Data Citation and Acknowledgment
As a condition of using these data, you must cite the use of this data set. Such a practice gives credit to data set producers and advances principles of transparency and reproducibility.
10.5067/OMHVSRGFX38O
O'Neill, P. E., Chan, S., Njoku, E. G., Jackson, T., Bindlish, R. & Chaubell, J. (2021). SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture. (SPL3SMP, Version 8). [Data Set]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/OMHVSRGFX38O. [describe subset used if applicable]. Date Accessed 11-13-2024.
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COMPREHENSIVE Level of Service
Data: Data integrity and usability verified; data customization services available for select data
Documentation: Key metadata and comprehensive user guide available
User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services
In this section
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Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Data Access & Tools
A free NASA Earthdata Login account is required to access these data. Learn More
Quickly download a few files using a web browser, or access data through a command-line utility such as WGET.
Filter files before downloading based on date, spatial area, or file name. Choose from various download options, such as Python script. Export bounding boxes as a GeoJSON.
Search and order data from all NASA DAACs using spatial and temporal filters in a map interface. Reformatting, reprojecting, and subsetting options are available for some data sets.
Type: Web Application
earthaccess is a python library to search and access NASA Earth science data with just a few lines of code.
Supported software languages:
Python
Programmatically request selected data products through our API. This tool is valuable for selecting just the parameters you need from big data sets. Apply spatial and temporal filters, subsetting, reformatting, and reprojection.
Customization Capabilities:
data reformatting
reprojection
spatial subsetting
variable subsetting
Output Projections:
WGS 84 / NSIDC EASE-Grid North
WGS 84 / NSIDC EASE-Grid Global
WGS 84 / NSIDC EASE-Grid South
Geographic
Universal Transverse Mercator
Polar Stereographic
Browse and display global satellite imagery layers from NASA GIBS. Download raw data, share screenshots, and create animations from the imagery.
Type: Web Application
Customization Capabilities:
data reformatting
Sign up for automatic delivery of new data from active NASA satellite missions. Customize data with reformatting, reprojection, and subsetting if desired.
Customization Capabilities:
data reformatting
reprojection
spatial subsetting
variable subsetting
Extract point and area samples from geospatial data via spatial, temporal, and/or parameter subsetting. Preview and interact with samples before downloading. The Application for Extracting and Exploring Analysis Ready Samples tool is only available for select NSIDC data products.
Type: Web Application
Customization Capabilities:
data reformatting
reprojection
spatial subsetting
temporal subsetting
variable subsetting
Geolocate and display EASE-Grid and EASE-Grid 2.0 data sets with IDL software.
Supported software languages:
IDL
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
Explore contents of HDF4 and HDF5 files, including file structure, metadata, and parameter values.
Type: Downloadable Software
Calculate past and future satellite overpasses, based on latitude/longitude or map location.
Type: Web Application
Visualize georeferenced arrays in NetCDF, HDF and GRIB formats. Plot data on global or regional maps, choosing from multiple map projections. Overlay continent outlines or masks.
Type: Downloadable Software
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
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
Find, download, and process select SMAP L3 and L4 data products using this R package. This tool includes functions to extract gridded products and reformat to a GeoTIFF.
Supported software languages:
R
Type: Downloadable Software
Customization Capabilities:
data reformatting
variable subsetting