USAP-DC

{"dp_type": "Dataset", "free_text": "Reflectance"}

[{"awards": "1847067 Levy, Joseph", "bounds_geometry": ["POLYGON((161 -77.5,161.3 -77.5,161.6 -77.5,161.9 -77.5,162.2 -77.5,162.5 -77.5,162.8 -77.5,163.1 -77.5,163.4 -77.5,163.7 -77.5,164 -77.5,164 -77.55,164 -77.6,164 -77.65,164 -77.7,164 -77.75,164 -77.8,164 -77.85,164 -77.9,164 -77.95,164 -78,163.7 -78,163.4 -78,163.1 -78,162.8 -78,162.5 -78,162.2 -78,161.9 -78,161.6 -78,161.3 -78,161 -78,161 -77.95,161 -77.9,161 -77.85,161 -77.8,161 -77.75,161 -77.7,161 -77.65,161 -77.6,161 -77.55,161 -77.5))"], "date_created": "Tue, 01 Sep 2026 00:00:00 GMT", "description": "This dataset contains reflectance measurements over the visible and near-infrared from Wright and Taylor Valleys, collected over austral summer 2024-2025. The spectra were collected in order to measure surface properties related to the water absorption spectral feature near 1.4 \u00b5m, but contain continuous spectral data from ~960 to 1700 nm at ~6 nm spectral resolution. Spectra were collected over wetted and dry soils in the MDV in order to measure soil moisture, with drone flights occurring in December 2024 and January 2025, from an altitude of ~5 m above ground level. ", "east": 164.0, "geometry": ["POINT(162.5 -77.75)"], "keywords": "Antarctica; Cryosphere; McMurdo Dry Valleys; Reflectance; Soil; Soil Moisture; Spectroscopy; UAV; Water Content", "locations": "Antarctica; McMurdo Dry Valleys; McMurdo Dry Valleys", "north": -77.5, "nsf_funding_programs": "Antarctic Earth Sciences", "persons": "Levy, Joseph; Kuentz, Lily; Talucci, Anna; Johnson, Jessica; Andrews, Ian; King, Isabela", "project_titles": "Linking Antarctic Cold Desert Groundwater to Thermokarst \u0026 Chemical Weathering in Partnership with the Geoscience UAV Academy", "projects": [{"proj_uid": "p0010286", "repository": "USAP-DC", "title": "Linking Antarctic Cold Desert Groundwater to Thermokarst \u0026 Chemical Weathering in Partnership with the Geoscience UAV Academy"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -78.0, "title": "Drone-borne, visible to near-IR reflectance measurements from the McMurdo Dry Valleys", "uid": "602087", "west": 161.0}, {"awards": "2136938 Tedesco, Marco", "bounds_geometry": ["POLYGON((-40 67.55,-39.611 67.55,-39.222 67.55,-38.833 67.55,-38.444 67.55,-38.055 67.55,-37.666 67.55,-37.277 67.55,-36.888 67.55,-36.499 67.55,-36.11 67.55,-36.11 67.28999999999999,-36.11 67.03,-36.11 66.77,-36.11 66.51,-36.11 66.25,-36.11 65.99,-36.11 65.73,-36.11 65.47,-36.11 65.21000000000001,-36.11 64.95,-36.499 64.95,-36.888 64.95,-37.277 64.95,-37.666 64.95,-38.055 64.95,-38.444 64.95,-38.833 64.95,-39.222 64.95,-39.611 64.95,-40 64.95,-40 65.21000000000001,-40 65.47,-40 65.73,-40 65.99,-40 66.25,-40 66.51,-40 66.77,-40 67.03,-40 67.28999999999999,-40 67.55))"], "date_created": "Mon, 07 Oct 2024 00:00:00 GMT", "description": "This dataset contains high-resolution satellite-derived snow/ice surface melt-related data on a common 100 m equal area grid (Albers equal area projection; EPSG 9822) over Helheim Glacier and surrounding areas in Greenland. The data is used as part of a machine learning framework that aims to fill data gaps in computed meltwater fraction on the 100 m grid using a range of methods, results of which will be published separately.\r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003eThe data include fraction of a grid cell covered by meltwater derived from Sentinel-1 synthetic aperture radar (SAR) backscatter, satellite-derived passive microwave (PMW) brightness temperatures, snowpack liquid water content within the first meter of snow and atmospheric and radiative variables from the Mod\u00e9le Atmosph\u00e9rique R\u00e8gional (MAR) regional climate model, spectral reflectance in four wavelength bands from the Moderate Resolution Imaging Spectroradiometer (MODIS), a static digital elevation model (DEM), and an ice sheet mask. \r\n\u003cbr/\u003e\u003cbr/\u003eA similar dataset has also been produced for Larsen C