Rendered 05 Environment into html

code/04_buildHeader.Rmd

@@ -185,6 +185,16 @@ header <- header %>%
   mutate(`Relevé area (m²)`=ifelse( (Dataset=="Patagonia" & is.na(`Relevé area (m²)`)), 
                                     -900, `Relevé area (m²)`))
 ```
+There are 518 plots from the dataset Germany_gvrd	(EU-DE-014) having a location uncertainty equal to 2,147,483 km (!). These plots have a location reported. Replace with a more likely estimate (20 km)
+
+```{r}
+header <- header %>% 
+  mutate(`Location uncertainty (m)`=replace(`Location uncertainty (m)`, 
+                                            list=`Location uncertainty (m)`==2147483647, 
+                                            values=20000))
+```
+
+
 
 ## 2 Formations
 Fill out the columns `Forest:Sparse.vegetation` with NAs, where necessary. Create columns `is.forest` and `is.non.forest` using script developed for sPlot 2.1  

code/05_ExtractEnvironment.Rmd

@@ -78,6 +78,7 @@ header.shp <- SpatialPointsDataFrame(coords= header.shp %>%
                                                loc.uncert=header.shp$`Location uncertainty (m)`, 
                                                `GIVD ID`=header.shp$`GIVD ID`))
 ```
+
 ```{r, echo=F}
 header.shp <- readOGR(dsn="../_derived", layer="header.shp")
 colnames(header.shp@data) <- c("PlotObservationID", "loc.uncert", "GIVD ID")
@@ -169,9 +170,9 @@ knitr::kable(tmp.sum,
 ```
 
 ```{r, echo=F}
-tmp.sum <- get.summary(chelsa.sd.out)
+tmp.sd.sum <- get.summary(chelsa.sd.out)
 
-knitr::kable(tmp.sum, 
+knitr::kable(tmp.sd.sum, 
   caption="Summary statistics for chelsa s.d. statistics") %>%
     kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), 
                   full_width = F, position = "center")