The NEON Project is reaching out to the archival community to gauge interest in supporting the long-term archival needs for the project. Responses are due by COB, Friday, June 23, 2017.
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.
National Socio-Environmental Synthesis Center (SESYNC)
The National Socio-Environmental Synthesis Center (SESYNC) will host a nine-day short course August 15 - 25, 2017 covering basic principles of using Bayesian models to gain insight from data.
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 working meeting will be used to resolve key issues and questions critical to formulating the institutional framework and operation and maintenance of the NEON Bioarchive.
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.
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.
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.
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.
This 30 minute webinar will provide an overview of who can use the toolkit, what resources are included, and how it can be used to improve projects and partnerships at all stages of development.
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).
Come visit NEON in the exhibit hall at booths 319, 321, 418 & 420 and learn more about the National Ecological Observatory Network. NEON staff will be presenting or co-presenting a variety of workshops.
This workshop will overview three key data formats: ASCII, HDF5 and las and several key data types including temperature data from a tower, vegetation structure data, hyperspectral imagery and lidar data, that are often encountered when working with ‘Big Data’.
This workshop will providing hands on experience with working with hyperspectral imagery in hierarchical data formats (HDF5) in R. It will also cover basic raster data analysis in R.
This NEON internal brownbag introduces the concept of Hierarchical Data Formats in the context of developing the NEON HDF5 operational file format. Look here to discover resources on HDF5, code snippets in R, Python and Matlab to use H5 files and some example H5 files for Remote Sensing Hyperspectral data and time series temperature data.
As a member of the organizing committee, Hank Loescher of the National Ecological Observatory Network will leading several sessions at the community-driven Building Global Ecological Understanding (BGEU) Workshop in Delaware between June 3-5.
This 10-day ICOS-NEON greenhouse gas data training workshop will train early career scientists in the discovery and use of in-situ data to address emerging issues in carbon cycle science including atmospheric science, biogeochemistry, and ecosystem science.