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added BADM data for canopy and measurement height
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@stineb
stineb committed Sep 12, 2024
1 parent e71ceab commit ef193df
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Showing 6 changed files with 728,525 additions and 34 deletions.
4 changes: 2 additions & 2 deletions data-raw/01_collect_meta-data.R
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Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,12 @@
# not correspond to the defaults as listed
# below)

library(tidyverse)
library(ingestr)
# remotes::install_github("bluegreen-labs/icoscp")
library(icoscp)
library(RCurl)
library(XML)
library(dplyr)
library(amerifluxr)

# Set local paths of data files -------------------------------------------------
Expand Down Expand Up @@ -142,7 +142,7 @@ if (!file.exists(filnam)){
saveRDS(sites_icos_warm_winter_2020, file = filnam, compress = "xz")
}

# # FLUXNET2015-------------------------------------------------------------------
# FLUXNET2015-------------------------------------------------------------------
# filnam <- here::here("data-raw/meta_data/fluxnet_meta_data.rds")
# if (!file.exists(filnam)){
#
Expand Down
198 changes: 166 additions & 32 deletions data-raw/02_compile_final_site_list.R
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,61 @@ output_path <- "/data_2/FluxDataKit/v3.4"
# sort through the sites lists depending on the
# order or preference of the data

# function to extract values from BADM file
get_values_badm <- function(df_badm, varnam){

groups <- amf_badm |>
filter(
VARIABLE_GROUP == paste0("GRP_", varnam),
VARIABLE == paste0(varnam, "_STATISTIC"),
DATAVALUE == "Mean"
) |>
pull(GROUP_ID)

amf_badm |>
filter(
GROUP_ID %in% groups,
VARIABLE == varnam
) |>
mutate(DATAVALUE = as.numeric(DATAVALUE)) |>
group_by(SITE_ID) |>
summarise(
var = mean(DATAVALUE)
) |>
rename(!!varnam := var)
}

get_values_badm_HEIGHTSENSOR <- function(df_badm){

# get group referring to variable information: height
groups <- df_flx_badm |>
filter(VARIABLE_GROUP == "GRP_VAR_INFO", VARIABLE == "VAR_INFO_HEIGHT") |>
pull(GROUP_ID)

# within that, get group referring to height of latent heat measurement
groups2 <- df_flx_badm |>
filter(
GROUP_ID %in% groups,
VARIABLE_GROUP == "GRP_VAR_INFO",
VARIABLE == "VAR_INFO_VARNAME",
DATAVALUE == "LE_F_MDS"
) |>
pull(GROUP_ID)

# extract value and average if multiple values are given per site
df_flx_badm |>
filter(
GROUP_ID %in% groups2,
VARIABLE == "VAR_INFO_HEIGHT"
) |>
mutate(DATAVALUE = as.numeric(DATAVALUE)) |>
group_by(SITE_ID) |>
summarise(
HEIGHTSENSOR = mean(DATAVALUE)
)
}


# Read collected meta data------------------------------------------------------
## Plumber ----------------------------------------------------------------------
plumber <- readRDS(here::here("data-raw/meta_data/plumber_meta-data.rds")) |>
Expand All @@ -34,7 +89,11 @@ plumber <- readRDS(here::here("data-raw/meta_data/plumber_meta-data.rds")) |>
product = "plumber"
)

## Ameriflux---------------------------------------------------------------------
## Ameriflux--------------------------------------------------------------------

# Additional site meta info from BADM file
df_amf_badm <- read_csv(here::here("data-raw/meta_data/AMF_AA-Flx_BIF_CCBY4_20240910.csv"))

ameriflux <- readRDS(here::here("data-raw/meta_data/amf_meta_data.rds")) |>
filter(
DATA_POLICY != "LEGACY"
Expand All @@ -50,10 +109,24 @@ ameriflux <- readRDS(here::here("data-raw/meta_data/amf_meta_data.rds")) |>
koeppen_code = CLIMATE_KOEPPEN
) |>
mutate(
canopy_height = NA,
reference_height = NA,
product = "ameriflux",
nyears = year_end - year_start + 1,
) |>
left_join(
get_values_badm(df_amf_badm, "HEIGHTC") |>
rename(
canopy_height = HEIGHTC,
sitename = SITE_ID
),
join_by("sitename")
) |>
left_join(
get_values_badm_HEIGHTSENSOR(df_amf_badm) |>
rename(
reference_height = HEIGHTSENSOR,
sitename = SITE_ID
),
join_by("sitename")
)

## ICOS Drought 2018 release ---------------------------------------------------
Expand Down Expand Up @@ -124,7 +197,8 @@ df <- plumber |>


