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8 results for “SnowEx”
Sentinel-1 Derived Snow Depths and SnowEx Lidar Netcdfs
<p>These are netcdfs of S1 raw data, intermediate products, derived snow depths, ancillary data (IMS snow coverage, tree percentage) and lidar snow depths used in an analysis of the Lievens et al. (2021) algorithm.</p> <p> </p> <p>9 sites - Banner 2020, Banner 2021, Cameron 2021, Dry Creek 2020, Fraser 2020, Fraser 2021, Little Cottonwood Canyon 2021, Mores 2020, Mores 2021</p> <p> </p> <p>Data Variables:</p> <p>s1 - sentinel 1 backscatter data. contains 3 bands - VV, VH, and incidence angle</p> <p>ims - IMS snow coverage data (4 = snow covered, 2 = None) []</p> <p>fcf - Forest coverage fraction [%]</p> <p>deltaCR - change in the S1 cross ratio through time [dB]</p> <p>deltaVV - change in S1 VV backscatter through time [dB]</p> <p>deltaGamma - change in combined gamma variable [dB]</p> <p>snow_index - snow index in dB that is converted to derived snow depth by C parameter [dB]</p> <p>snow_depth - derived snow depth from S1 [m]</p> <p>wet_flag - flagged for snow with -2dB of change in CR. 1 = wet, 0 = dry</p> <p>alt_wet_flag - snow flagged by negative snow_index. 1 = wet 0 = dry</p> <p>freeze_flag - snow flagged as refreezing by increase of 1 dB in CR</p> <p>wet_snow - combined wet flag, alt wet flag, freeze flag, and previous time step's wet snow to get current wet snow flags</p> <p>perma_wet - snow that is flagged as wet more than 50% of last four acquisitions after Feb 1</p> <p>lidar-sd - Lidar derived snow depths [m]</p> <p>lidar-vh - lidar derived vegetation heights [m]</p> <p>lidar-dem - lidar derived snow free dems [m]</p> <p>aspect - aspect in degrees from lidar-dem [°]</p> <p>easting - degrees of easting from aspect[°]</p> <p>north - degrees of northing from aspect[°]</p> <p>confidence - unused metric of confidence</p>
SnowEx Hackweek 2021 Tutorial Data
<p>Datasets used for tutorials during 2021 SnowEx Hackweek https://snowex-hackweek.github.io/website/tutorials/index.html. Datasets are documented in each tutorial Jupyter Notebook, which have code examples for common analysis tasks. </p>
Lidar data for snowex hackweek
<p>This is a lidar data for 2022 snowex hackweek tutorial</p>
SnowEx Meteorological Station Measurements from Grand Mesa, CO V001
This dataset contains meteorological data collected as part of the ongoing the NASA SnowEx mission, from five meteorological stations installed between 2016-2017 in Grand Mesa, Colorado, to provide supporting data for SnowEx field campaigns and forcing data for modeling. Each station collects a suite of meteorological data at a fixed geographic point, from varying heights above and below the surface elevation. Measured data include: air temperature, relative humidity, long and shortwave solar radiation, barometric pressure, soil moisture and temperature, and derived snow depth. The temporal data coverage varies between each station, but spans October 2016 to August 2022. The dataset(s) contain air temperature and relative humidity (10ft and 20ft levels), 4-component radiation (shortwave, longwave), barometric pressure, soil-moisture and temperature (three depths), and a snow-depth product. Data coverage varies for each met station, but spans the time period of October 2016 – August, 2022. The data frequency is hourly and times are in UTC. The data is monotonic (no duplicate or mis-orderd timestamps) and steps have been taken to remove erroneous data. Periods of missing data are filled with NaN values. The scripts used to process raw data into the current format are available on the github page (https://github.com/wrudisill/GrandMesaMetData/blob/main/process_data_initial.py).
SnowEx Meteorological Station Measurements from Grand Mesa, CO Raw V001
This dataset contains raw meteorological data collected as part of the ongoing the NASA SnowEx mission, from five meteorological stations installed between 2016-2017 in Grand Mesa, Colorado, to provide supporting data for SnowEx field campaigns and forcing data for modeling
SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey V001
The data set provides digital terrain models (DTM), digital surface models (DSM) snow depth models, and canopy height models (CHM), derived from point cloud data (available as <a href="https://nsidc.org/data/SNEX_MCS_Lidar_Raw">SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey Raw, Version 1</a>) acquired by airborne lidar scanning. Data were collected as part of a multi-year effort to monitor monthly snow distribution over a 35 km² region of the Mores Creek Headwaters in the Boise Mountains of central Idaho between 2021 and 2024. Data acquisition in 2021 overlapped temporally with the NASA SnowEx 2021 field campaign.
SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey Raw V001
The data set described here provides raw lidar data collected as part of a multi-year effort to monitor monthly snow distribution over a 35 km² region of the Mores Creek Headwaters in the Boise Mountains of central Idaho between 2021 and 2024. Data acquisition in 2021 overlapped temporally with the NASA SnowEx 2021 field campaign. Digital terrain models (DTM), digital surface models (DSM) snow depth models, and canopy height models (CHM) derived from these point cloud data are available as <a href="https://nsidc.org/data/SNEX_MCS_Lidar">SnowEx Mores Creek Summit (MCS) Airborne LiDAR Survey, Version 1</a>.
SnowEx Colorado 3M Snow Depth Time Series and DEMs from High-Resolution Satellite Image Pairs V001
This data set contains a time series of snow depth maps and related intermediary snow-on and snow-off DEMs for Grand Mesa and the Banded Peak Ranch areas of Colorado derived from very-high-resolution (VHR) satellite stereo images and lidar point cloud data. Two of the snow depth maps coincide temporally with the 2017 NASA SnowEx Grand Mesa field campaign, providing a comparison between the satellite derived snow depth and in-situ snow depth measurements. The VHR stereo images were acquired each year between 2016 and 2022 during the approximate timing of peak snow depth by the Maxar WorldView-2, WorldView-3, and CNES/Airbus Pléiades-HR 1A and 1B satellites, while lidar data was sourced from the USGS 3D Elevation Program.
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