The NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) will be presenting a hands-on tutorial during the 2019 AGU Fall Meeting, hosted by the ARCUS Arctic Community Meeting Space. This tutorial will demonstrate our data discovery, access, subsetting services, and how to utilize basic open source resources to harmonize and analyze data across different remote sensing products.
Our data services team will be presenting this tutorial as a series of Python-based Jupyter Notebooks, focusing on sea ice height and ice surface temperature data from NASA’s ICESat-2 and MODIS missions, respectively, to characterize Arctic sea ice. No coding experience or computing prerequisites are required, though some familiarity with Python and Jupyter Notebooks is recommended.
Registration for this tutorial will close on Tuesday, December 10th, so please be sure to sign up to ensure a seat: https://forms.gle/48AiCNPdxbzoUDBH7
When: Wednesday, December 11th, 2:00 – 3:30 PST
Hotel Nikko, Room: Monterrey I
222 Mason St, San Francisco, CA 94102
We look forward to seeing you in San Francisco!This composite image is a measurement of Arctic sea ice freeboard taken by ICESat-2’s instrument from data acquired between 1 to 30 November 2018. Freeboard is the difference between the top of ice and the ocean. Pink = higher elevation; blue/white = lower elevation; white circle = no data. Image Credit: NASA GSFC Kel Elkins
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 firstname.lastname@example.org to let us know how we can improve this API.
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.