ice shelf and is also available through the US Antarctic Program Data Center. \r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003e\r\n\u003cbr/\u003e\u003cbr/\u003e", "east": -36.11, "geometry": ["POINT(-38.055 66.25)"], "keywords": "Antarctica; Climate Modeling; Cryosphere; Downscaling; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Greenland; Ice Sheet; Machine Learning; MAR; Remote Sensing; Sea Level Rise; Snow/ice; Snow/Ice; Surface Melt", "locations": "Greenland; Antarctica; Greenland", "north": 67.55, "nsf_funding_programs": "Polar Cyberinfrastructure", "persons": "Alexander, Patrick; Antwerpen, Raphael; Cervone, Guido; Fettweis, Xavier; L\u00fctjens, Bj\u00f6rn; Tedesco, Marco", "project_titles": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning", "projects": [{"proj_uid": "p0010277", "repository": "USAP-DC", "title": "Collaborative Research: EAGER: Generation of high resolution surface melting maps over Antarctica using regional climate models, remote sensing and machine learning"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": 64.95, "title": "Surface melt-related multi-source remote-sensing and climate model data over Helheim Glacier, Greenland for segmentation and machine learning applications", "uid": "601841", "west": -40.0}, {"awards": "2044924 Barrett, John", "bounds_geometry": ["POLYGON((161.70776367188 -77.519802097166,161.899475097661 -77.519802097166,162.091186523442 -77.519802097166,162.282897949223 -77.519802097166,162.474609375004 -77.519802097166,162.666320800785 -77.519802097166,162.858032226566 -77.519802097166,163.049743652347 -77.519802097166,163.241455078128 -77.519802097166,163.433166503909 -77.519802097166,163.62487792969 -77.519802097166,163.62487792969 -77.54867059480199,163.62487792969 -77.57753909243799,163.62487792969 -77.606407590074,163.62487792969 -77.63527608771,163.62487792969 -77.664144585346,163.62487792969 -77.69301308298199,163.62487792969 -77.72188158061799,163.62487792969 -77.750750078254,163.62487792969 -77.77961857589,163.62487792969 -77.808487073526,163.433166503909 -77.808487073526,163.241455078128 -77.808487073526,163.049743652347 -77.808487073526,162.858032226566 -77.808487073526,162.666320800785 -77.808487073526,162.474609375004 -77.808487073526,162.282897949223 -77.808487073526,162.091186523442 -77.808487073526,161.899475097661 -77.808487073526,161.70776367188 -77.808487073526,161.70776367188 -77.77961857589,161.70776367188 -77.750750078254,161.70776367188 -77.72188158061799,161.70776367188 -77.69301308298199,161.70776367188 -77.664144585346,161.70776367188 -77.63527608771,161.70776367188 -77.606407590074,161.70776367188 -77.57753909243799,161.70776367188 -77.54867059480199,161.70776367188 -77.519802097166))"], "date_created": "Wed, 03 Apr 2024 00:00:00 GMT", "description": "Microbial communities are the primary drivers of carbon cycling in the McMurdo Dry Valleys of Antarctica. Dense microbial mats, consisting mainly of photosynthetic cyanobacteria, occupy aquatic areas associated with streams and lakes. Other microbial communities also occur at lower densities as patchy surface biological soil crusts (biocrusts) across the terrestrial landscape. Multispectral satellite data have been used to model microbial mat abundance in high-density areas like stream and lake margins, but no previous studies had investigated the lower detection limits of biocrusts. Here, we describe remote sensing and field-based survey and sampling approaches to study the detectability and distribution of biocrusts in the McMurdo Dry Valleys. Using a combination of multi- and hyperspectral tools and spectral linear unmixing, we modeled the abundances of biocrust in eastern Taylor Valley. Our spectral approaches can detect low masses of biocrust material in laboratory microcosms down to biocrust concentrations of 1% by mass. These techniques also distinguish the spectra of biocrust from both surface rock and mineral signatures from orbit. We found that biocrusts are present throughout