totholz.qmd erstellt, daten in struk_tot mit aktuellen zahlen geupdated und ergänzt

lfe_bwi/R_bwi/Interpretationsworkshop-MLUK.qmd

@@ -342,30 +342,4 @@ ggplot((ver_vor_long %>% filter(Land == 'Brandenburg') %>% filter(Ba_Gruppen !=
 scale_y_continuous(labels = scales::comma_format(big.mark = ".", decimal.mark = ","),
                      #breaks = seq(0, 1100000, by = 100000)
                    )
-```
-
+```
\ No newline at end of file
-
-## Quarto
-
-Quarto enables you to weave together content and executable code into a
-finished document. To learn more about Quarto see <https://quarto.org>.
-
-## Running Code
-
-When you click the **Render** button a document will be generated that
-includes both content and the output of embedded code. You can embed
-code like this:
-
-```{r}
-1 + 1
-```
-
-You can add options to executable code like this
-
-```{r}
-#| echo: false
-2 * 2
-```
-
-The `echo: false` option disables the printing of code (only output is
-displayed).

lfe_bwi/R_bwi/totholz.qmd

+---
+title: "Totholz"
+subtitle: "Vorbereitung WS 08.07.24"
+institution: "Landeskompetenzzentrum Forst Eberswalde"
+author: "Torsten Wiebke und Sebastian Schmidt"
+date: "`r Sys.Date()`"
+bibliography: ../../LaTeX/bib/bibl.bib
+csl: ../../LaTeX/bib/iso690-author-date-de.csl
+editor: visual
+format: 
+  pdf:
+    documentclass: scrreprt #Komascript reprt
+    pdf-engine: pdflatex
+    keep-tex: true 
+    # wenn nur PDF: in der Console: quarto::quarto_render("your_document.qmd", output_format = "pdf")
+    # quarto::quarto_render("bwi_interpretationsworkshop.qmd", output_format = "revealjs")
+  revealjs:
+    navigation-mode: vertical # ermölicht horizontale und vertikale Gliederung
+    slide-level: 5 # gibt Überschriftenebene an bis zu der eine eigene Folie erzeugt werden soll 
+    incremental: false 
+    slide-number: true
+prefer-html: true
+---
+
+::: content-hidden
+# Libraries und Daten
+
+## Libraries laden
+
+```{r librarys, include=FALSE}
+library(readxl)
+library(ggplot2)
+library(stats)
+library(corrplot)
+library(tidyverse)
+library(feather) # um Daten zu speichern
+library(tidyr)
+library(scales)
+library(RColorBrewer)  # Für eine breite Palette von Farben
+library(patchwork) # um Diagramme nebeneinander darzustellen
+library(knitr)
+library(kableExtra)
+library(xtable) # für LaTeX-Tabellen
+library(quarto)
+```
+
+## Farben festlegen
+
+```{r Farben, include=FALSE}
+# Benutzerdefinierte Farben für die Layer
+ba_farben <- c("Eiche (Quercus)" = "#ffffcc",
+               "Eiche" = "#ffffcc",
+               "Eichen-Typ"  = "#ffffcc",
+               "Buche (Fagus)" = "#ccfe64",
+               "Buche" = "#ccfe64",
+               "Buchen-Typ" = "#ccfe64",
+               "Esche (Fraxinus)" = "#fed976",
+               "Eschen-Typ" = "#fed976",
+               "Ahorn (Acer)" = "#fd8d3c",
+               "sonst. Lb hoher Lebensdauer" = "#fc4e2a",
+               "andere Lb hoher Lebensdauer" = "#fc4e2a",
+               "Typ sonst. Laubbäume mit hoher Lebensdauer" = "#fc4e2a", 
+               "Erle (Alnus)" = "#8c96c6",
+               "Erlen-Typ" = "#8c96c6",
+               "Birke (Betula)" = "#e0ecf4",
+               "Birken-Typ" = "#e0ecf4",
+               "sonst. Lb niedriger Lebensdauer" = "#88419d",
+               "andere Lb niedriger Lebensdauer" = "#88419d",
+               "Typ sonst. Laubbäume mit niedriger Lebensdauer"= "#88419d",
+               "alle Laubbäume" = "#ae017e",
+               "Fichte (Picea)" = "#7f7f7f",
+               "Fichte" = "#7f7f7f",
+               "Fichten-Typ"  = "#7f7f7f",
+               "Tanne (Abies)" = "#a6bddb",
+               "Tanne" = "#a6bddb",
