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2,021 results for “valley”
McMurdo Dry Valleys Adams Stream Gage Measurements
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. These tables contain data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the hydrology data set for the McMurdo Dry Valley's Adams stream measurements in the 1990-91 season. The Adams Stream data from 1990-91 was generated by the New Zealand ARP. Beginning January 2012, the MCMLTER established a new control downstream of the NZARP control. To date, we have not had enough field data to justify a rating curve to offer the 2012 onwards quality controlled hydrological data, but we expect to be able to offer these data by the 2016-17 season
McMurdo Dry Valleys Microbial mat biomass, isotopes, and nutrient ratios sampled over a longitudinal gradient of two McMurdo Dry Valley streams
We performed a field survey to assess changes in biomass, nutrient ratios, and isotopic signatures of three different microbial mat types in two glacial meltwater streams in the McMurdo Dry Valleys, Antarctica. Samples were taken in January 2013 from pre-existing transects over Von Guerard Stream and the Relict Channel, and stretched from near the Von Guerard Glacier terminus to the stream outlets at Lake Fryxell. In addition to the three microbial mat types, which included Nostoc (black), Chlorophyte (green), and Oscillatorean (orange) mats, particulate organic matter (POM) was collected from Von Guerard Stream in January 2008 over a full diel cycle in order to determine the origin of material in transport by comparing its elemental and isotopic characteristics with stream mats.
Lake water quality, chemistry and zooplankton composition for 16 lakes surrounding the Green Lakes Valley, 2016
This dataset contains water chemistry measurements made from 16 different lakes north and south of LTER site in the green lakes valley. At each visit water samples were collected for analysis of chlorophyll a and nutrient analysis and field measurements were recorded for pH, temperature, specific conductivity, dissolved oxygen (DO), % saturation, secchi depth, PAR. Secchi depth was measured using a 30cm disk to the nearest 0.25 meter and here recorded at the 0m row in the data file however it is a measurement of depth and so the units are meters. Most samples were collected between 0900 and 1300 MST. The first sampling date occurred shortly after lake had become ice free and then if the lake was at least 3 meters deep it was re-surveyed at approximately 2 week intervals. All data are collected from an inflatable raft at the point of deepest depth. All water samples were taken at the surface (0m), and the hypolimnion (about 2m above the lake sediment) using a Van Dorne sampler. Chlorophyll-a was extracted from water sample filters and absorbance was measured before and after acidification to quantify chlorophyll a concentration. Field measurements were conducted using a YSI either DO or multiple probe meter (YSI MPS 556) and a Li-Cor meter with a quantum sensor. Zooplankton samples were collected opportunistically 3 times throughout the summer, once immediately after ice-out and two more times with at least 14 days bewteen each subsequent visit. Zooplankton were sampled at the deepest location of each lake by pulling a conical net (Wisconsin net) vertically through the water column (i.e., vertical tow sample). The Wisconsin net is 0.9m long with an opening of an inner diameter of 0.2m and a mesh size of 80um. The vertical tow samples are taken from approximately 0.5 m off the lake bottom. After the net is raised and the sides rinsed, the sample is transferred to a 250 mL jar and preserved in a solution of 80% Ethanol. Jars are labeled with date (yyyy-mm-dd), time hh:
Physiological stress of pika for Niwot Ridge, Green Lakes Valley and Brainard Lake Recreation Area, 2017
During the spring and fall of 2017 we collected fecal samples to evaluate physiological stress within American pika (Ochotona princeps) populations occupying different sites on and near Niwot Ridge. By using non-invasive methods to collect fecal samples from pikas in the field, we were able to measure baseline stress hormone (glucocorticoid) metabolites in individuals. Fresh fecal samples deposited in traps by trapped pikas were paired with fresh fecal samples collected from the territory in which the same pika was trapped. Fresh fecal samples were also collected from plot surveys and other locations during the 2017 Niwot Ridge pika survey. Along with pika occupancy surveys, surveys of physiological stress have the potential to explain patterns of pika distribution across the landscape.
