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1,337 results for “antarctica”
Figure 4. Eudorylaimus sabulophilus A in Five new records of nematodes from East Antarctica
Figure 4. Eudorylaimus sabulophilus A - Female Anterior region; B - Female Posterior region.
Figure 2. Helicotylenchus exallus A in Five new records of nematodes from East Antarctica
Figure 2. Helicotylenchus exallus A - Female Anterior region; B - Posterior region.
Chloroform fluxes measured at the tundra on King George Island, Antarctica
<p>In this study, the first <em>in situ</em> static-chamber measurements were conducted at coastal Antarctica tundra for CHCl<sub>3</sub> fluxes, which showed that CHCl<sub>3</sub> was naturally emitted from the Antarctic tundra. This dataset includes the chloroform fluxes measured from the tundra at the Fildes Peninsula and Ardley Island based upon static-chamber measurements and lab-based incubations under different manipulated conditions. Chloroform concentrations were analyzed by gas chromatography coupled with a mass spectrometry (GC/MS; Agilent 6890N/5973, Agilent Technologies, Santa Clara, CA). </p>
Large-Scale Atmospheric Drivers of Snowfall over Thwaites Glacier, Antarctica
<p>Monthly RACMO2 snowfall rates (1979-2015, in mm w.e. per month), as described in Lenaerts et al., 2018 (https://www.cambridge.org/core/journals/annals-of-glaciology/article/climate-and-surface-mass-balance-of-coastal-west-antarctica-resolved-by-regional-climate-modelling/E3DD6D0DA914C6031F96A548AF53603A), and used in this paper. </p>
Life beneath the ice: jellyfish and ctenophores from the Ross Sea, Antarctica, with an image-based training set for machine learning
<p>This Zenodo dataset contain the Common Objects in Context (COCO) files linked to the following publication:</p> <p>Verhaegen, G, Cimoli, E, & Lindsay, D (2021). Life beneath the ice: jellyfish and ctenophores from the Ross Sea, Antarctica, with an image-based training set for machine learning. Biodiversity Data Journal.</p> <p>Each COCO zip folder contains an "annotations" folder including a json file and an "images" folder containing the annotated images.</p> <p>Details on each COCO zip folders:</p> <ul> <li><strong>Beroe_sp_A_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Beroe </em>sp. A<em> </em>for the following 114 images:</p> <p>MCMEC2018_20181116_NIKON_Beroe_sp_A_c_1 to MCMEC2018_20181116_NIKON_Beroe_sp_A_c_16, MCMEC2018_20181125_NIKON_Beroe_sp_A_d_1 to MCMEC2018_20181125_NIKON_Beroe_sp_A_d_57, MCMEC2018_20181127_NIKON_Beroe_sp_A_e_1 to MCMEC2018_20181127_NIKON_Beroe_sp_A_e_2, MCMEC2019_20191116_SONY_Beroe_sp_A_a_1 to MCMEC2019_20191116_SONY_Beroe_sp_A_a_28, and MCMEC2019_20191127_SONY_Beroe_sp_A_f_1 to MCMEC2019_20191127_SONY_Beroe_sp_A_f_12</p> <ul> <li><strong>Beroe_sp_B_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Beroe </em>sp. B<em> </em>for the following 2 images:</p> <p>MCMEC2019_20191115_SONY_Beroe_sp_B_a_1 and MCMEC2019_20191115_SONY_Beroe_sp_B_a_2</p> <ul> <li><strong>Callianira_cristata_images-coco 1.0.zip </strong></li> </ul> <p>COCO annotations of <em>Callianira cristata</em><em> </em>for the following 21 images:</p> <p>MCMEC2019_20191120_SONY_Callianira_cristata_b_1 to