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
NASA’s Operation IceBridge airborne mission has flown over 700 flights through some of the most stunning regions of the Arctic and Antarctic. Join us to learn how to discover and access data that “bridges” the gap between the ICESat and ICESat-2 missions.
When: Wednesday, July 25, 2018 at 2pm EDT (UTC/GMT-4).
For more information about the webinar, please visit NASA Earthdata
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