+               "Tannen-Typ"  = "#a6bddb",
+               "Douglasie (Pseudotsuga)" = "#67a9cf",
+               "Douglasie" = "#67a9cf",
+               "Douglasien-Typ" = "#67a9cf",
+               "Kiefer (Pinus)" = "#e4ce4c", 
+               "Kiefer" = "#e4ce4c",
+               "Kiefern-Typ"  = "#e4ce4c",
+               "Lärche (Larix)" = "#f4a6a4",
+               "Lärche" = "#f4a6a4",
+               "Lärchen-Typ" = "#f4a6a4",
+               "alle Nadelbäume" = "#02818a",
+               "Typ mit mehreren gleichrangigen Baumarten" ="#006d2c",
+               "Lücke" = "#dcdcdc",
+               "Blöße" = "#edf8fb",
+               "Nichtholzboden" = "#b2e2e2",
+               "Holzboden" = "#66c2a4",
+               "bestockter Holzboden" = "#2ca25f",
+               "Wald" = "#006d2c",
+               "stehend, ganzer Baum" = "goldenrod1",
+               "stehend, Bruchstück (Höhe ab 130 cm)" = "goldenrod2",
+               "stehend" = "goldenrod3",
+               "liegend, ganzer Baum mit Wurzelanlauf" = "darkseagreen1",
+               "liegend, Stammstück mit Wurzelanlauf" = "darkseagreen2",
+               "liegend, Teilstück ohne Wurzelanlauf" = "darkseagreen3",
+               "liegend" = "darkseagreen4",                           
+               "Wurzelstock (Höhe < 130 cm)" = "#88419d",
+               "Abfuhrrest (aufgeschichtet)" = "#ae017e",
+               "alle Totholztypen" = "#67a9cf"  
+)
+```
+
+## [**Datenimport**]
+
+### Totholzzustand {.hidden .unnumbered .unlisted}
+
+```{r imp_struktur_tot, include=FALSE}
+tot_sheet_names <- excel_sheets("data/struktur_tot.xlsx")
+tot <- lapply(tot_sheet_names, function(sheet) {
+  read_excel("data/struktur_tot.xlsx", sheet = sheet, skip = 5, na = c("NaN"))
+})
+names(tot) <- tot_sheet_names
+```
+
+## Auswertung
+### Vergleich Totholzvorrat 13-22
+```{r totvorrat13_22, include=FALSE}
+# Daten Vorbereiten
+# Totholzvorrat BB Vergleich 13-22
+
+totvorrat_long_13_22 <- tot$bb_tot_typ_13_22 %>% 
+  filter(Eigentumsart == "alle Eigentumsarten 2013"|Eigentumsart == "alle Eigentumsarten 2022") %>%
+  pivot_longer(cols = c("alle Totholztypen"), 
+               names_to  = "Totholztyp", 
+               values_to = "Totholzvorrat")
+```
+
+```{r totvorrat13_22_bar, echo=FALSE}
+# Bar Totholzvorrat BB Vergleich 13-22
+
+# Plot erstellen als Säulendiagramm für 2013 & 2022
+totvorrat_13_22 <- ggplot(totvorrat_long_13_22, aes(x = Eigentumsart, y = Totholzvorrat)) +
+  geom_bar(stat = "identity", fill = "dodgerblue3", show.legend = FALSE) +  # Set custom color
+  geom_text(aes(label = paste0(round(Totholzvorrat, 1), " m³/ha")), 
+            vjust = 0.5, hjust = 0.5, color = "white", size = 4.5, 
+            position = position_stack(vjust = 0.5), fontface = "bold") +  # Center the labels
+  labs(x = "Inventur",
+       y = "Totholzvorrat [m³/ha]") +
+  ggtitle("Vergleich der Totholzvorräte in m³/ha in Brandenburg \n LWI 2013 / BWI 2022") +
+  theme(plot.title = element_text(hjust = 0.5)) +
+  theme(axis.text.x = element_text(angle = 45, hjust = 1),
+        plot.title = element_text(margin = margin(b = 20)),
+        plot.title.position = "plot",
+        legend.position = "none") +
+  scale_x_discrete(labels = c("alle Eigentumsarten 2013" = "LWI 2013", "alle Eigentumsarten 2022" = "BWI 2022")) +
+  scale_y_continuous(labels = scales::comma_format(big.mark = ".", decimal.mark = ","),
+                     breaks = seq(0, 18, by = 2),  # Adjust breaks as needed
+                     limits = c(0, 18))  # Set y-axis limit
+
+totvorrat_13_22
+```
+Der Totholzvorrat in Brandenburg hat von der Landeswaldinventur 2013 zur Bundeswaldinventur 2022 um 6,1 m³/ha zugenommen.