MCMEC2019_20191120_SONY_Callianira_cristata_b_21</p> <ul> <li><strong>Diplulmaris_antarctica_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Diplulmaris antarctica</em> for the following 83 images:</p> <p>MCMEC2019_20191116_SONY_Diplulmaris_antarctica_a_1 to MCMEC2019_20191116_SONY_Diplulmaris_antarctica_a_9, and MCMEC2019_20191201_SONY_Diplulmaris_antarctica_c_1 to MCMEC2019_20191201_SONY_Diplulmaris_antarctica_c_74</p> <ul> <li><strong>Koellikerina_maasi_images-coco 1.0.zip </strong></li> </ul> <p>COCO annotations of <em>Koellikerina maasi</em><em> </em>for the following 49 images:</p> <p>MCMEC2018_20181127_NIKON_Koellikerina_maasi_b_1 to MCMEC2018_20181127_NIKON_Koellikerina_maasi_b_4, MCMEC2018_20181129_NIKON_Koellikerina_maasi_c_1 to MCMEC2018_20181129_NIKON_Koellikerina_maasi_c_29, and MCMEC2019_20191126_SONY_Koellikerina_maasi_a_1 to MCMEC2019_20191126_SONY_Koellikerina_maasi_a_16</p> <ul> <li><strong>Leptomedusa_sp_A-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of Leptomedusa sp. A<em> </em>for Figure 5 (see paper).</p> <ul> <li><strong>Leuckartiara_brownei_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Leuckartiara brownei</em> for the following 48 images: </p> <p>MCMEC2018_20181129_NIKON_Leuckartiara_brownei_b_1 to MCMEC2018_20181129_NIKON_Leuckartiara_brownei_b_27, MCMEC2018_20181129_NIKON_Leuckartiara_brownei_c_1 to MCMEC2018_20181129_NIKON_Leuckartiara_brownei_c_6, and MCMEC2019_20191116_SONY_Leuckartiara_brownei_a_1 to MCMEC2019_20191116_SONY_Leuckartiara_brownei_a_15</p> <ul> <li><strong>MCMEC2019_20191115_SONY_Mertensiidae_sp_A_a_3-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of Mertensiidae sp. A for the following video (total of 1847 frames): MCMEC2019_20191115_SONY_Mertensiidae_sp_A_a_3 (<a href="https://youtu.be/0W2HHLW71Pw">https://youtu.be/0W2HHLW71Pw</a>)</p> <ul> <li><strong>MCMEC2019_20191116_SONY_Leuckartiara_brownei_a_3-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Leuckartiara brownei</em> for the following video (total of 1367 frames): MCMEC2019_20191116_SONY_Leuckartiara_brownei_a_3 (<a href="https://youtu.be/dEIbVYlF_TQ">https://youtu.be/dEIbVYlF_TQ</a>)</p> <ul> <li><strong>MCMEC2019_20191122_SONY_Callianira_cristata_a_1-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Callianira cristata</em> for the following video (total of 2423 frames): MCMEC2019_20191122_SONY_Callianira_cristata_a_1 (<a href="https://youtu.be/30g9CvYh5JE">https://youtu.be/30g9CvYh5JE</a>)</p> <ul> <li><strong>MCMEC2019_20191122_SONY_Leptomedusa_sp_B_a_1-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of Leptomedusa sp. B for the following video (total of 1164 frames): MCMEC2019_20191122_SONY_Leptomedusa_sp_B_a_1 (<a href="https://youtu.be/hrufuPQ7F8U">https://youtu.be/hrufuPQ7F8U</a>)</p> <ul> <li><strong>MCMEC2019_20191126_SONY_Koellikerina_maasi_a_1-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Koellikerina maasi</em> for the following video (total of 1643 frames): MCMEC2019_20191126_SONY_Koellikerina_maasi_a_1 (<a href="https://youtu.be/QiBPf_HYrQ8">https://youtu.be/QiBPf_HYrQ8</a>)</p> <ul> <li><strong>MCMEC2019_20191129_SONY_Mertensiidae_sp_A_b_1-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of Mertensiidae<em> </em>sp. A for the following video (total of 239 