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  1. Get Involved
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  3. NEON-CyVerse Webinar

Event - Webinar

NEON-CyVerse Webinar

Feb 19, 2021

Hosted By:

CyVerse

NEON's massive database presents challenges for researchers who wish to analyze these 'big data' on their own personal computer. Fortunately, CyVerse offers a cloud computing platform that is optimized for 'big data' processing, with many tools available to support NEON data specifically. On Friday February 19th 2021 NEON Scientists Bridget Hass and Donal O'Leary will be joining CyVerse to present a 1-hour webinar highlighting the tools and workflows needed to process NEON data on CyVerse's massive cloud computing platform.

During this webinar, the presenters will discuss many of the NEON resources available to support your teaching, learning, and research. We have included links to these resources here for your review.

Webinar Recording:

Please see the Webinar Recording here [links to external CyVerse page] for the full discussion including Q&A. We suggest that you try to follow along with all of Bridget's demonstration, pausing and rewinding the video as needed. If you have any questions or need help, feel free to contact Bridget Hass or Donal O'Leary.

 

NEON Data API Tokens:

You have the option to set up your own NEON Data account, which will give you access to your own API token. Using this token as a part of your API requests has several benefits; most of which is faster download speeds (which really add up with our huge remote sensing data files!). 

Please see our R-Based Using an API Token when Accessing NEON Data with neonUtilities to set up an account and improve your download speeds.

In-depth resources are available on the NEON API page here.

 

Tutorials:

NEON's Data Skills tutorial resources are primarily designed for researchers who use R and/or Python. Listed below are the best tutorials for getting started with NEON Remote Sensing data, listed by coding language first.

R-based Introduction to Hyperspectral Remote Sensing Data Tutorial Series.

R-based Introduction to LiDAR tutorial series.

Python Based: The 2018 NEON Remote Sensing Data Institute has a great collection of python-based tutorials across the week-long workshop. Please see the agenda here to view these tutorials in their suggested order, sorted by topic.

 

Webpage Resources:

NEON Airborne Remote Sensing overview webpage with links to details about each of the three sensor systems: Discrete and full-waveform lidar, the hyperspectral imaging spectrometer, and the high-resolution RGB camera.

 

NEON Science YouTube Videos:

Exploring & Downloading NEON Data Products (one video, 7:27) This video is a little bit outdated but still a functional overview of how to download data from the NEON Data Portal graphical user interface

Virtual Tour of NEON's Airborne Observation Platform (AOP) (one video, 7:13) this is an excellent overview of the AOP and how NEON operates this amazing technology.

Science Explained Videos (eight videos, ~45 minutes total) these are excellent undergraduate-level animated videos that explain complex subjects such as lidar and hyperspectral imaging, as well as ecological forecasting and eddy covariance. Teachers love to use these in their classrooms!

NEON Remote Sensing: Fundamental Concepts and Data Products (10 videos, ~5 hours total) these are outstanding graduate-level seminars that explain in great detail the technology and theory behind NEON's AOP data products. Highly recommended for graduate audiences and the ambitious undergraduate for extracurricular purposes.

 

CyVerse Resources

In November, 2020, CyVerse welcomed NEON to co-host a multi-day workshop focused on NEON remote sensing data and CyVerse compute and storage resources. We have some great materials from this event, including:

  • The full workshop agenda here,
  • A great overview of file storage management on CyVerse here (so that you don't lose your work when your virtual machine shuts down!),
  • And a step-by-step walkthrough of how to launch your own 'analysis' (virtual machine) on CyVerse.

 

Recap

Location:

United States

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The National Ecological Observatory Network is a major facility fully funded by the National Science Foundation.

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