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25_cov_expl_analysis_clorpt.Rmd
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25_cov_expl_analysis_clorpt.Rmd
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---
title: "Exploratory Analysis of Covariates"
subtitle: "Based on CLORPT soil forming factors"
author: "Anatol Helfenstein"
date: "2021-06-02 (updated)"
output:
html_document:
toc: yes
toc_float: yes
'': default
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(echo = FALSE)
options(width = 100) # sets width of R code output (not images)
```
```{r load required pkgs, include = FALSE}
# load packages
pkgs <- c("tidyverse", "raster", "rgdal", "sf", "rasterVis", "viridis", "foreach",
"RColorBrewer")
lapply(pkgs, library, character.only = TRUE)
```
## Complete List of Covariates
```{r list of covariates, echo = TRUE, warning = FALSE}
# locate rasters for stack
v_cov_names <- dir("out/data/covariates/final_stack",
pattern = "\\.grd$", recursive = TRUE)
# read in prepared rasters ready for model calibration
ls_r_cov <- foreach(cov = 1:length(v_cov_names)) %do%
raster(paste0("out/data/covariates/final_stack/", v_cov_names[[cov]]))
# read in prepared covariate stack
r_stack_cov <- stack(ls_r_cov)
# All covariates at 25m resolution excluding soil maps
dim(r_stack_cov)
# Names of all covariates
names(r_stack_cov)
```
## A glimpse of a few covariates according to soil formation factors
### Climate
```{r climate covariates, echo=TRUE, warning=FALSE, out.height='100%', out.width='100%'}
# Example of covariate belonging to clorpt factor "climate": average precipitation
r_stack_cov$precip_yearly_1981_2010_25m
hist(r_stack_cov$precip_yearly_1981_2010_25m)
levelplot(r_stack_cov$precip_yearly_1981_2010_25m,
margin = list(FUN = 'median'),
par.settings = list(axis.line = list(col = "transparent")),
scales = list(draw = FALSE),
main = "Precipitation: long term average (1981-2010)",
col.regions = viridis(n = 100))
plot(r_stack_cov$precip_yearly_1981_2010_25m,
main = "Precipitation: long term average (1981-2010)",
col = bpy.colors(),
axes = FALSE,
box = FALSE)
# Example of covariate belonging to clorpt factor "climate": average max temperature
r_stack_cov$temp_yearlymax_1981_2010_25m
hist(r_stack_cov$temp_yearlymax_1981_2010_25m)
levelplot(r_stack_cov$temp_yearlymax_1981_2010_25m,
margin = list(FUN = 'median'),
main = "Temperature: average yearly max temperature (1981-2010)")
plot(r_stack_cov$temp_yearlymax_1981_2010_25m,
col = heat.colors(100, rev = TRUE),
main = "Temperature: average yearly max temperature (1981-2010)",
axes = FALSE,
box = FALSE)
```
### Organisms (mostly vegetation and anthropogenic influence)
```{r organism covariates, echo = TRUE, warning = FALSE}
# Example of covariate belonging to clorpt factor "organism": Tree Height
r_stack_cov$boomhoogte_2017_25m
hist(r_stack_cov$boomhoogte_2017_25m)
plot(r_stack_cov$boomhoogte_2017_25m,
main = "Tree Heights in 2017",
axes = FALSE,
box = FALSE,
col = viridis(n = 100))
# Example of covariate belonging to clorpt factor "organism": Landuse (LGN8)
r_stack_cov$lgn8_25m
r_stack_cov$lgn8_25m@data@attributes[[1]]
n_classes <- nrow(levels(r_stack_cov$lgn8_25m)[[1]])
# if > 12 classes, create an assortment of categorical colors
qual_col_pals = brewer.pal.info[brewer.pal.info$category == 'qual',]
v_colors = unlist(mapply(brewer.pal,
qual_col_pals$maxcolors,
rownames(qual_col_pals)))
levelplot(r_stack_cov$lgn8_25m,
att = "description",
main = "Land Use (LGN8)",
par.settings = list(axis.line = list(col = "transparent")),
scales = list(draw = FALSE),
col.regions = v_colors[1:n_classes])
```
## Relief
```{r relief covariates, echo = TRUE, warning = FALSE}
# Example of covariate belonging to clorpt factor "relief": DEM (AHN2)
r_stack_cov$ahn2_25m
hist(r_stack_cov$ahn2_25m)
levelplot(r_stack_cov$ahn2_25m,
margin = list(FUN = 'median'),
main = "DEM (AHN2)")
# Examples of covariate belonging to clorpt factor "relief": some DEM derivatives
r_stack_DEMderiv <- stack(r_stack_cov$ahn2_25m_slope, r_stack_cov$ahn2_25m_twi,
r_stack_cov$ahn2_25m_vbf, r_stack_cov$ahn2_25m_vdepth)
plot(r_stack_DEMderiv, col = rev(magma(10, alpha = 0.8)),
axes = FALSE,
box = FALSE)
```
## Parent Material (Geology/Lithology/Geomorphology)
```{r parent material covariates, echo = TRUE, warning = FALSE}
# Example of covariate belonging to clorpt factor "parent material": geomorphological map 2019
r_stack_cov$geomorph2019_25m
r_stack_cov$geomorph2019_25m@data@attributes[[1]]
n_classes <- nrow(levels(r_stack_cov$geomorph2019_25m)[[1]])
levelplot(r_stack_cov$geomorph2019_25m,
att = "description",
main = "Geomorphological Map 2019",
par.settings = list(axis.line = list(col = "transparent")),
scales = list(draw = FALSE),
col.regions = sample(v_colors, n_classes, replace = TRUE))
# Example of covariate belonging to clorpt factor "parent material": geomorphological genesis classes
r_stack_cov$geomorph2019_genese_25m
r_stack_cov$geomorph2019_genese_25m@data@attributes[[1]]
n_classes <- nrow(levels(r_stack_cov$geomorph2019_genese_25m)[[1]])
levelplot(r_stack_cov$geomorph2019_genese_25m,
att = "description",
main = "Geomorphological Genesis Classes (2019 Map)",
par.settings = list(axis.line = list(col = "transparent")),
scales = list(draw = FALSE),
col.regions = RColorBrewer::brewer.pal(n = n_classes, name = "Paired"))
```
### Time (?)
Time is incorporated in time series of several other covariates, mostly belonging to soil formation factor "organism". E.g. land use maps, vegetation maps, satellite derived data, etc.
- Time Series of Landuse Maps:
```{r time covariates, echo = TRUE, warning = FALSE}
# Example of time-varying covariate belonging to clorpt factor "organism": Landuse 1900 (HGN)
r_stack_cov$hgn_1900_filled_25m
r_stack_cov$hgn_1900_filled_25m@data@attributes[[1]]
n_classes <- nrow(levels(r_stack_cov$hgn_1900_filled_25m)[[1]])
levelplot(r_stack_cov$hgn_1900_filled_25m,
att = "description",
main = "Land Use in 1900",
par.settings = list(axis.line = list(col = "transparent")),
scales = list(draw = FALSE),
col.regions = RColorBrewer::brewer.pal(n = n_classes, name = "Paired"))
```