frames): MCMEC2019_20191129_SONY_Mertensiidae_sp_A_b_1 (<a href="https://youtu.be/pvXYlQGZIVg">https://youtu.be/pvXYlQGZIVg</a>)</p> <ul> <li><strong>MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_2-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Pyrostephos vanhoeffeni</em> for the following video (total of 444 frames): MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_2 (<a href="https://youtu.be/2rrQCybEg0Q">https://youtu.be/2rrQCybEg0Q</a>)</p> <ul> <li><strong>MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_3-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Pyrostephos vanhoeffeni</em> for the following video (total of 683 frames): MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_3 (<a href="https://youtu.be/G9tev_gdUvQ">https://youtu.be/G9tev_gdUvQ</a>)</p> <ul> <li><strong>MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_4-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Pyrostephos vanhoeffeni</em> for the following video (total of 1127 frames): MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_4<strong> </strong>(<a href="https://youtu.be/NfJjKBRh5Hs">https://youtu.be/NfJjKBRh5Hs</a>)</p> <ul> <li><strong>MCMEC2019_20191130_SONY_Beroe_sp_A_b_1-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Beroe </em>sp. A for the following video (total of 2171 frames): MCMEC2019_20191130_SONY_Beroe_sp_A_b_1<strong> </strong>(<a href="https://youtu.be/kGBUQ7ZtH9U">https://youtu.be/kGBUQ7ZtH9U</a>)</p> <ul> <li><strong>MCMEC2019_20191130_SONY_Beroe_sp_A_b_2-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Beroe </em>sp. A for the following video (total of 359 frames): MCMEC2019_20191130_SONY_Beroe_sp_A_b_2 (<a href="https://youtu.be/Vbl_KEmPNmU">https://youtu.be/Vbl_KEmPNmU</a>)</p> <ul> <li><strong>Mertensiidae_sp_A_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of Mertensiidae sp. A for the following 49 images:</p> <p>MCMEC2018_20181127_NIKON_Mertensiidae_sp_A_c_1 to MCMEC2018_20181127_NIKON_Mertensiidae_sp_A_c_2, MCMEC2018_20181127_NIKON_Mertensiidae_sp_A_f_1 to MCMEC2018_20181127_NIKON_Mertensiidae_sp_A_f_8, MCMEC2018_20181129_NIKON_Mertensiidae_sp_A_d_1 to MCMEC2018_20181129_NIKON_Mertensiidae_sp_A_d_13, MCMEC2018_20181201_ROV_Mertensiidae_sp_A_e_1 to MCMEC2018_20181201_ROV_Mertensiidae_sp_A_e_15, and MCMEC2019_20191115_SONY_Mertensiidae_sp_A_a_1 to MCMEC2019_20191115_SONY_Mertensiidae_sp_A_a_11</p> <ul> <li><strong>Pyrostephos_vanhoeffeni_images-coco 1.0.zip</strong></li> </ul> <p>COCO annotations of <em>Pyrostephos vanhoeffeni</em> for the following 14 images: MCMEC2019_20191125_SONY_Pyrostephos_vanhoeffeni_a_1 to MCMEC2019_20191125_SONY_Pyrostephos_vanhoeffeni_a_8, MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_1 to MCMEC2019_20191129_SONY_Pyrostephos_vanhoeffeni_b_6</p> <ul> <li><strong>Solmundella_bitentaculata_images-coco 1.0.zip </strong></li> </ul> <p>COCO annotations of <em>Solmundella bitentaculata</em> for the following 13 images: MCMEC2018_20181127_NIKON_Solmundella_bitentaculata_a_1 to MCMEC2018_20181127_NIKON_Solmundella_bitentaculata_a_13</p>
FIG. 1 in Reappraisal of an ankylosaurian dinosaur from the Upper Cretaceous of James Ross Island (Antarctica)
FIG. 1. — Location map of the holotype of Antarctopelta oliveroi n. gen., n. sp. (arrow).