the soils of eastern Taylor Valley and are associated with diverse underlying soil communities. The densest biocrust communities identified in this study had total organic carbon 5x greater than the content of typical arid soils. The most productive biocrusts were located downslope of melting snowpacks in unique soil ecosystems that are distinct from the surrounding arid landscape. There are similarities between the snowpack and stream sediment communities (high diversity of soil invertebrates) as well as their ecosystem properties (e.g., persistence of liquid water, high transfer of available nutrients, lower salinity from flushing) compared to the typical arid terrestrial ecosystem of the dry valleys. Our approach extends the capability of orbital remote sensing of photosynthetic communities out of the aquatic margins and into the drier soils which comprise most of this landscape. This interdisciplinary work is critical for measuring and monitoring terrestrial carbon stocks and predicting future ecosystem dynamics in this currently water-limited but increasingly dynamic Antarctic landscape, which is particularly climate-sensitive and difficult to access.\r\n", "east": 163.62487792969, "geometry": ["POINT(162.666320800785 -77.664144585346)"], "keywords": "Antarctica; Carbon; Cryosphere; McMurdo Dry Valleys; Snow", "locations": "McMurdo Dry Valleys; Antarctica", "north": -77.519802097166, "nsf_funding_programs": "Antarctic Organisms and Ecosystems", "persons": "Barrett, John", "project_titles": null, "projects": null, "repositories": null, "science_programs": null, "south": -77.808487073526, "title": "Hyperspectral reflectance values and biophysicochemical properties of biocrusts and soils in the Fryxell Basin, McMurdo Dry Valleys, Antarctica", "uid": "601773", "west": 161.70776367188}, {"awards": null, "bounds_geometry": ["POLYGON((-180 -60,-144 -60,-108 -60,-72 -60,-36 -60,0 -60,36 -60,72 -60,108 -60,144 -60,180 -60,180 -63,180 -66,180 -69,180 -72,180 -75,180 -78,180 -81,180 -84,180 -87,180 -90,144 -90,108 -90,72 -90,36 -90,0 -90,-36 -90,-72 -90,-108 -90,-144 -90,-180 -90,-180 -87,-180 -84,-180 -81,-180 -78,-180 -75,-180 -72,-180 -69,-180 -66,-180 -63,-180 -60))"], "date_created": "Fri, 13 Oct 2023 00:00:00 GMT", "description": "Blue-ice areas (BIAs) and their geographical distribution in Antarctica were mapped using Landsat-7 ETM+ images with 15 m spatial resolution obtained during the 1999\u20132003 austral summers and covering the area north of 82.5\u00b0 S, and a snow grain-size image of the MODIS-based Mosaic of Antarctica (MOA) dataset with 125 m grid spacing acquired during the 2003/04 austral summer from 82.5\u00b0S to the South Pole. A map of BIAs was created with algorithms of thresholds based on band ratio and reflectance for ETM+ data and thresholds based on snow grain size for the MOA dataset. The underlying principle is that blue ice can be separated from snow or rock by their spectral discrepancies and by different grain sizes of snow and ice. We estimate the total area of BIAs in Antarctica during the data acquisition period is 234 549 km2, or 1.67% of the area of the continent. Blue ice is scattered widely over the continent but is generally located in coastal or mountainous regions. The BIA dataset presented in this study is the first map covering the entire Antarctic continent sourced solely from ETM+ and MODIS data. Support by National Natural Science Foundation of China (grant No. 41106157) and NASA grant NNX10AL42G (nsidc0549_hui_V0).", "east": 180.0, "geometry": ["POINT(0 -89.999)"], "keywords": "Antarctica; Blue Ice; GIS; Glaciology; LANDSAT; MODIS; Remote Sensing; Snow/ice; Snow/Ice", "locations": "Antarctica", "north": -60.0, "nsf_funding_programs": null, "persons": "Hui, Fengming; Scambos, Ted", "project_titles": null, "projects": null, "repositories": null, "science_programs": null, "south": -90.0, "title": "Distribution of blue ice areas in Antarctica derived from Landsat ETM+ and Modis