+
+In der Veränderungsrechung (welche nur Punkte im Veränderungsnetz mit einbezieht) liegt der Anstieg bei 6,4 m³/ha
+
+### Vergleich Totholzvorrat nach Laub-/Nadel-/Eichenholz
+```{r totvorrat13_22_bag, include=FALSE}
+# Daten Vorbereiten
+# Totholzvorrat Baumartengruppe BB Vergleich 13-22
+
+#str(tot$bb_tot_art_13_22)
+
+totvorrat_bag_long_13_22 <- tot$bb_tot_art_13_22 %>%
+  filter(Eigentumsart == "alle Eigentumsarten 2013" | Eigentumsart == "alle Eigentumsarten 2022") %>%
+  pivot_longer(cols = -c(Jahr,Eigentumsart, Einheit,"alle Baumartengruppen von Totholz"),
+               names_to = "Baumartengruppe",
+               values_to = "Totholzvorrat")
+```
+
+```{r totvorrat13_22_bag_stackbar, echo=FALSE}
+# Stacked Bar Totholzvorrat Baumartengruppe BB Vergleich 13-22
+
+#Prozentwert ausrechnen
+totvorrat_bag_long_13_22 <- totvorrat_bag_long_13_22 %>%
+  arrange(Totholzvorrat) %>%
+  group_by(Eigentumsart) %>%
+  mutate(Percentage = 100 * Totholzvorrat / sum(Totholzvorrat)) %>%
+  ungroup()
+
+#sortieren nach Menge
+totvorrat_bag_long_13_22 <- arrange(totvorrat_bag_long_13_22, Totholzvorrat)
+
+# Custom colors
+custom_colors <- c("dodgerblue3", "forestgreen", "firebrick")
+
+# Plot erstellen als gestapeltes Säulendiagramm für 2013 & 2022
+totvorrat_bag_13_22 <- ggplot(totvorrat_bag_long_13_22, aes(x = Eigentumsart, y = Totholzvorrat, fill = reorder(Baumartengruppe, Totholzvorrat, FUN = sum))) +
+  geom_bar(stat = "identity", position = "stack") +
+  geom_text(aes(label = paste0(round(Totholzvorrat, 1), " m³/ha (", round(Percentage, 1), "%)")), 
+            vjust = 0.5, hjust = 0.5, color = "white", size = 3.5, 
+            position = position_stack(vjust = 0.5), fontface = "bold") +
+  labs(x = "Inventur",
+       y = "Totholzvorrat [m³/ha]") +
+  ggtitle("Vergleich der Totholzvorräte in m³/ha nach Baumartengruppe in Brandenburg \n LWI 2013 / BWI 2022") +
+  theme(plot.title = element_text(hjust = 0.5)) +
+  theme(axis.text.x = element_text(angle = 45, hjust = 1),
+        plot.title = element_text(margin = margin(b = 20)),
+        plot.title.position = "plot") +
+        #legend.position = "none") +
+  scale_x_discrete(labels = c("alle Eigentumsarten 2013" = "LWI 2013", "alle Eigentumsarten 2022" = "BWI 2022")) +
+  guides(fill = guide_legend(title = "Baumartengruppe", title.position = "top")) +
+  scale_fill_manual(values = custom_colors) +
+  scale_y_continuous(labels = scales::comma_format(big.mark = ".", decimal.mark = ","),
+                     breaks = seq(0, 18, by = 2),  # Adjust breaks as needed
+                     limits = c(0, 18))  # Set y-axis limit
+
+totvorrat_bag_13_22
+```
+
+
+### Vergleich Totholzvorrat und Totholztyp 12-22
+```{r totvorrat12_22_typ_stackbar, echo=FALSE}
+# Stacked bar Vergleich Totholzvorrat 12-22
+
+totvorrat_typ_long_2012_2022 <- arrange(totvorrat_typ_long_2012_2022, Totholzvorrat)
+
+# Plot erstellen als gestapeltes Säulendiagramm - geordnet mit Flächenangaben - für 2012 & 2022
+totvorrat12_22_typ_stackbar <- ggplot(totvorrat_typ_long_2012_2022, aes(x = Eigentumsart, y = Totholzvorrat, fill = reorder(Totholztyp, Totholzvorrat, FUN = sum))) +
+  geom_bar(stat = "identity", position = "stack") +
+ # scale_fill_manual() +  # Farben manuell festlegen +
+  labs(x = "Totholztyp",
+       y = "Totholzvorrat [m³/ha]") +
+  ggtitle("Vergleich der Totholzvorräte nach Totholztyp in m³/ha\n über alle Eigentumsarten in Brandenburg - BWI2012 / BWI2022") +
+  theme(plot.title = element_text(hjust = 0.5)) +
+  theme(axis.text.x = element_text(angle = 45, hjust = 1),
+        plot.title = element_text(margin = margin(b = 20)),
+        plot.title.position = "plot") +
+  guides(fill = guide_legend(title = "Totholztyp", title.position = "top")) +
+  scale_y_continuous(labels = scales::comma_format(big.mark = ".", decimal.mark = ","),
+                     breaks = seq(0, sum(totvorrat_typ_long_2012_2022$Totholzvorrat), by = 2))  
+
+totvorrat12_22_typ_stackbar
+```
\ No newline at end of file