Figure 6 in Osteology of Cryolophosaurus ellioti (Dinosauria: Theropoda) from the Early Jurassic of Antarctica and implications for early theropod evolution
Figure 6. Skull of Cryolophosaurus ellioti in dorsal aspect (photo courtesy of J. Weinstein).
Figure 18 in Osteology of Cryolophosaurus ellioti (Dinosauria: Theropoda) from the Early Jurassic of Antarctica and implications for early theropod evolution
Figure 18. Proximal left tibia of Cryolophosaurus ellioti in proximal (A) and lateral (B) aspects.
Snow hyperspectral measurements in Terra Nova Bay (Antarctica) and supplementary materials
<p>SISpec is a database containing spectroradiometric, snow and ancillary (environmental and meteorological) data acquired in polar environments. The project is the result of the co-operation of different expertise, and its main objective is to contribute to the knowledge of the interaction between microphysics characteristic of the snow cover and its reflection properties of the solar incident radiation and to study glacial environment and particularly to monitor the snow/ice covers by multispectral remote sensing data. Field surveys were performed in Antarctica, in the region where the Italian research station of Terra Nova Bay is located, the climatic characteristics and the low human impact allow to study snow/ice surfaces without impurities and with different characteristics with respect to those of the Arctic and the Alpine regions, where seasonal melting of the snow cover occur.</p>
Supraglacial lakes and channels in West Antarctica and Antarctic Peninsula during January 2017 - Maximum Extent
<p>The maximum extent of supraglacial lakes and channels in West Antarctica and the Antarctic Peninsula in January 2017 was produced by a Dual-NDWI (Normalised Difference Water Index) approach with thresholds. >2000 individual scenes were captured by Sentinel-2 (S2) and Landsat-8 (L8) satellite sensors during the entire month of January 2017. To obtain maximum coverage on the cloudy Antarctic Peninsula, the time period is extended to February 10, 2017 over this region.</p> <p>This dataset consists of the maximum extent of supraglacial hydrological activity during January 2017 and detailed 10,478 supraglacial features (10,223 lakes and 255 channels), with cumulative area 119.4 square km in total on the West Antarctic ice sheet and Antarctic Peninsula. In addition to the final product, the supraglacial hydrological features from both sensors (23,389 polygons for S2 and 17,571 polygons for L8) overlapping the final map are included in supplementary datasets. The supraglacial lake and channel polygons are available as digital GIS, Geographic Information System, shapefiles (.shp) and GeoJSON files as well as Google Earth format (.kmz). The code used to produce the lake and channel dataset for each sensor (S2 and L8) is implemented using Python, and can be accessed on Zenodo (<a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.4906097&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=JPsWDkSk9wqxEcoxMGWzbNgleTFB1NoIFn7t0WlDg3Q%3D&amp;reserved=0">https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.4906097&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=JPsWDkSk9wqxEcoxMGWzbNgleTFB1NoIFn7t0WlDg3Q%3D&amp;reserved=0</a>) . Landsat-8 and Sentinel-2 imagery are freely available at (<a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fearthexplorer.usgs.gov%2F&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=RidpbAMFz28isbZM6vNZWPMTdl3bl5OxO3SVWvBu6MQ%3D&amp;reserved=0">https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fearthexplorer.usgs.gov%2F&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=RidpbAMFz28isbZM6vNZWPMTdl3bl5OxO3SVWvBu6MQ%3D&amp;reserved=0</a>) and (<a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscihub.copernicus.eu%2F&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=lZINlehD3i%2BN%2BPSVZgSJnZa%2FruFq2vGHoEnkQGMmq%2Fg%3D&amp;reserved=0">https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscihub.copernicus.eu%2F&amp;data=04%7C01%7Ccorrd%40live.lancs.ac.uk%7Ce16045ed14e34f2cb4f108d92b70565e%7C9c9bcd11977a4e9ca9a0bc734090164a%7C0%7C0%7C637588586902880130%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000&amp;sdata=lZINlehD3i%2BN%2BPSVZgSJnZa%2FruFq2vGHoEnkQGMmq%2Fg%3D&amp;reserved=0</a>), respectively.