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R Bloggers
Date(s): - Aug 13, 2015

Scientists often need to create continuous datasets, in raster or gridded format, of biomass, carbon, vegetation height and other metrics from points sampled on the landscape. However, when converting points to pixels, there are many processing choices that can impact the uncertainty of derived raster datasets. Incomplete understanding of the uncertainty in derived products, in turn, impacts downstream analytical and model results and can lead to erroneous conclusions drawn from the data. 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.

Participants will leave the workshop with a better understanding of various point-to-pixel conversion methods (interpolators and other gridding methods), how to interpret the resulting pixel values, how to perform basic raster math, and some of the key questions we should ask ourselves before creating a seamless grid from a point-based dataset. ArcGIS will be the primary demonstration tool used in this workshop however all concepts can be applied using any program with gridding capabilities.

Workshop Instructor

  • Leah Wasser @leahawasser, Supervising Scientist, NEON,Inc

Workshop Assistants

  • Natalie Robinson, Staff Scientist, NEON,Inc
  • Claire Lunch @dr_lunch, Staff Scientist, NEON,Inc
  • Kate Thibault @fluby, Senior Staff Scientist, NEON,Inc

#WorkWithData Hashtag

Please tweet using the hashtag #WorkWithData during this workshop!

Also, you can tweet at @NEON_Sci!


Date: 13 August 2015 - Ecological Society of America Meeting Location: Baltimore, Maryland - Baltimore Convention Center, Rm 311

Time Topic
11:30 Spatial Gridding & Interpolation
1:00 —— Wrap Up! ——

Note: We will not cover geostatistical methods in this brown bag!