Process

Basic Steps

• get LiDAR data from the USGS LiDAR Explorer
• get digital surface model (DSM) and digital terrain model (DTM) from LiDAR data
• DSM - DTM = canopy height model (CHM)
• push CHM's to this repo
• use CHM to estimate individual tree heights
• use CHM to estimate tree volume
• produce reports (e.g. histograms, stats)
• document these steps in more detail, so they can be reviewed and replicated

Possible Enhancements

• get Global Forest Change (GFC) data to account for post-2017 forest loss (TN LiDAR dates to 2016-2017)
  • create a script for getting GFC data using Google Earth Engine
• refine parcels to clean up boundaries and align them with .gov parcel data
• remove GFC areas of recent forest loss from the canopy height models
• test AI plugins for tree detection
  • Tree Eyed
  • MapFlow
• do a comparative analysis using USGS TreeMap data