# Complement missing meta information-------------------------------------------
## Get info from Falge et al https://doi.org/10.3334/ORNLDAAC/1530 -------------
## Get data from Falge et al -------------
# obtained from https://doi.org/10.3334/ORNLDAAC/1530
siteinfo_falge <- readr::read_csv(here::here("data-raw/meta_data/fluxnet_site_info_all_falge.csv")) |>
dplyr::select(-sitename) |>
dplyr::rename(
Expand Down Expand Up @@ -161,6 +235,42 @@ siteinfo_falge <- readr::read_csv(here::here("data-raw/meta_data/fluxnet_site_in
) |>
dplyr::select(-koeppen_climate)

## Get data from ICOS site list file -----------------------------------
siteinfo_icos <- readr::read_csv(
here::here(
"data-raw/meta_data/sites_list_icos.csv"
)
)

## Get data from Fluxnet2015 and their BADM -----------------------------------
siteinfo_fluxnet2015 <- readr::read_csv(
here::here(
"data-raw/meta_data/fluxnet2015_site_list.csv"
)
)

# Additional site meta info from FLUXNET BADM file
df_flx_badm <- read_csv(here::here("data-raw/meta_data/FLX_AA-Flx_BIF_DD_20200501.csv"))

siteinfo_fluxnet2015 <- siteinfo_fluxnet2015 |>
left_join(
get_values_badm(df_flx_badm, "HEIGHTC") |>
rename(
canopy_height = HEIGHTC,
id = SITE_ID
),
join_by("id")
) |>
left_join(
get_values_badm_HEIGHTSENSOR(df_flx_badm) |>
rename(
reference_height = HEIGHTSENSOR,
id = SITE_ID
),
join_by("id")
)

## Complement various variables with Falge et al. -----------------
df <- df |>
arrange(sitename) |>
left_join(
Expand All @@ -175,20 +285,8 @@ df <- df |>
koeppen_code = ifelse(is.na(koeppen_code), koeppen_code_falge, koeppen_code)
)

## Get missing data from ICOS and Fluxnet2015 site list files -----------------------------------
siteinfo_icos <- readr::read_csv(
here::here(
"data-raw/meta_data/sites_list_icos.csv"
)
)

siteinfo_fluxnet2015 <- readr::read_csv(
here::here(
"data-raw/meta_data/fluxnet2015_site_list.csv"
)
)

# Correct IGBP types
## Correct IGBP types -----------------
# Priority: ICOS, Fluxnet2015, plumber
# i.e, Fluxnet2015 overwrites plumber, then ICOS overwrites the reuslt
df <- df |>
Expand Down Expand Up @@ -286,6 +384,57 @@ df <- df |>
elv)
)

## Get C3/C4 classification ----------------------------------------------------
# ... and C4-% from data shared by Yanghui Kang (Trevor's group)
site_summary_YK = readr::read_csv("data-raw/meta_data/site_summary_yanghui_kang.csv")

df <- df |>
left_join(
site_summary_YK |>
dplyr::select(SITE_ID, c3c4 = `C3/C4`) |>
rename(sitename = SITE_ID),
by = join_by(sitename)
) |>
mutate(c3c4 = dplyr::case_match(
c3c4,
"unknown" ~ NA,
.default = c3c4
)
)

## Get vegetation and measurement height ---------------------------------------
df <- df |>

# complement with AmeriFlux meta info
left_join(
ameriflux |>
select(
sitename,
canopy_height_amf = canopy_height,
reference_height_amf = reference_height
),
join_by(sitename)
) |>
mutate(
ifelse(is.na(canopy_height), canopy_height_amf, canopy_height),
ifelse(is.na(reference_height), reference_height_amf, reference_height)
) |>

# complement with FLUXNET2015 meta info
left_join(
siteinfo_fluxnet2015 |>
select(
sitename = id,
canopy_height_flx = canopy_height,
reference_height_flx = reference_height
),
join_by(sitename)
) |>
mutate(
ifelse(is.na(canopy_height), canopy_height_flx, canopy_height),
ifelse(is.na(reference_height), reference_height_flx, reference_height)
)

# ## get IGBP from MODIS data-----------------------------------------------------
# # download IGBP class values (MODISTools)
# igbp <- apply(df, 1, function(x){
Expand Down Expand Up @@ -360,22 +509,7 @@ message("IGBP: found ",
print(igbp_by_source |>
dplyr::filter(IGBP_fdk != IGBP_eu | IGBP_fdk != IGBP_flx2015))

# Get C3/C4 classification and C4-% from data shared by Yanghui Kang (Trevor's group)
site_summary_YK = readr::read_csv("data-raw/meta_data/site_summary_yanghui_kang.csv")

df <- df |>
left_join(
site_summary_YK |>
dplyr::select(SITE_ID, c3c4 = `C3/C4`) |>
rename(sitename = SITE_ID),
by = join_by(sitename)
) |>
mutate(c3c4 = dplyr::case_match(
c3c4,
"unknown" ~ NA,
.default = c3c4
)
)

# save the data, retaining only key columns (note: valuable information also in
# other columns!)
Expand Down
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