Join Battelle scientists for the NEON project, Stefan Metzger and Cove Sturtevant as they talk about NEON's flux tower network, atmospheric data collection and the continued development of supporting software for reproducible, extensible and portable data analysis.
Join colleagues from around the world for a discussion of opportunities and challenges in using data from multiple observatory networks to advance modeling of Earth system dynamics.
The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America will host more than 4,000 scientists, professionals, educators, and students at the 2017 International Annual Meeting, "Managing Global Resources for a Secure Future," on Oct. 22-25, 2017, in Tampa, Florida.
Participants in this workshop will explore how to directly access the full NEON database to get the data they want for use in the classroom. Participants will also explore already curated teaching data subsets that are available for download and classroom use.
The 14th annual Research Insights in Semiarid Ecosystems (RISE) Symposium will be held Saturday, 21 October 2017, 8:30 AM to 3:00 PM on the University of Arizona campus.
NEON will be at the 4th Annual Life Discovery - Doing Science Biology Education Conference (LDC)! The theme challenges educators to create environments for their learners to discover, investigate, and inform with data.
Come to this workshop to learn to navigate the NEON API. NEON scientists will demonstrate how to use the API, focusing on access via the R package httr, but also covering the general API structure.
Come to this workshop to learn to navigate the NEON data Application Programming Interface (API). It will be held at the 2017 meeting of the Ecological Society of America (ESA) in Portland, OR.
This year, NEON scientists will be at the 2017 Ecological Society for America (ESA) annual meeting presenting at more than a dozen symposia and poster sessions. The NEON program booth is #410, and many of our scientists will be on-hand throughout the week at the booth to answer your questions about the observatory.
Our 2017 Data Institute focuses on remote sensing of vegetation using open source tools and reproducible science workflows – the primary programming language will be Python. The Institute will be held at NEON headquarters in June 2017.
The 2017 Data Institute in Remote Sensing with Reproducible Workflows provides a unique opportunity for participants to gain hands-on experience working with open data using well-documented reproducible methods.
Apply for the 11-week NEON internship program, in which NEON hosts undergraduate interns who work on projects from helping design sensor assemblies to testing sampling protocols to analyzing data.
This workshop is part of a series of NSF/NEON supported training on the use of datasets from the NEON Airborne Observing Platform to enable new discoveries in the biophysical research community.
Topographic, Geomorphic, And Vegetation Analysis With Lidar is a NSF/NEON workshop taught by OpenTopography and NEON lidar experts will consist of lectures and labs on topographic, geomorphic, and vegetation analysis with lidar point clouds and derived products. The course will utilize NEON data and attendees will have the opportunity to bring their own datasets for analysis.
The 2016 Data Institute focused on remote sensing of vegetation using open source tools to promote reproducible science. This Institute was be held in Boulder, CO from 20-25 June 2016.
This two day workshop, taught at the USGS National Training Center at the Federal Center in Denver, CO on April 12-13, 2016, will cover how to work with spatio-temporal data in R.
The National Ecological Observatory Network (NEON) is hosting a 3-day lesson-building hackathon to develop a suite of NEON/ Data Carpentry data tutorials and corresponding assessment instruments.
This lunchtime brown-bag workshop will explore how different gridding methods and associated settings can impact rasters derived from sample points. We will use a LiDAR point cloud, which represents canopy height values, to create several raster grids using different point-to-pixel conversion methods. We will then quantify and assess differences in height values derived using these different methods.
This session, held at the Ecological Society of America's (ESA) Annual Meeting, highlights current and future opportunities for utilizing the data and other resources available from the National Ecological Observatory Network (NEON).
