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).
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’.
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 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.
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.
This workshop will provide hands on experience with working hierarchical data formats (HDF5) in R. Objectives After completing this workshop, you will be able to: Describe what the Hierarchical Data Format (HDF5) is. Create and read from HDF5 files in R. Read and visualization time series data stored in an HDF5 format. Things to Do Before the Workshop To participant in this workshop, you will need a laptop with the most current version of R and, preferably, RStudio loaded on your computer. For details on setting up R & RStudio in Mac, PC, or Linux operating systems please see Additional Set up...
This workshop will provide hands on experience with working lidar data in raster format in R. It will cover the basics of what lidar data are and commonly derived data products.
NEON is participating in this workshop, which will evaluate the combined value of observations from large networks and emerging approaches in earth system modeling.
This science team meeting for Principal Investigators, Co-Investigators, Collaborators and Students funded through NASA’s Carbon Cycle and Ecosystems Focus Area programs provides an opportunity to share scientific research results and foster interdisciplinary interactions.
The NSF's Directorate for Biological Sciences will consider requests for funding to support conferences for bringing together a team of researchers to coordinate plans for synthesis of NEON data, and early concept grants for exploratory research to support innovative research that leverages NEON data.
NEON Staff Scientist Andy Fox is moderating the breakout session "catalyzing carbon cycle science through synergies among research networks" on Wednesday, January 28 at 5:30 pm EST.
This workshop will offer ecologists an overview of the variety of data formats and types that are typically encountered when working with 'Big Data', and an introduction to available tools in R for working with these formats.
