Spatial data coverage
Pasqualina Vonlanthen & Jens Daniel Müller
22 October, 2021
Last updated: 2021-10-22
Checks: 7 0
Knit directory: bgc_argo_r_argodata/
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Task
Map the location of oxygen, pH, and nitrate observations recorded by BGC-Argo floats
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──✓ ggplot2 3.3.5 ✓ purrr 0.3.4
✓ tibble 3.1.3 ✓ dplyr 1.0.5
✓ tidyr 1.1.3 ✓ stringr 1.4.0
✓ readr 1.4.0 ✓ forcats 0.5.0── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()library(argodata)
library(ggplot2)
library(lubridate)
Attaching package: 'lubridate'The following objects are masked from 'package:base':
date, intersect, setdiff, unionlibrary(sf)Linking to GEOS 3.6.2, GDAL 3.0.4, PROJ 7.0.0library(rnaturalearth)
library(rnaturalearthdata)
# load in coastline data (uses sf and rnaturalearthdata packages)
world = ne_coastline(scale = 'medium', returnclass = 'sf')Load data
Read the files created in loading_data.html:
path_argo_preprocessed <- paste0(path_argo, "/preprocessed_bgc_data")
bgc_subset <-
read_rds(file = paste0(path_argo_preprocessed, "/bgc_subset.rds"))
bgc_metadata <-
read_rds(file = paste0(path_argo_preprocessed, "/bgc_metadata.rds"))
bgc_data <-
read_rds(file = paste0(path_argo_preprocessed, "/bgc_data.rds"))
bgc_merge <-
read_rds(file = paste0(path_argo_preprocessed, "/bgc_merge.rds"))Spatial data coverage
Count the number of profiles per year
bgc_profile_counts_year <- bgc_metadata %>%
select(platform_number, cycle_number, date, longitude, latitude,
profile_doxy_qc, profile_ph_in_situ_total_qc, profile_nitrate_qc) %>%
pivot_longer(profile_doxy_qc:profile_nitrate_qc,
names_to = "parameter",
values_to = "profile_flag",
names_prefix = "profile_") %>%
mutate(year = year(date),
latitude = round(latitude, digits = 0),
longitude = round(longitude, digits = 0)) %>%
filter(!is.na(profile_flag),
profile_flag != "") %>%
count(latitude, longitude, year, parameter) # count the number of profiles per year in each lon/lat grid for each parameter
bgc_profile_counts_flag <- bgc_metadata %>%
select(platform_number, cycle_number, date, longitude, latitude,
profile_doxy_qc, profile_ph_in_situ_total_qc, profile_nitrate_qc) %>%
pivot_longer(profile_doxy_qc:profile_nitrate_qc,
names_to = "parameter",
values_to = "profile_flag",
names_prefix = "profile_") %>%
mutate(year = year(date),
latitude = round(latitude, digits = 0),
longitude = round(longitude, digits = 0)) %>%
filter(!is.na(profile_flag),
profile_flag != "") %>%
count(latitude, longitude, parameter, profile_flag) # count the number of profiles for each profile QC flag in each lon/lat area and for each parameter Map the profile locations
Map of profile locations for each parameter, per year
bgc_profile_counts_year %>%
ggplot() +
geom_sf(data = ne_countries(returnclass = "sf"),
fill = "gray90",
color = NA) +
geom_sf(data = ne_coastline(returnclass = "sf")) +
geom_tile(aes(x = longitude, y = latitude, fill = n)) +
scale_fill_gradient(low="blue", high="red",
trans = "log10") +
theme_bw() +
facet_grid(year ~ parameter)bgc_profile_counts_year %>%
group_split(parameter) %>%
map(
~ ggplot() +
geom_sf(data = ne_countries(returnclass = "sf"),
fill = "gray90",
color = NA) +
geom_sf(data = ne_coastline(returnclass = "sf")) +
geom_tile(data = .x, aes(x = longitude, y = latitude, fill = n)) +
scale_fill_gradient(low="blue", high="red",
trans = "log10") +
theme_bw() +
labs(x = 'longitude', y = 'latitude', fill = 'number of profiles',
title = paste('Parameter:', unique(.x$parameter)))+
facet_grid(. ~ year)
)[[1]]Warning: Removed 3 rows containing missing values (geom_tile).
