# INBO CODING CLUB

24 November 2022

Welcome!

## Share your code snippet

If you want to share your code snippet, copy paste your snippet within a section of three backticks (```):

As an **example**:

library(tidyverse)

(*you can copy paste this example and add your code further down*)

## Yellow sticky notes

No yellow sticky notes online. Put your name + " | " and add a "*" each time you solve a challenge (see below example where Damiano solved all three challenges).

## Participants

Name | Challenges
--- | ---
Damiano Oldoni | ***
Dirk Maes | ***
Wim Kuypers |
Natalie Beenaerts |
Teun Everts |
Raïsa Carmen | *
Wouter Depaepe | *

## Challenge 1

Solution Raïsa
## CHALLENGE 1
lu_nara_2016 <- terra::rast(x = "./data/20221124/20221124_lu_nara_2016_100m.tif")

#2.
names(lu_nara_2016)
crs(lu_nara_2016)
ext(lu_nara_2016)
res(lu_nara_2016)
minmax(lu_nara_2016)

#3.
plot(lu_nara_2016)
# 4. Read `20211125_lu_nara_legend.csv` (code is provided!) so that you can set
# the color table associated with `lu_nara_2016`.
legend <- read.delim(
  "./data/20221124/20221124_lu_nara_legend.txt",
  sep = ",")
legend

plot(lu_nara_2016,
     type = "classes",
     col = legend$color,
     levels = legend$land_use)

#' 5. Calculate the most and least occurring land use category in each of the
#' Natura2000 protected areas (read these areas using the provided code). Tip: use exactextractr::exact_extract() and find
#' the right [summary operations](https://isciences.gitlab.io/exactextractr/#summary-operations)
natura2000 <- st_read("./data/20211125/20211125_protected_areas_Lambert72.gpkg",
                      layer = "ps_hbtrl")
# make dataframes with the name of the Natura2000 area, the majority/minority id and name                      
majority <- natura2000 %>% 
  st_drop_geometry() %>%
  dplyr::select(NAAM) %>%
  mutate(majority = exact_extract(lu_nara_2016, natura2000,
              fun = "majority")) %>%
  left_join(dplyr::select(legend, id, land_use), by = c("majority" = "id"))
minority <- natura2000 %>% 
  st_drop_geometry() %>%
  dplyr::select(NAAM) %>%
  mutate(minority = exact_extract(lu_nara_2016, natura2000,
                                  fun = "minority")) %>%
  left_join(dplyr::select(legend, id, land_use), by = c("minority" = "id"))

## Challenge 2

## INTERMEZZO

## Challenge 3

## Bonus challenge