eds

This package lets you run Environmental Data Summary (EDS) that merges survey data with external environmental data, such as chlorophyll A, photosynthetically active radiation (PAR), turbidity (Kd490), wave height, and sea surface temperature (SST).

Installation

You can install the development version of eds from GitHub with:

# install.packages("devtools")
devtools::install_github("krtanaka/eds")

Example

This is a basic example which shows you how to solve a common problem:

library(eds)

# Create a data frame with the provided data
eds_parameter <- data.frame(
  Dataset = c("Bathymetry_ETOPO_2022_v1_15s", "Sea_Surface_Temperature_OISST_Monthly"),
  Download = c("YES", "YES"),
  Frequency = c("Climatology", "Monthly"),
  URL = c("https://coastwatch.pfeg.noaa.gov/erddap/", "https://upwell.pfeg.noaa.gov/erddap/"),
  Dataset_ID = c("ETOPO_2022_v1_15s", "noaa_psl_4af9_4ab0_ab10"),
  Fields = c("z", "sst"),
  Summaries = c(NA, "mean;q05;q95;sd"),
  Mask = c(FALSE, FALSE)
)

# Save the data frame to a CSV file on the desktop
write.csv(eds_parameter, file = file.path("/Users/", Sys.info()[7], "Desktop", "eds_parameters.csv"), row.names = FALSE)

# Load example dataset (NCRMP 2010-2022)
df <- subset(df, region == "MHI")

run_eds(lon = df$lon,
        lat = df$lat,
        unit = df$island,
        time = df$date)