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[2]]Warning: Removed 1 rows containing missing values (geom_tile).
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[3]]
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
Map the profile locations for each profile QC flag of each parameter
bgc_profile_counts_flag %>%
ggplot() +
geom_sf(data = ne_countries(returnclass = "sf"),
fill = "gray90",
color = NA) +
geom_sf(data = ne_coastline(returnclass = "sf")) +
geom_tile(aes(x = longitude, y = latitude, fill = n)) +
scale_fill_gradient(low="blue", high="red",
trans = "log10") +
theme_bw() +
facet_grid(profile_flag ~ parameter)# create a separate plot for each QC flag (instead of multiple panels in one plot)
bgc_profile_counts_flag %>%
group_split(profile_flag) %>%
map(
~ ggplot() +
geom_sf(data = ne_countries(returnclass = "sf"),
fill = "gray90",
color = NA) +
geom_sf(data = ne_coastline(returnclass = "sf")) +
geom_tile(data = .x, aes(x = longitude, y = latitude, fill = n)) +
scale_fill_gradient(low="blue", high="red",
trans = "log10") +
theme_bw() +
labs(x = 'longitude', y = 'latitude', fill = 'number of profiles',
title = paste('Profile QC flag', unique(.x$profile_flag)))+
facet_grid(. ~ parameter)
)[[1]]Warning: Removed 2 rows containing missing values (geom_tile).
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[2]]Warning: Removed 1 rows containing missing values (geom_tile).
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[3]]
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[4]]
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[5]]
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
[[6]]Warning: Removed 2 rows containing missing values (geom_tile).
| Version | Author | Date |
|---|---|---|
| 701fffa | pasqualina-vonlanthendinenna | 2021-10-20 |
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2
Matrix products: default
BLAS: /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] rnaturalearthdata_0.1.0 rnaturalearth_0.1.0 sf_1.0-2
[4] lubridate_1.7.9 argodata_0.0.0.9000 forcats_0.5.0
[7] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4
[10] readr_1.4.0 tidyr_1.1.3 tibble_3.1.3
[13] ggplot2_3.3.5 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.2 sass_0.4.0 jsonlite_1.7.2 modelr_0.1.8
[5] bslib_0.2.5.1 assertthat_0.2.1 highr_0.8 sp_1.4-4
[9] blob_1.2.1 cellranger_1.1.0 yaml_2.2.1 pillar_1.6.2
[13] backports_1.1.10 lattice_0.20-41 glue_1.4.2 digest_0.6.27
[17] promises_1.2.0.1 rvest_0.3.6 colorspace_2.0-2 htmltools_0.5.1.1
[21] httpuv_1.6.2 pkgconfig_2.0.3 broom_0.7.9 haven_2.3.1
[25] s2_1.0.6 scales_1.1.1 whisker_0.4 later_1.3.0
[29] git2r_0.27.1 proxy_0.4-26 generics_0.1.0 farver_2.1.0
[33] ellipsis_0.3.2 withr_2.4.2 cli_3.0.1 magrittr_2.0.1
[37] crayon_1.4.1 readxl_1.3.1 evaluate_0.14 fs_1.5.0
[41] fansi_0.5.0 xml2_1.3.2 class_7.3-17 tools_4.0.3
[45] hms_0.5.3 lifecycle_1.0.0 munsell_0.5.0 reprex_0.3.0
[49] compiler_4.0.3 jquerylib_0.1.4 e1071_1.7-8 RNetCDF_2.4-2
[53] rlang_0.4.11 classInt_0.4-3 units_0.7-2 grid_4.0.3
[57] rstudioapi_0.13 rmarkdown_2.10 wk_0.5.0 gtable_0.3.0
[61] DBI_1.1.1 R6_2.5.1 knitr_1.33 rgeos_0.5-5
[65] utf8_1.2.2 rprojroot_2.0.2 KernSmooth_2.23-17 stringi_1.5.3
[69] Rcpp_1.0.7 vctrs_0.3.8 dbplyr_1.4.4 tidyselect_1.1.0
[73] xfun_0.25