</p> <p>The products provide a scientific benchmark to monitor the development of these features in a warming climate, and thus enhancing our capability to predict the calving and collapse of any ice shelves in the future. The results provide a baseline for future monitoring of supraglacial hydrology and can be particularly useful to train supervised machine learning algorithms. The lake and channel dataset will be valuable as training data for pixel-based or object-based approaches to map large-scale features automatically using machine learning. This dataset can also provide an a-priori lake distribution for studies incorporating synthetic-aperture radar, SAR and other sensors and platforms.</p> <p> </p>
A polar insect's tale: observations on the life cycle of Parochlus steinenii, the only winged midge native to Antarctica
<p><span>Antarctica and the sub-Antarctic islands are considered natural laboratories to study and understand the influence of environmental variable and patterns of variation therein on the biota, including the influences of climate change. The Antarctic terrestrial fauna consists only of small invertebrates, with just two native species of holometabolous insects, Parochlus steinenii and Belgica antarctica, and two established non-native species, Eretmoptera murphyi and Trichocera maculipennis. Studies of the life history, phenology and stress tolerances of insects are critical to better understand adaptations to natural environmental stress and the ecological consequences of recent and ongoing climate change. In this context, we characterized the habitat preferences, life cycle and phenology of P. steinenii, the winged Antarctic midge, in a lake on King George Island, South Shetland Islands, maritime Antarctic. Based on the data obtained, we hypothesize that P. steinenii has a multi-year life cycle that may span as much as four years. The species is very restricted in terms of its preferred microhabitat distribution, being highly abundant only at shallow depths close to the edge of the lakes in which it is found. A combination of further field and laboratory studies are now required to assess how the length of P. steinenii life cycle is influenced by the scale of temperature variation typically experienced in its natural habitat, and as predicted under different climate change scenarios, as well investigating the ability and timing of larval movement to take advantage of the conditions of specific microhabitats at different times of year.</span></p>
Data from: Ankylosaurian body armor function and evolution with insights from osteohistology and morphometrics of new specimens from the Late Cretaceous of Antarctica
<p>The body armor of ankylosaurians is a unique morphological feature among dinosaurs. Despite being studied for decades, paleohistological analyses have only started to uncover the details of its function. Yet, there has been an overall bias toward sampling ankylosaurian remains from the Northern Hemisphere and limited quantitative studies on the morphological and functional evolution. Here, we describe new ankylosaurian materials recovered from the Late Cretaceous of Antarctica that, in combination with data compiled from the literature, reveal new insights into the evolution of the ankylosaurian body armor. Based on histological microstructure and phylogenetic results, the new Antarctic material can be assigned to Nodosauridae. This group shares the absence/poor development of the basal cortex and highly ordered sets of orthogonal structural fibers in the superficial cortex. Our morphospace analyses indicate that large morphological diversity is observed among both nodosaurids and ankylosaurids, but they became more functionally specialized in late-diverging nodosaurids. Besides acting as effective protection against predation, osteoderms also exhibit highly ordered structural fibers in nodosaurids, enabling a decrease in cortical bone thickness (as in titanosaurs), which could have been co-opted for secondary functions, such as calcium remobilization for physiological balance. The latter may have played a key role in nodosaurid colonization of high-latitude environments, such as Antarctica and the Arctic Circle.</p>
Phenomenological images (LL-CAM2) of Limnopolar Lake CALM site, Byers Peninsula, Livingston island, Antarctica (2022).
