Are you looking to customize MODIS, GLAS, AMSR-E, or SMAP data? While customization options such as subsetting and reformatting are currently available through the NASA Earthdata Search web application, these services can now be accessed programmatically as a synchronous REST interface.
How does the API work?
Programmatic access to these data services is provided via an HTTPS URL. The programmatic access endpoint contains key-value pairs that utilize the Common Metadata Repository (CMR) to find the requested data, as well as the subsetting, reformatting, and reprojecting services to customize those data. When utilizing this API in a command line environment, the customized output is returned as either a single file or multi-file zip downloaded directly to your machine’s current working directory.
Why access data services programmatically?
While the NASA Earthdata Search application provides a comprehensive web-based search and order interface, you may be looking for a more direct access point for customized data. Using the new API feature, these data can now be easily accessed using a variety of approaches including URL transfer protocols (e.g. curl: https://curl.haxx.se/) and MATLAB readers (e.g. https://www.mathworks.com/help/matlab/ref/geotiffread.html). In addition, work is currently ongoing to provide OGC Web Coverage Service (WCS) compatibility, enabling data access through WCS-supported software such as ArcGIS, QGIS, and GeoServer.
Where can I learn more?
An overview guide to this API can be found at http://nsidc.org/support/how/how-do-i-programmatically-request-data-services. This guide walks you through the basic steps needed to construct the API, as well as resources to help you determine the customization options available for your data set(s) of interest. Comprehensive documentation provided by the API developers is also available on the Earthdata Developer Portal.
Comments? Concerns? Feedback?
Let us know! Email us at email@example.com to let us know how we can improve this API.
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 HDFView, which 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.
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:
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
No. The data variables are named differently in the HDF files than they are in the binary files. Thus, there are separate Data Dictionaries for these two file types.
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.