Upcoming Events

Past Events

NEON Data Education Fellows Faculty Mentoring Network Application Deadline

December 05, 2017

Apply to join a Faculty Mentoring Network (FMN) focused on implementing or adapting existing NEON teaching materials into your educational settings. Faculty who already teach using NEON data and would like to use this FMN to improve and transition it to an open educational resource are also welcome. 

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Harmonizing scale and process representation across the ecosystem of critical zone-oriented models and opportunities for cross-network synthesis

December 06, 2017

 In this webinar we will facilitate a lively discussion about the spatiotemporal scales, process representation, and motivating science questions by modelers involved in the CZO, LTER, ISMC, and NEON communities. Specifically, we seek to identify previously unrealized opportunities for synthesizing understanding across modeling perspectives, gaps in understanding that require new approaches, expertise not currently captured by community members, and key observations within the CZO/LTER/ISMC/NEON networks that could support breakthroughs in near Earth surface modeling.

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2017 AGU Fall Meeting

December 11 - 15, 2017

Make sure to attend NEON project and data related presentations at this year's AGU meeting to learn more about what we've been up to for the past year. It's been a busy, productive year for the Obervatory with significant progress made on construction of field sites, field sampling, sensor installation, remote sensing data collection, production of data products and delivery of data to the data portal.

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Workshop: Using NEON’s eddy4R eddy-covariance software and data products

December 12, 2017

A demo/discussion/workshop on eddy4R-Docker presented by NEON/Battelle atmospheric scientists. Eddy-4R Docker users can easily construct end-to-end workflows from raw NEON data to hypothesis testing in single processing environment. 

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Data science competition for converting remote sensing to ecological data

December 15, 2017

Scaling-up ecological patterns and processes is crucial to understanding the effects of environmental change on natural systems and human society. This Data Science Challenge pilot will include the use of NEON data in a challenge that multiple groups will attempt: to use the same remote sensing data from low flying airplanes to infer the location and type of trees in forests, and in turn, allow researchers to study forests in detail at much larger scales than is currently possible. This kind of collaborative data analysis challenge has proven highly effective in other fields for quickly improving methods for converting image data to useful information.

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