<p>Images acquired by a phenomenological automatic time-lapse camera (LL-CAM2) located in Limnopolar Lake permafrost and active layer monitoring site in the Limnopolar Lake basin in Byers Peninsular, Livingston island, Antarctica, in 2022.</p> <ul> <li>Location: Livingston Island, Antarctica</li> <li>Site: Limnopolar Lake sounders</li> <li>Instrument/Experiment: Phenomenological time-lapse automatic photographic camera</li> <li>Period: 2022</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Limnopolar Lake CALM site, in Limnopolar Lake basin (Byers Peninsula), Livingston island, Antarctica.</li> <li>Latitude: -62.6485556 </li> <li>Longitude:-61.1013611</li> <li>Elevation: 77 m</li> <li>Initial dataset date/time: January 25, 2022 14:00h GMT</li> <li>Final dataset date/time: February 7, 2023 16:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>File code: LIV_LL_CAM2_2022_v100</li> <li>Location code: LIV</li> <li>Site code: LL</li> <li>Instrument code: CAM2</li> <li>Folders: 14</li> <li>Files: 1132</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Phenomenological images (LL-CAM2) of Limnopolar Lake CALM site, Byers Peninsula, Livingston island, Antarctica (2024).
<p>Images acquired by a phenomenological automatic time-lapse camera (LL-CAM1B) located in Limnopolar Lake permafrost and active layer monitoring site in the Limnopolar Lake basin in Byers Peninsular, Livingston island, Antarctica, in 2022.</p> <ul> <li>File code: LIV_LL_CAM1B_2022_v100</li> <li>Location code: LIV</li> <li>Site code: LL</li> <li>Instrument code: CAM1B</li> <li>Period: 2022</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Limnopolar Lake CALM site, in Limnopolar Lake basin (Byers Peninsula), Livingston island, Antarctica.</li> <li>Location: </li> <li>Elevation:</li> <li>Initial dataset date/time: January 26, 2022 15:00h GMT</li> <li>Final dataset date/time: February 7, 2023 16:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>Folders: 14</li> <li>Files: 1133</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Phenomenological images (LL-CAM2) of Limnopolar Lake CALM site, Byers Peninsula, Livingston island, Antarctica (2020-21).
<p>Images acquired by a phenomenological automatic time-lapse camera (LL-CAM2) located in Limnopolar Lake permafrost and active layer monitoring site in the Limnopolar Lake basin in Byers Peninsular, Livingston island, Antarctica, in 2020 and 2021.</p> <ul> <li>Location: Livingston Island, Antarctica</li> <li>Site: Limnopolar Lake sounders</li> <li>Instrument/Experiment: Phenomenological time-lapse automatic photographic camera</li> <li>Period: 2020 and 2021</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Limnopolar Lake CALM site, in Limnopolar Lake basin (Byers Peninsula), Livingston island, Antarctica.</li> <li>Latitude: -62.6485556 </li> <li>Longitude:-61.1013611</li> <li>Elevation: 77 m</li> <li>Initial dataset date/time: January 1, 2020 14:00h GMT</li> <li>Final dataset date/time: January 16, 2022 16:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>File code: LIV_LL_CAM2_2020-21_v100</li> <li>Location code: LIV</li> <li>Site code: LL</li> <li>Instrument code: CAM2</li> <li>Folders: 25</li> <li>Files: 2260</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Phenomenological images (LL-CAM1B) of Limnopolar Lake CALM site, Byers Peninsula, Livingston island, Antarctica (2020-21).
<p>Images acquired by a phenomenological automatic time-lapse camera (LL-CAM1B) located in Limnopolar Lake permafrost and active layer monitoring site in the Limnopolar Lake basin in Byers Peninsular, Livingston island, Antarctica, in 2020 and 2021.</p> <ul> <li>File code: LIV_LL_CAM1B_2020-21_v100</li> <li>Location code: LIV</li> <li>Site code: LL</li> <li>Instrument code: CAM1B</li> <li>Period: 2020 and 2021</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Limnopolar Lake CALM site, in Limnopolar Lake basin (Byers Peninsula), Livingston island, Antarctica.</li> <li>Location: </li> <li>Elevation:</li> <li>Initial dataset date/time: January 16, 2020 15:00h GMT</li> <li>Final dataset date/time: January 25, 2022 16:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>Folders: 25</li> <li>Files: 2221</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Phenomenological images (CL-CAM1B) of Crater Lake CALM site, Deception island, Antarctica (2021).
