Instruction will include an overview of the breadth of available NEON AIS data and data product naming conventions, before jumping using the neonUtilities R package to access NEON AIS data. Participants will then learn how to interpret NEON data by referencing metadata records and standardized quality flags. In the final portion of the workshop, participants will be able to explore the individual AIS data products of interest to their research while NEON staff are on hand to address specific questions.
This workshop introduces participants to NEON, teaches them how to access and work with NEON data, and allows them to interact with NEON science staff to get assistance working on the specific data products they are interested in using. The workshop includes hands-on, interactive instruction on how to access and work with NEON data, both through the NEON data portal and programmatically. This workshop will also feature one or more presentations by scientists who work with NEON data within their area of expertise.
NEON will be hosting a 3-hour virtual workshop on accessing and using NEON biodiversity data for the 2020 Society for Freshwater Science (SFS) Summer of Science. Instruction will include an overview of the breadth of NEON biodiversity data before providing code-along with instruction on how to retrieve and convert NEON biodiversity data to standardized formats.
The ASLO-SFS Joint Meeting is cancelled, and consequently this program and all in-person NEON-related activities associated with ASLO-SFS are cancelled. However, NEON is teaching two workshops through the SFS Summer of Science and all NEON Early Career Scholars participants received an email inviting them to register for these workshops.
ENONE will be holding a virtual Explore NEON workshop for the University of Tennessee Chattanooga. This workshop includes instruction on how to access and use NEON data.
NEON will be holding a virtual workshop on exploring new dimensions of forest ecosystems with structural diversity in collaboration with PI Songlin Fei and co-PIs BS Hardiman and EA LaRue of Purdue University.
The National Science Foundation (NSF)-sponsored Ecological Forecasting Initiative Research Coordination Network (EFI-RCN) project, in partnership with the National Ecological Observatory Network (NEON), are hosting a virtual workshop focused on ecological forecasting using NEON data from May 12-13, 2020.
NEON will be participating in the 2020 EGU Virtual Data Help Desk by answering data questions on twitter, providing data demos and tutorials, and holding a virtual office hour.
The NSF sponsored joint NCAR/NEON workshop, Predicting life in the Earth system – linking the geosciences and ecology, is an opportunity to bring together members of the atmospheric science and ecological communities to advance the capability of Earth system prediction to include terrestrial ecosystems and biological resources. The workshop’s overarching theme will focus on convergent research between the geosciences and ecology for ecological forecasting and prediction at subseasonal to seasonal, seasonal to decadal, and centennial timescales, including use of observations, required data...
NCAR and NEON will be hosting a joint, NSF-funded workshop: Predicting life in the Earth system – linking the geosciences and ecology. The workshop’s overarching theme will focus on convergent research between the geosciences and ecology for ecological forecasting and prediction at subseasonal to seasonal, seasonal.
With the transition of AAG 2020 to a virtual meeting due to the COVID-19 pandemic, the Access and Work with Open, Continental-Scale Data from NEON workshop will also be virtual. Participants will get an introduction to accessing and using NEON data in this workshop.
The National Socio-Environmental Synthesis Center (SESYNC) announces its Spring 2020 Request for Proposals for collaborative team-based research projects that synthesize existing data, methods, theories, and tools to address a pressing socio-environmental problem. The request includes a research topic focused on NEON-enabled Socio-Environmental Synthesis. Proposals are due March 30, 2020 at 5 p.m. ET.
The National Socio-Environmental Synthesis Center (SESYNC) announces its Spring 2020 Request for Proposals for collaborative team-based research projects that synthesize existing data, methods, theories, and tools to address a pressing socio-environmental problem. The request includes a research topic focused on NEON-enabled Socio-Environmental Synthesis. Proposals are due March 30, 2020 at 5 p.m. ET.
This webinar will cover how to integrate NEON data into undergraduate classrooms, through Macrosystems EDDIE (Environmental Data-Driven Inquiry & Exploration; MacrosystemsEDDIE.org) teaching modules, other NEON teaching modules, and through independent use of NEON data.
The NEON program and the Ecological Society of America (ESA) are pleased to announce a 2020 NEON-ESA Early Career Scholars (NECS) program to help cultivate and support a diverse group of early career scholars and practitioners.
This 3-day workshop will seek to address several systemic problems that currently limit convergent research that uses the highest remote sensing technology to study problems at the interface of ecology, land change science, and social science.
NEON is seeking proposals for the Macrosystems Biology and NEON-Enabled Science (MSB-NES) Research on Biological Systems at Regional to Continental Scales program. Submit your proposal by January 16, 2020!
This unique networking and professional development opportunity is geared towards faculty interested in implementing or adapting existing NEON teaching materials to their educational settings.
How to make sense of complex observational datasets, such as collected by CHEESEHEAD, the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors? Could it be possible to bridge scale-mismatches such as between observations and models by jointly using spatial grids, continuous time series and discrete surveys? This workshop offers practical solutions through tutorials on accessing CHEESEHEAD data and using Environmental Response Functions (ERF) to combine multiple data sources for inference across observational and model perspectives!
This workshop focuses on remote sensing of vegetation and landforms using open source tools and reproducible science workflows -- the primary programming language will be Python.
This workshop will provide an introduction to the basics of data access and data navigation: discovering and accessing data via the NEON data portal, accessing data via the neonUtilities R package, understanding the content and quality of the data downloaded, and performing common data merges and transformations. Basic familiarity with R is recommended for participation in the workshop.
We are excited to join a diverse community of scientists as we all celebrate AGU’s centennial at the 2019 AGU Fall Meeting in San Francisco. You can learn more about the NEON program at booth #206 in the exhibit hall and then please make sure to attend the many NEON-related sessions taking place this year. All times are Pacific (local) Time. NEON-led Workshops Concurrent with AGU 2019 These free workshops require pre-registration, however, they are not part of the AGU 2019 conference and do not require conference registration. The registration form can be found on the workshop page linked in...
The 15th ArcticNet Annual Scientific Meeting is being held December 2-5, 2019 in Halifax, Canada. Interact with scientists working on the NEON program throughout the meeting and learn more about Sustainable Observing: Examining the Logistics and Infrastructure Required for Long-term Research in a Changing Arctic.
This webinar will provide an introduction to NEON and the over 175 data products with an emphasis on the aquatics and remote sensing data and infrastructure.
NEON will be at the 2019 Soil Science Society of America annual meeting. NEON scientists will be giving presentations on the NEON program and scientists from the soil community will also be presenting on their NEON-related research.