Join this 1.5-hour online workshop to learn the fundamentals of working with NEON Airborne Observation Platform remote sensing data in Google Earth Engine (GEE).
Join this 1.5-hour online workshop to learn the fundamentals of NEON data access and navigation, including using the neonUtilities package, reading metadata, and downloading data into a programming environment.
Join Hydrologists and data managers from the National Ecological Observatory Network (NEON) to learn more about the breadth of NEON's hydrology data products collected across observational, instrumented, and remote sensing subsystems. This is the second event in a two-part series.
Join Hydrologists and data managers from the National Ecological Observatory Network (NEON) to learn more about the breadth of NEON's hydrology data products collected across observational, instrumented, and remote sensing subsystems. This is a two part series taking place on Mar 4, 2026, and the second on Apr 1, 2026.
Register to attend a hands-on webinar, led by NEON Ambassador Kit Lewers, on July 9 that explores integrating NEON remotely sensed data with Global Biodiversity Information Facility (GBIF) mediated data and NASA hyperspectral imagery. Whether you're new to remote sensing or looking to deepen your integration of biodiversity and geospatial datasets, this session will offer concrete tools and reproducible code to jumpstart your own analyses.
The NEON Research Support Services (NRSS) makes available components of NEON’s infrastructure to members of the community to support their own research or other activities. Explore aspects of the NRSS Program, including the array of research support options and accessible infrastructure in this webinar.
This will be a webinar to introduce the mosquito pathogen testing survey. Participants will go through the background and rationale that was used to generate the survey and have an opportunity for questions at the end.
This Data Skills Webinar Series workshop will use NEON Airborne Observation Platform (AOP) discrete-return lidar point cloud data to explore change detection in vegetation structure following a wildfire disturbance.