<p>Images acquired by a phenomenological automatic time-lapse camera (CL-CAM1B) located in Crater Lake permafrost and active layer monitoring site in Crater Lake sounders in Deception island, Antarctica, in 2021.</p> <ul> <li>File code: DEC_CL_CAM1B_2021_v100</li> <li>Location code: DEC</li> <li>Site code: CL</li> <li>Instrument code: CAM1B</li> <li>Period: 2021</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Crater Lake CALM site, in Crater Lake sounders of Deception island, Antarctica.</li> <li>Location: </li> <li>Elevation:</li> <li>Initial dataset date/time: February 20, 2021 14:00h GMT</li> <li>Final dataset date/time: January 13, 2022 15:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>Folders: 12</li> <li>Files: 983</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Phenomenological images (CL-CAM2) of Crater Lake CALM site, Deception island, Antarctica (2021).
<p>Images acquired by a phenomenological automatic time-lapse camera (CL-CAM2) located in Crater Lake permafrost and active layer monitoring site in Crater Lake sounders in Deception island, Antarctica, in 2021.</p> <ul> <li>File code: DEC_CL_CAM2_2021_v100</li> <li>Location code: DEC</li> <li>Site code: CL</li> <li>Instrument code: CAM2</li> <li>Period: 2021</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Crater Lake CALM site, in Crater Lake sounders of Deception island, Antarctica.</li> <li>Location: </li> <li>Elevation:</li> <li>Initial dataset date/time: February 17, 2021 14:00h GMT</li> <li>Final dataset date/time: January 8, 2022 15:00h GMT</li> <li>Gaps: Yes, multiple due to power failure</li> <li>Notes: <ul> <li>Folders: 4</li> <li>Files: 93</li> <li>Other files: no</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
Antarctica Supraglacial Lakes Sentinel-1 SAR Images
<p>This dataset contains synthetic aperture radar (SAR) images of supraglacial lakes on the Antarctic ice shelves, acquired by the Sentinel-1 satellite. Supraglacial lakes are surface meltwater features that can affect the stability and dynamics of ice shelves by hydrofracturing, basal sliding, or surface thinning. Monitoring the spatio-temporal distribution and evolution of these lakes is important for understanding the impact of surface meltwater on ice shelf collapse and sea level rise.</p> <p>The dataset covers four key regions: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are characterized by extensive surface meltwater features. The images are single-polarized (VV or VH) and have a spatial resolution of 10 m. The images are processed using a modified U-Net algorithm for semantic segmentation of supraglacial lakes, based on deep learning and multiscale feature extraction. The algorithm is trained and validated on Landsat 8 and Sentinel-2 optical imagery, which provide high-resolution and multispectral information on supraglacial lake detection.</p> <p>The dataset provides binary masks of supraglacial lake extent for each Sentinel-1 image, as well as metadata on acquisition date, polarization, orbit number, and region name. The dataset also includes a decision-level fused product of Sentinel-1 and Sentinel-2 maximum lake extent for January 2020, which reveals a more complete supraglacial lake coverage than the individual single-sensor products. The dataset covers the austral summer seasons from 2015/2016 to 2019/2020 and contains over 1000 images.</p> <p>The dataset is intended to provide a first-ever continental record of supraglacial lake extent and volume in Antarctica using SAR imagery, which can complement optical datasets and overcome limitations of cloud cover and polar darkness. The dataset can be used for studying the intra-annual and interannual variability of supraglacial lake occurrence, depth, and drainage events, as well as their relationship with surface air temperature, ice shelf geometry, and fracture patterns. </p>
FIG. 6 in First report of diversity of Cyanobacteria of Broknes Peninsula of Larsemann Hills, East Antarctica
FIG. 6. — Cyanobacteria sample in water logged area.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.