Applications of SMAP and Evapotranspiration Data: Webinar Series

If you are interested in Soil Moisture Active Passive (SMAP) data, we would like to bring your attention to an upcoming webinar series offered by the NASA Applied Remote Sensing Training (ARSET) Program that is focused on applications of SMAP and evapotranspiration data. This webinar series will help attendees learn about NASA soil moisture and evapotranspiration products and how to access and apply them for water resource management. Over the course of five weeks, attendees will learn how to monitor and manage water resources with techniques learned in training. The series will begin with an introduction to satellite missions and useful data sets. Next, trainers will demonstrate online portals for accessing data. The series will conclude with specific examples of how you can apply the data and modeled data products.

Webinar series details
Applications of Remote Sensing to Soil Moisture and Evapotranspiration
Dates: Thursdays, from September 1 to September 29.
Times: 11:30-12:30 or 18:00-19:00, Eastern Daylight Time (EDT).

Week 1: Introduction to Soil Moisture, Evapotranspiration, and an Overview of the SMAP Satellite Mission
Week 2: Applications of SMAP Data
Week 3: Accessing SMAP Data
Week 4: Landsat-based Evapotranspiration Estimates (METRIC) and Google Earth Engine Evapotranspiration Flux (EEFlux) Portal
Week 5: MODIS-based Evapotranspiration (ALEXI) and Soil Moisture and Evapotranspiration data from GLDAS/NLDAS

For more information and to register, please see:


Surface soil moisture in the Southeastern United States as retrieved from NASA’s SMAP satellite observatory at around 6 a.m. on Oct. 5, 2015. Large parts of South Carolina appear blue, representing areas with saturated soil conditions and possible standing water resulting from heavy localized rains and flooding. Large-scale flooding was experienced all over South Carolina on Oct. 5-6, 2015. Credit: NASA/JPL-Caltech/GSFC

ICESat/GLAS Data Produced in a Self-Describing Format (HDF5)

Throughout the life of the NASA ICESat mission and beyond, GLAS data have been distributed in binary format by the National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). These data have been extremely popular but not always conducive for all users to work with due to their binary format. Recently, with releases 33 and 34, GLAS data sets have also been produced in HDF5 format, providing data users with an alternative option for data analysis and visualization.

HDF5 is a self-describing data format, supporting complex data relationships via n-dimensional data sets. HDF5 is also compatible with many open source tools including HDFViewwhich allows you to easily browse the tree structure of each file and view the data as a table or image. Many other popular software programs and languages including MATLAB, Python, and ArcGIS support HDF5 file format, making it a versatile option depending on how you use GLAS data in your research.


Additionally, the NSIDC DAAC has been able to provide more services for GLAS HDF5 data, including spatial and temporal subsetting, file stitching, and the much sought after parameter subsetting, through the NASA Reverb search and order tool.

GLAS Reverb services

We need your feedback!

Although HDF5 format has many advantages over binary, the NSIDC DAAC receives a much greater number of GLAS binary subsetting requests and downloads than their HDF5 counterparts. In order to better understand the relative functionality and usability of each format, we are looking for your feedback. If you are familiar with ICESat/GLAS data, please take a few minutes to fill out our brief survey:

ICESat/GLAS Data Format Survey 


See the following Help Topic articles for further information:

How do I order a subset of GLAS HDF5 data?

How can I extract elevation from GLAS HDF5 data?

Stepping through the HDFView User Guide with GLAS HDF5 Data

Charctic: Viewing Sea Ice Data Interactively

The ability to view data interactively adds convenience to dynamic data analysis. While static graphs and images are informative, interactive tools allow users to view and analyze data on-the-fly. Readers of our Arctic Sea Ice News and Analysis blog enjoy daily updates on sea ice extent, but some wanted to see data from specific days or years that weren’t provided in the static graphs. Behold Charctic.


Explore sea ice data for the Arctic and Antarctic from NSIDC’s Sea Ice Index data set with the Charctic Interactive Sea Ice Graph. Sample graph for Arctic sea ice extent shown.

Developed at NSIDC with support from NASA, the Charctic Interactive Sea Ice Graph enables users to more easily access and explore NSIDC’s Sea Ice Index data set.

