impute_missing_gaps: Impute missing annual & perennial canopy gaps with a linear...

In annack84/STMdevelopment: Develop State-and-Transition Models for the Upper Colorado River Basin

Impute missing annual & perennial canopy gaps with a linear model built by Anna based on NRI and LMF data

Description

Impute missing annual & perennial canopy gaps with a linear model built by Anna based on NRI and LMF data

Usage

impute_missing_gaps(
  indicator_data_target_wide,
  impute_gap_type = c("CA_percent_100plus", "CA_percent_200plus"),
  impute_sources = NULL
)

Arguments

indicator_data_target_wide	Data frame. Intermediate data product within plot_data_pull
impute_gap_type	Character vector. Gap type to predict. Supported options are "CA_percent_100plus" (% cover annual & perennial gaps >100 cm) and "CA_percent_200plus" (% cover annual & perennial gaps >200 cm)
impute_sources	Character. Optional. Only impute missing data for specific data source(s). Supported options are any source in plot_data$SourceKey

Value

Wide format data frame containing all indicators for the target ESG, including estimated annual & perennial canopy gaps for plots missing that data type.

annack84/STMdevelopment documentation built on April 12, 2024, 6:46 p.m.