The participants of the workshop will learn about the available datasets and tools to study ecological processes using NEON data. By the end of the workshop, participants will understand how they can use the suite of NEON data products to address their research questions.
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.
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 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 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.
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.
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.