With this tool, you can:

  • Visualize sea ice extent data for the Arctic and more recently, the Antarctic.
  • View and compare sea ice extent data for any year or any combination of years between 1979 and 2014 (including near-real-time daily data).
  • Get daily sea ice extent values by rolling your cursor over a line in the graph.
  • See a corresponding daily sea ice concentration image by clicking on a line in the graph.
  • Download your customized graph or any of the corresponding daily sea ice concentration images.

If you are interested in tracking sea ice in the Arctic or the Antarctic, try it out.

Tips for working with AMSR-E Daily Soil Moisture data

Soil moisture is a key variable in understanding land surface hydrology and in modeling ecosystems, weather, and climate. Among NSIDC’s most popular data sets is the “AMSR-E/Aqua Daily L3 Surface Soil Moisture, Interpretive Parameters, & QC EASE-Grids” (AE_Land3) data set. This data set is distributed in HDF-EOS format and one of the biggest hurdles encountered by many users is simply learning how to display the data. Here are some tips on how to get started.

The HDF Group provides sample code for access and visualization of HDF data into IDL, MATLAB, and NCL. Access to the sample code for AMSR-E HDF data is provided on the HDF Group’s HDF-EOS Comprehensive Examples Web page.

If you are more familiar with GeoTIFF format, you may choose to utilize the HDF-EOS to GeoTIFF (HEG) Tool to convert AMSR-E Daily Soil Moisture HDF data into GeoTIFF format. This tool also allows you to subset the data with spatial or parameter constraints, as well as change the output projection. These HEG Tool services are also available as an option when ordering these data through the Reverb search and order interface. Instructions on how to use these data services in Reverb can be found in this Online Support article.

If you are interested in importing the data into ArcGIS, you can either use the GeoTIFF files generated by the HEG Tool or downloaded from Reverb, or you can perform a few steps to import the native HDF-EOS files into ArcMap. Using the ArcToolbox, you can easily extract a data field from an HDF file and save it in a different raster format that you are more familiar with. Instructions detailing how to do this can be found in this Online Support article.

AMSR-E L3 Daily Soil Moisture plot, 07/01/2002

AMSR-E L3 Daily Soil Moisture plot, 07/01/2002.

Looking for sample code for reading and visualizing NSIDC’s HDF data?

Hierarchical Data Format (HDF) supports a variety of data types and allows for the transfer and manipulation of scientific data across diverse operating systems and computer platforms. It was developed by the HDF Group at the University of Illinois and is the standard data format for all NASA Earth Observing System (EOS) data.

A variety of HDF data are distributed at NSIDC, including data from the AMSR-E, MODIS, and GLAS sensors as well as the NISE data set.

Despite the versatility of HDF, some data users have had difficulty in reading and displaying HDF data and often ask if we have sample code for reading HDF data in programs such as IDL and MATLAB.

Fortunately, the HDF Group provides sample code for access and visualization of HDF data into IDL, MATLAB, and NCL. Access to the sample code for NSIDC HDF data is provided on the HDF Group’s HDF-EOS Comprehensive Examples Web page.

Also note that this information can be found in our Online Support under the AMSR-E, MODIS, GLAS, and NISE forums.

Sample Matlab plot of AMSR-E 12km Sea Ice

Sample plot generated in MATLAB from AMSR-E 12km Sea Ice data (from

Recent enhancements to the NASA IceBridge Data Portal

The NASA IceBridge Project is comprised of airborne data over the most dynamic areas of the Arctic, Greenland, Alaska and Antarctica. The data gathered by this project are unique in that they are spatially referenced by flight lines, flights are flown during approximately 3-month campaigns, and data are collected by a wide variety of instrumentation.

The NASA IceBridge Data Portal provides a single location from which one can get an overview of all the IceBridge data sets. It allows for map-based visualization of the flight paths via polar views of the Northern and Southern Hemispheres.  Using a variety of filters and image overlays, one can visualize, search and download IceBridge data campaigns. NSIDC recently added some new capabilities to the IceBridge Data Portal. These new features include:

– A simpler display which allows users to hide and move informational windows

– The ability to filter results by selecting one or more instruments

– A tar-on-the-fly option for downloading complete directories of data at once

– New map layers for enhanced visualization including:

  • Mosaic of Greenland (MOG)
  • Shaded Relief DEM
  • MEaSUREs Velocity Map
  • Mosaic of Antarctica (MOA)
  • Antarctic Bedrock DEM
  • Radarsat Antarctic Mapping Project (RAMP)

Begin your search for IceBridge data through the newly improved NASA IceBridge Data Portal.