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Training data for aboveground biomass estimation models

Lidar_Training_Data - Lidar_Training_Data.csv
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Variables
Training data for aboveground biomass estimation models
  • Label:
  • Definition: Ranked predictor variable importance were, in descending order, Maximum Height, Minimum Height, 90th percentile, 10th percentile, 20th percentile, 50th percentile, 30th percentile, 80th percentile, 40th percentile, 60th percentile, and lastly the 70th percentile. Predictor variables were then added in order of ranked importance to the model until the addition of additional predictor variables resulted in a model with poorer model performance (lower cross validated R2 and Root Mean Squared Error (RMSE)).
  • Type: Nominal
  • Missing values: None specified

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Additional Information

FieldValue
mimetypetext/csv
filesize12.06 KB
resource typefile upload
timestampJun 29, 2021