Creating New Nearest Neighbor Matches

This document is intended to be a roadmap for future cases of creating a new set of plots to run nearest neighbor matches against.

What you need:

• a file containing LAT/LON point data for all conditions to be considered
  • IDB v2.0
  • PNW FIA DB 2011
  • etc...
• buffered polygon data representing the regional variants to be considered
• a file containing summary data for the conditions, including:
  • stand age
  • LAT, LON
  • [fill in]
• Treelist data of the conditions, including
  • species
  • diameter (dbh)
  • [fill in]

Steps:

Create Condition-Variant Lookup CSV

• run an intersection query between the condition point-data and the buffered variant polygon data
• required columns:
  • Condition ID
  • Latitude
  • Longitude
  • Variant ID
• Export as a CSV
• Tools to choose from:
  • ArcMap (works well)
  • QGIS
    • Couldn't get field calculation to work as expected
  • Spatialite
  • geopandas (python package)

Create Forest-Type/Previous-Nearest-Neighbor-Match Table

• Table including:
  • User ID
  • Forest Type ID
  • Existing NN match for the Forest Type
  • Variant
• Format as input for "Matt's Query" (https://github.com/Ecotrust/forestplanner/blob/9d7043e4520b7af885b16618fd2b781d6df5138d/lot/trees/plots.py)

Replace TreeliveSummary and IdbSummary Tables With Updated Candidates

• David creates CSVs
• Ryan truncates old tables and loads in the new data
  • script to populate treelive_summary
    • Workhorse: lot/load_new_conditions.py (does both Treelive & CVLookup)
    • Run it from: lot/scripts/load_treelive.sh
      • Process gradually sucks up all memory and slows to a crawl. This wrapper script will restart it when it slows down too much.
      • This script does not like being executable in Vagrant Shared Folders. Feel free to copy it to /tmp and run it from there.
  • script to populate condition variant lookup
    • lot/load_new_conditions.py (uncomment correct lines)

Loop Through Existing Matches

• Current Nearest Neighbor matching code takes 1 Forest Type at a time.
• Wrap it in a loop to run once per each user-defined Forest Type/Stand info
• Creates a list of "Growth Candidates"
• output should be csv: each row is a user stand, variant, forest type, one of the matching ids found, and the rank (i.e. 1-10) of that match

Collect Desired Growth Candidate Coverage By Variant

• Be sure that you pull enough candidates to represent each variant
• Inputs:
  • FP User Forest-Types/Previous-Nearest-Neighbor-Match Table
  • Condition-Variant Lookup CSV
  • Condition Summary Table
  • Treelist for all Conditions

Run candidates through GYB