Talus microbes and plant assessment for the upper Green Lake Valley from 2007 to 2008.
It is increasingly recognized that species distributions are driven by both abiotic factors and biotic interactions. Despite much recent work incorporating competition, predation, and mutualism into species distribution models (SDMs), the focus has been confined to aboveground macroscopic interactions. Biotic interactions between plants and soil microbial communities are understudied as potentially important drivers of plant distributions. Some soil bacteria promote plant growth by cycling nutrients, while others are pathogenic; thus they have a high potential for influencing plant occurrence. We investigated the influence of soil bacterial clades on the distributions of bryophytes and 12 vascular plant species in a high elevation talus-field ecosystem in the Rocky Mountain Front Range, Colorado, USA. We used an information- theoretic criterion (AICc) modeling approach to compare SDMs with the following different sets of predictors: abiotic variables, abiotic variables and other plant abundances, abiotic variables and soil bacteria clade relative abundances, and a full model with abiotic factors, plant abundances, and bacteria relative abundances. We predicted that bacteria would influence plant distributions both positively and negatively, and that these interactions would improve prediction of plant species distributions. We found that inclusion of either plant or bacteria biotic predictors generally improved the fit, deviance explained, and predictive power of the SDMs, and for the majority of the species, adding information on both other plants and bacteria yielded the best model. Interactions between the modeled species and biotic predictors were both positive and negative, suggesting the presence of competition, parasitism, and facilitation. While our results indicate that plant–plant co-occurrences are a stronger driver of plant distributions than plant–bacteria co-occurrences, they also show that bacteria can explain parts of plant distributions that remain
Water chemistry data for Green Lakes Valley, 2018
Recently, the link between air warming and stream chemistry fluxes at GLV was evaluated by Crawford et al (2019) that showed strong connection between the sum of average daily temperature at a monthly time step and normalized fluxes of base cations and SO4--. They explored the reasons for this relation evoking several direct and indirect mechanisms and concluded that enhanced sulfide mineral weathering in and around the rock glacier is a result of recent warming-induced changes to minerals weathering. However, on the basis of a pattern recognition analysis of base cations and major anions concentrations we hypothesized that the observed trends in the GLV and probably across the Rocky Mountains region resulted from a combination of several mechanisms rather than warming trend alone. So the main objective of this work is to re-examine the Niwot Ridge LTER long-term data coupled with additional ancillary data sets to ascertain the mechanisms instigating the observed trends.
High-Resolution Orthorectified Imagery from 1999, Niwot Ridge LTER Green Lakes Valley Project Area, Colorado
The 1:12,000 photos were flown by Rocky Mountain Aerial, the LTER project manager is Don Cline. The Green Lakes Valley orthophoto was produced using 8 black and white photograph stereopair diapositives, flown at 1:12,000 scale in September, 1994 by Rocky Mountain Aerial, Denver, Colorado. Two flightlines were used to create this orthophoto, as there was not enough information in one flightline to include the entire GLV watershed. The diapositives were scanned in using ASIs high resolution drum scanner. An evenly spaced 25-m cellsize DEM was created from dtm.xyz using the outer boundary of the photographs. This DEM was used to register the 1:12,000 stereopairs to the UTM coordinate system with a horizontal location accuracy of 25-m. Once the 1:12,000 photographs were registered and rectified a .5-m cellsize digital orthophoto was produced for the Green Lakes Valley. There were a few problems with orthophoto generation in this area, mostly because of the steep terrain. Firstly, the stereopairs were NOT flown to generate othophotos, they were flown to generate DEMs. Because of this there was not enough overlap for generation of a seamless orthophoto. As the photos were warped to fit a planimetric base, there were a few areas with no data in the middle of the orthophoto. These areas were minimized because of ASIs expertise, but they show up as small black bars in the middle of the orthophoto. There are also some layover problems because of the steep terrain. This is caused by a steep mountain on the edge of the photo that lays over in one direction on one photo and lays over in another direction on the photo beside it. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
High-Resolution Orthorectified Imagery from 1999, Resampled to 10 meter, Niwot Ridge LTER Green Lakes Valley Project Area, Colorado