images", "uid": "601742", "west": -180.0}, {"awards": null, "bounds_geometry": ["POINT(-58 -62)"], "date_created": "Mon, 21 Dec 2020 00:00:00 GMT", "description": "Surface spectra of red and green snow algae were collected at two sites on King George Island (KGI), the largest of the South Shetland Islands, and one site on northern Nelson Island (NI), southwest of KGI in January 2018. Optically thick (\u003e 30cm) snow packs were prioritized for spectral albedo data acquisition and corresponding snow algae sampling in order to minimize the impact of the underlying ground on spectral albedo. Sites were also selected based on where it was possible to sample 1) a control site with relatively clean snow having no visible snow algae 2) green snow algae, 3) red snow algae and 4) mixed-phase green and red algae. At each site, duplicates of each snow type were measured with the spectrometer (except at Nelson Island where only one Mixed site was observed). All samples were collected around noon local Chilean time, when the seasonal snow pack was also receiving the most incoming solar radiation. Spectral reflectance measurements were collected with an Analytical Spectral Devices (ASD) FieldSpec\u00ae 4 hyperspectral spectroradiometer (Malvern Panalytical, USA) between 350 and 2500 nm. The sensor was equipped with a light-diffusing fore optic remote cosine receptor (RCR) to measure planar irradiance. We selected three different locations and collected spectral measurements for two samples each of green, red, and mixed snow algae patches, and two algae-free or \u201cclean\u201d snow areas, for a total of 24 measurement sites (2 of each of the 4 types across the 3 sites). Areas with snowmelt ponding were avoided. The RCR was placed upward to collect the downwelling planar irradiance incident upon the snow surface (Ed) and the upwelling planar irradiance reflected from the snow (Eu). Measurements were collected in triplicate. The operator was located in a direction 90 - 135\u00ba away from the sun to minimize solar glint and self-shadowing. Snow conditions did not allow for a tripod, so nadir orientation was determined by practice with a level and by visual assistance of an observer. Since the measurements were carried out under heavily overcast conditions where irradiance is dominated by the diffuse insolation with no solar azimuthal dependence, the influence of slight tilt when measuring the downwelling irradiance (i.e. the cosine error) is expected to be minor (\u003c0.5%). The reflectance measurements were taken prior to excavation of snow sample for laboratory analysis. Post-processing of the data involved computing spectral reflectance, as the ratio of the upwelling flux normalized to the downwelling flux for each wavelength. The mean of the three measurements was calculated for each site. Ambient light conditions were too low in the short-wave infrared wavelengths for getting adequate signal-to-noise for our measurements. In post-processing, reflectance values were truncated at 1350 nm for this analysis. This value represents the limit often used for RF calculations in other studies. In addition, empirical correction coefficients were used to correct for temperature related radiometric inter-channel steps using the procedure and MATLAB code from Hueni et al. (2017). This removed the step function near 1000 nm for most of the spectra, although not fully for all spectra. However, this discontinuity does not significantly impact results or albedo calculations. Albedo was calculated as the integrated R in two different intervals: visible (400-700 nm) and infrared (700-1300 nm). ", "east": -58.0, "geometry": ["POINT(-58 -62)"], "keywords": "Antarctica; South Shetland Islands", "locations": "South Shetland Islands; Antarctica", "north": -62.0, "nsf_funding_programs": null, "persons": "Khan, Alia", "project_titles": null, "projects": null, "repositories": null, "science_programs": null, "south": -62.0, "title": "Red and Green Snow Algae Surface