Data Tools
Explore web services, interactive tutorials, and other tools to access and work with NSIDC data
There are many ways to access and work with NSIDC data to accommodate a wide diversity of users. Use the filter menu to explore and narrow down your options. Note that the list defaults to show our Featured tools first, however, you have more options in the Sort by menu.
- To see which tools are available for which data sets, you must go to a specific data set landing page. On the landing page under Data Access and Tools, you will see data-set specific tools to access and work with the data.
- Once you are ready to find a data set, explore our data catalog.
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Discover, access, and visualize data from NASA's ICESat and ICESat-2 missions.
Supported software languages:
Python
Type: Web Application
Customization Capabilities:
spatial subsetting
temporal subsetting
Output Formats:
ASCII
CSV
HDF5
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earthaccess is a python library to search and access NASA Earth science data with just a few lines of code.
Supported software languages:
Python
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Learn how to discover, access, subset, and visualize Arctic sea ice data from Python-based Jupyter Notebooks. Tutorial comes with open-source libraries to harmonize sea ice height from ICESat-2, and ice surface temperature from MODIS.
Supported software languages:
Python
Customization Capabilities:
spatial subsetting
temporal subsetting
variable subsetting
reprojection
Output Formats:
HDF-EOS2
HDF5
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Download data, and explore data coverage and customization using the Python-based Jupyter Notebook.
Supported software languages:
Python
Customization Capabilities:
reprojection
spatial subsetting
temporal subsetting
variable subsetting
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Geolocate and display EASE-Grid and EASE-Grid 2.0 data sets with IDL software.
Supported software languages:
IDL
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Use example Python, MATLAB, IDL, or NCL code to import, read, and/or visualize select NSIDC DAAC data products.
Supported software languages:
MATLAB
Python
IDL
Type: Downloadable Software
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Access ICESat-2 data with as few as three lines of code. This Python software library wraps around APIs supported by the NSIDC DAAC.
Supported software languages:
Python
Type: Downloadable Software
Customization Capabilities:
spatial subsetting
temporal subsetting
variable subsetting
Output Formats:
HDF5
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Demonstrates using the earthaccess python package to search for and directly access cloud-hosted ICESat-2 data from an Amazon Compute Cloud (EC2) instance. This python-based Jupyter notebook uses Land Ice Height (ATL06) granules as an example.
Supported software languages:
Python
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Utilize the Jupyterbook for the latest Hackweek virtual event and learn about the ICESat-2 satellite, data products, data-access tools, and more. Access past hackwork tutorials from the ICESat-2 Hackweek Github Organization listed in the Quick Links.
Supported software languages:
Python
Type: Downloadable Software
Customization Capabilities:
spatial subsetting
temporal subsetting
variable subsetting
Customize
Interpolate BedMachine Antarctica data (NSIDC-0756) onto user-defined polar stereo coordinates with Python and MATLAB scripts. This tool lets you reproject data to geodetic latitude/longitude.
Supported software languages:
MATLAB
Python
Customization Capabilities:
reprojection
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Search and select Greenland Ice Mapping Project GIMP data at NSIDC, guided by a Python-based Jupyter Notebook. Build a QGIS project file from the search results. View data remotely if desired.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
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Spatially and temporally filter Greenland Ice Mapping Project (GIMP) image and velocity data, guided by a Python-based Jupyter Notebook. Spatially subset data and download in NetCDF format. This tool creates an interactive plot of time series data at selected points.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
Customization Capabilities:
spatial subsetting
variable subsetting
data reformatting
Output Formats:
NETCDF-4
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Reformat and/or visualize LVIS level 1B and 2 data products. Readers are available in C and IDL.
Supported software languages:
C
IDL
Type: Downloadable Software
Customization Capabilities:
data reformatting
Output Formats:
ASCII
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Use Python scripts to read and visualize daily and monthly snow depth and snow water equivalent ASCII files from the Canadian Meteorological Center Daily Snow Depth Analysis Data (NSIDC-0477) product. Convert a one-year snow depth ASCII file to GeoTIFF.
Supported software languages:
Python
Type: Downloadable Software
Last updated:
Customization Capabilities:
data reformatting
Output Formats:
GEOTIFF
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Reformat and/or visualize IceBridge data products using readers available in multiple programming languages.
Supported software languages:
Matlab
C
IDL
Python
Perl
Customization Capabilities:
data reformatting
Output Formats:
ASCII
BINARY
PNG
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Use this toolbox to read, process, analyze, and output ICESat-2 ATL03 and ATL08 data in these formats: figures, .las, .csv, .kml.
Supported software languages:
Python
Type: Downloadable Software
Customization Capabilities:
data reformatting
spatial subsetting
temporal subsetting
variable subsetting
Output Formats:
ASCII
CSV
HDF5
KML
PNG
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GIS
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Access, subset, project, interpolate, analyze, and/or combine data products with this Python library. Useful for geospatial analyses run locally or in the cloud.
Supported software languages:
Python
Type: Downloadable Software
Customization Capabilities:
data reformatting
spatial subsetting
temporal subsetting
variable subsetting
reprojection
Output Formats:
GEOTIFF
HDF4
HDF5
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Search for and download NSIDC DAAC data using the earthaccess python package. This python-based Jupyter notebook also demonstrates geospatial operations to crop and resample one GeoTIFF based on the extent and pixel size of another GeoTIFF, with the end goal of plotting one on top of the other. Two data sets from the NASA MEaSUREs program are used as examples.
Supported software languages:
Python
Customization Capabilities:
spatial subsetting
resampling
Output Formats:
GEOTIFF
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Download, bulk download, or visualize SMAP L3 and L4 data, guided by Python-based Jupyter Notebooks. These notebooks include examples of applying recommended quality flags for SMAP data.
Supported software languages:
Python
Output Formats:
HDF5
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GIS
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A Python-based Jupyter Notebook demonstrating how to access and visualize coincident snow data from the NSIDC DAAC across in-situ, airborne, and satellite platforms from NASA's SnowEx, ASO, and MODIS data sets, respectively.
Supported software languages:
Python
Customization Capabilities:
data reformatting
reprojection
spatial subsetting
Output Formats:
CSV
GEOTIFF
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Query, access, analyze, and download SnowEx data sets using a SQL database.
Supported software languages:
Python
Type: Downloadable Software
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