Orthophoto has been resampled to 10 meter. The 1:12,000 photos were flown by Rocky Mountain Aerial, the LTER project manager is Don Cline. The Green Lakes Valley orthophoto was produced using 8 black and white photograph stereopair diapositives, flown at 1:12,000 scale in September, 1994 by Rocky Mountain Aerial, Denver, Colorado. Two flightlines were used to create this orthophoto, as there was not enough information in one flightline to include the entire GLV watershed. The diapositives were scanned in using ASIs high resolution drum scanner. An evenly spaced 25-m cellsize DEM was created from dtm.xyz using the outer boundary of the photographs. This DEM was used to register the 1:12,000 stereopairs to the UTM coordinate system with a horizontal location accuracy of 25-m. Once the 1:12,000 photographs were registered and rectified a .5-m cellsize digital orthophoto was produced for the Green Lakes Valley. There were a few problems with orthophoto generation in this area, mostly because of the steep terrain. Firstly, the stereopairs were NOT flown to generate othophotos, they were flown to generate DEMs. Because of this there was not enough overlap for generation of a seamless orthophoto. As the photos were warped to fit a planimetric base, there were a few areas with no data in the middle of the orthophoto. These areas were minimized because of ASIs expertise, but they show up as small black bars in the middle of the orthophoto. There are also some layover problems because of the steep terrain. This is caused by a steep mountain on the edge of the photo that lays over in one direction on one photo and lays over in another direction on the photo beside it. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospa
Digital Terrain Model (DTM) from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Terrain Model (DTM) is derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain importan
Digital Terrain Model (DTM) shaded relief from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Terrain Model (DTM) shaded relief is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DTM shaded relief was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DTM shaded relief has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. This shaded relief model was also generated. A similar layer, the Digital Surface Model (DSM), is a first-stop elevation layer. A processing report and readme file are included with this data release. The DTM dataset is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain important geospatial data pr
Digital Surface Model (DSM) from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Surface Model (DSM) is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. A shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: This EML metadata file does not contain
Digital Surface Model (DSM) shaded relief from 2005 LiDAR for the Green Lakes Valley, Colorado
This 1m Digital Surface Model (DSM) shaded relief is derived from first-stop Light Detection and Ranging (LiDAR) point cloud data from September 2005 for the Green Lakes Valley, near Boulder Colorado. The DSM was created from LiDAR point cloud tiles subsampled to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the University of Colorado, Institute of Arctic and Alpine Research (INSTAAR) and NCALM, which is funded by the National Science Foundation (NSF). The DSM shaded relief has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 35 km^2. The LiDAR point cloud data was acquired with an Optech 1233 Airborne Laser Terrain Mapper (ALTM) and mounted in a twin engine Piper Chieftain (N931SA) with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from two GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DSM surface was created by mosaicing and then kriging 1 km2 LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy and vertical accuracy is unknown. cm RMSE at 1 sigma. The layer is available in GEOTIF format approx. 265 MB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum computed using NGS GEOID03 model, with FGDC-compliant metadata. This shaded relief model was also generated. A similar layer, the Digital Terrain Model (DTM), is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. A processing report and readme file are included with this data release. The DSM dataset is available through an unrestricted public license. The LiDAR DEMs will be of interest to land managers, scientists, and others for study of topography, ecosystems, and environmental change. NOTE: T
2010 Snow Survey for Green Lakes Valley, Niwot Ridge LTER, Colorado
