will be included in the NSDI, given the likely future expansion of NSDI data sets. Such underground information can be divided into data related to construction and data related to resource development. Standardization has been separately attempted in both of these fields, but insufficient studies exist on standardization across the fields. In the present study, we propose a scheme for a national standard underground spatial information database. As an example of the application of a standard database, we developed several application systems, including an information system that operates in the Web environment and a system that operates in the mobile environment. Because infrastructure for mobile communications in South Korea is rapidly expanding, there exist high expectations regarding the usability of mobile systems. Therefore, we developed some creative functions to assist with fieldwork in a mobile system, including mobile phones implementing augmented reality. The proposed system is expected to assist with the integrated management of underground geospatial information in the fields of construction and resource development at the national level.

The evolution of large-scale landslides should be studied because, over long periods of time, primary remediation measures may suffer reduced efficiency or have to be adjusted many times. The 102 Landslide in southeast Tibet, which originally formed in 1991 with a volume of 5.1 million m3 and still exhibits post-failure activity, provides a distinctive case study. The landslide evolved from earthquake destruction and unloading, rainfall-triggered sliding, and debris flow to sands sliding slopes. The NE ringed scarp receded by 38.96 m during a five-year period (2003–2008). The total recession was 160 m with a total area of 2500 m2 during a 17-year period (1991–2008). Although several types of remediation measures were applied and were temporarily effective, the normal function of the Sichuan–Tibet Highway was affected by landslide reactivation from time to time. Actual effects of the engineering measures such as retaining walls, prestressed anchor cables, and drainage ditches confirm that hasty governance of this type of large-scale landslide is generally unfeasible over long time periods. Finally, an approach involving a tunnel running backward from the front face has been adopted as a permanent solution to large-scale moraine slope failures: This engineering practice has been in progress since April 2012. This paper describes the evolution of the 102 Landslide, the engineering interventions to mitigate the effects of the landslide on the Sichuan–Tibet Highway, and the choice of tunneling as a final mitigation measure. The present study concludes that approaches that allow escape from developing geo-hazards should always be the initial choice.

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multitemporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of 3× 3, 5×5, 7×7, and 9×9 pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of 7×7 produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of 9×9 produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

This paper presents a new index, the Total Mine Hazards Index (TMHI), which has been developed to support reclamation planning in abandoned mining areas in Korea. The TMHI quantifies the extent of the hazards caused by mining in terms of five problem areas: (a) mine subsidence, (b) deforestation, (c) mine tailings, (d) waste rock dumps, and (e) mine water. These five mining hazards are statistically analyzed and the results are combined with Geographic Information Systems (GIS) modeling to prioritize the abandoned mines that pose the greatest hazard risk. A GIS database of mine-related information, including topographic data, land cover data, and road maps, is analyzed and used to evaluate the likely extent of mine-related pollution. As a case study, the TMHI is applied to Gangwon-do province in Korea, and the results show that the TMHI can be used to identify those mines most in need of attention and support mine reclamation planning by comprehensively quantifying the nature and extent of any hazards associated with abandoned mines.

Quantitative analysis of CaO in limestone mining is mandatory, not only for ore exploration, but also for grade control. A partial least squares regression (PLSR) CaO estimation technique was developed for limestone mining. The proposed near-infrared spectroscopy (NIR)-based method uses reflectance spectra of the rock sample surface in the visible to short-wave infrared wavelength regions (350–2500 nm (4000–28,571 cm−1)) without the need to crush and pulverize the rock samples. The root mean square (RMS) error of CaO estimation using limestone ore fragment was 1.2%. The CaO content estimated by the PLSR method was used to predict average CaO content of composite samples with a sample size of 15, which resulted in an RMS error of 0.3%. The prediction accuracy with moisture on sample surfaces was also examined to find out if the NIR-based method showed a similar RMS error. Results suggest that the NIR technique can be used as a rapid assaying method in limestone workings with or without the presence of groundwater.