Spectra", "uid": "601412", "west": -58.0}, {"awards": "1758224 Salvatore, Mark", "bounds_geometry": ["POLYGON((-180 -83,-177 -83,-174 -83,-171 -83,-168 -83,-165 -83,-162 -83,-159 -83,-156 -83,-153 -83,-150 -83,-150 -83.5,-150 -84,-150 -84.5,-150 -85,-150 -85.5,-150 -86,-150 -86.5,-150 -87,-150 -87.5,-150 -88,-153 -88,-156 -88,-159 -88,-162 -88,-165 -88,-168 -88,-171 -88,-174 -88,-177 -88,180 -88,177 -88,174 -88,171 -88,168 -88,165 -88,162 -88,159 -88,156 -88,153 -88,150 -88,150 -87.5,150 -87,150 -86.5,150 -86,150 -85.5,150 -85,150 -84.5,150 -84,150 -83.5,150 -83,153 -83,156 -83,159 -83,162 -83,165 -83,168 -83,171 -83,174 -83,177 -83,-180 -83))"], "date_created": "Fri, 15 Mar 2019 00:00:00 GMT", "description": "This data set contains reflectance spectra (350 - 2500 nm) of a range of rocks and sediments from the Central Transantarctic Mountains. Data were acquired using an Analytical Spectral Devices (ASD) FieldSpec4 high-resolution spectrometer under illumination with a high-output halogen bulb, with illumination and observation angles fixed at 0 and 30 degrees off-nadir, respectively. Data were acquired for the purposes of validation and \u0027ground truthing\u0027 of orbital multispectral data.", "east": -150.0, "geometry": ["POINT(180 -85.5)"], "keywords": "Antarctica; Glaciers/ice Sheet; Glaciers/Ice Sheet; Remote Sensing; Rocks; Solid Earth; Spectroscopy; Transantarctic Mountains", "locations": "Transantarctic Mountains; Antarctica", "north": -83.0, "nsf_funding_programs": "Antarctic Earth Sciences", "persons": "Salvatore, Mark", "project_titles": "EAGER: Surface Variability and Spectral Analyses of the Central Transantarctic Mountains, Antarctica", "projects": [{"proj_uid": "p0010020", "repository": "USAP-DC", "title": "EAGER: Surface Variability and Spectral Analyses of the Central Transantarctic Mountains, Antarctica"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -88.0, "title": "Laboratory Hyperspectral Reflectance Data of Central Transantarctic Mountain Rocks and Sediments", "uid": "601163", "west": 150.0}, {"awards": "0944248 MacAyeal, Douglas", "bounds_geometry": ["POLYGON((-63 -63,-62.2 -63,-61.4 -63,-60.6 -63,-59.8 -63,-59 -63,-58.2 -63,-57.4 -63,-56.6 -63,-55.8 -63,-55 -63,-55 -63.4,-55 -63.8,-55 -64.2,-55 -64.6,-55 -65,-55 -65.4,-55 -65.8,-55 -66.2,-55 -66.6,-55 -67,-55.8 -67,-56.6 -67,-57.4 -67,-58.2 -67,-59 -67,-59.8 -67,-60.6 -67,-61.4 -67,-62.2 -67,-63 -67,-63 -66.6,-63 -66.2,-63 -65.8,-63 -65.4,-63 -65,-63 -64.6,-63 -64.2,-63 -63.8,-63 -63.4,-63 -63))"], "date_created": "Tue, 29 Apr 2014 00:00:00 GMT", "description": "This data set addresses why surface melt water lakes on ice shelves and ice sheets are notably influential in triggering ice-shelf break-up and modulating seasonal ice flow, and are thus principle avenues by which environmental change can be transmitted to the ice sheets of Antarctica and Greenland. A comparative analysis is performed of lake geometry and derived depth (using Landsat image reflectance) in two distinct regions, one a collapsing ice shelf and the other an ablation zone of a land terminating ice sheet, to better characterize the range of surface lake variability.", "east": -55.0, "geometry": ["POINT(-59 -65)"], "keywords": "Antarctica; Antarctic Peninsula; Glaciers/ice Sheet; Glaciers/Ice Sheet; Glaciology; Ice Shelf; Larsen B Ice Shelf; Sample/collection Description; Sample/Collection Description; Supraglacial Meltwater", "locations": "Antarctic Peninsula; Larsen B Ice Shelf; Antarctica", "north": -63.0, "nsf_funding_programs": "Antarctic Glaciology", "persons": "MacAyeal, Douglas", "project_titles": "Model Studies of Surface Water Behavior on Ice Shelves", "projects": [{"proj_uid": "p0000052", "repository": "USAP-DC", "title": "Model Studies of Surface Water Behavior on Ice Shelves"}], "repo": "USAP-DC", "repositories": "USAP-DC", "science_programs": null, "south": -67.0, "title": "Standing Water Depth on Larsen B Ice Shelf", "uid": "609584", "west": -63.0}]

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