Yearly snow surveys were conducted in the Green Lakes Valley in the City of Boulder Watershed at the estimated peak of snowpack in late spring. Over a period of several days, surveying teams (1 to several people) traversed valley slopes measuring snow depth with avalanche probes. Locations of each depth measurement were recorded as waypoints in Garmin hand-held GPS units (eTrex Legend and eTrex Legend H models). Snow depths were recorded on standardized field sheets along with dates, recorder names, waypoint numbers, and comments. GPS locations were downloaded as text files from Garmin units using Topo! software, specifying NAD83 for surveys conducted after 2009. Download files contained waypoint number, latitude, longitude, date, and elevation. Each file was imported into a Microsoft Excel spreadsheet and snow depths corresponding to waypoints were entered manually from field sheets. Shapefiles were constructed in ArcInfo/ArcGIS from dbf files generated either directly from Excel spreadsheets (before 2008) or after importing into Microsoft Access and then exporting as dbfs. All shapefiles are provided in a UTM zone 13 projection and NAD83 horizontal datum. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
2011 Snow Survey for Green Lakes Valley, Niwot Ridge LTER, Colorado
Yearly snow surveys were conducted in the Green Lakes Valley in the City of Boulder Watershed at the estimated peak of snowpack in late spring. Over a period of several days, surveying teams (1 to several people) traversed valley slopes measuring snow depth with avalanche probes. Locations of each depth measurement were recorded as waypoints in Garmin hand-held GPS units (eTrex Legend and eTrex Legend H models). Snow depths were recorded on standardized field sheets along with dates, recorder names, waypoint numbers, and comments. GPS locations were downloaded as text files from Garmin units using Topo! software, specifying NAD83 for surveys conducted after 2009. Download files contained waypoint number, latitude, longitude, date, and elevation. Each file was imported into a Microsoft Excel spreadsheet and snow depths corresponding to waypoints were entered manually from field sheets. Shapefiles were constructed in ArcInfo/ArcGIS from dbf files generated either directly from Excel spreadsheets (before 2008) or after importing into Microsoft Access and then exporting as dbfs. All shapefiles are provided in a UTM zone 13 projection and NAD83 horizontal datum. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
2012 Snow Survey for Green Lakes Valley, Niwot Ridge LTER, Colorado
Yearly snow surveys were conducted in the Green Lakes Valley in the City of Boulder Watershed at the estimated peak of snowpack in late spring. Over a period of several days, surveying teams (1 to several people) traversed valley slopes measuring snow depth with avalanche probes. Locations of each depth measurement were recorded as waypoints in Garmin hand-held GPS units (eTrex Legend and eTrex Legend H models). Snow depths were recorded on standardized field sheets along with dates, recorder names, waypoint numbers, and comments. GPS locations were downloaded as text files from Garmin units using Topo! software, specifying NAD83 for surveys conducted after 2009. Download files contained waypoint number, latitude, longitude, date, and elevation. Each file was imported into a Microsoft Excel spreadsheet and snow depths corresponding to waypoints were entered manually from field sheets. Shapefiles were constructed in ArcInfo/ArcGIS from dbf files generated either directly from Excel spreadsheets (before 2008) or after importing into Microsoft Access and then exporting as dbfs. All shapefiles are provided in a UTM zone 13 projection and NAD83 horizontal datum. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER collected on 1988-12-12
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER, originally collected on 1988-12-12 (19:58:37.3570810Z) by Landsat 4, row 116, path 55. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40551161988347XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-02T22:37:57Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER collected on 1988-12-28
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER, originally collected on 1988-12-28 (19:58:48.9010940Z) by Landsat 4, row 116, path 55. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40551161988363XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-08-18T09:44:46Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER collected on 1989-01-29
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER, originally collected on 1989-01-29 (19:59:20.8290310Z) by Landsat 4, row 116, path 55. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40551161989029XXX04, LPGS_12.0.2, USGS, Sioux Falls, 2012-08-18T09:45:09Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER collected on 1989-02-14
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER, originally collected on 1989-02-14 (19:59:35.1740130Z) by Landsat 4, row 116, path 55. Cloud cover was 20 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40551161989045XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-08-18T09:44:36Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER collected on 1989-03-18
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for McMurdo Dry Valleys LTER, originally collected on 1989-03-18 (19:59:29.0770880Z) by Landsat 4, row 116, path 55. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40551161989077XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-06-30T16:59:45Z.
ScienceDex guides
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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.