formatting

Author: dimimarkou

vignettes/articles/2.4-ElevationData.Rmd.orig

@@ -423,7 +423,7 @@ There does not appear to be a clear relationship between species diversity and e
 
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-Congratulations! You completed **Chapter 4 - Digital Elevation Data**. In this chapter, you successfully 1) processed raster DTM's 2) performed cropping and masking procedures and 3) extracted elevation data over vector data points. In [Chapter 5](05-LandcoverData.Rmd), you will explore how to extract unique pixel values from landcover data and link it to NatureCounts data.
+**Congratulations!** You completed **Chapter 4 - Digital Elevation Data**. In this chapter, you successfully 1) processed raster DTM's 2) performed cropping and masking procedures and 3) extracted elevation data over vector data points. In [Chapter 5](05-LandcoverData.Rmd), you will explore how to extract unique pixel values from landcover data and link it to NatureCounts data.
 
 Below are some additional resources you may find useful to further your understanding of LiDAR data.
 

vignettes/articles/2.6-SatelliteImagery.Rmd.orig

@@ -71,8 +71,6 @@ These interactions also mean that we can represent multispectral imagery through
 Specify the path to your folder containing the satellite images in the code chunk below. Each image represents a distinct band. If you downloaded the data by following [Section 6.3](#6.3CopernicusDataDownload), look for the folder labeled S2A_MSIL2A. Copy the file path to S2A_MSIL2A... \> GRANULE \> L2A... \> IMG_DATA \> R10m which contains the satellite images we will use here.
 
 ```{r, message = FALSE, warning = FALSE}
-getwd()
-
 bands <- list.files(path = here::here("misc/data/R10m"), 
                     pattern = "\\.jp2$", full.names = TRUE)
 

vignettes/articles/2.7-SummaryTools.Rmd.orig

@@ -384,4 +384,4 @@ As edge density increase, the probability of a Golden Crown Kinglet increase sli
 
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-Congratulations! You completed Chapter 7 - Summary Tools. In this chapter, you successfully summarized and visualized environmental data, biodiversity counts, and presence/absence data using various plotting techniques. If you'd like to explore some Additional Resources based on previous Spatial Data chapters, the [Raster Tools](Additional%20Resources%20-%20Raster%20Tools.Rmd) article is also available.
+**Congratulations!** You completed **Chapter 7 - Summary Tools**. In this chapter, you successfully summarized and visualized environmental data, biodiversity counts, and presence/absence data using various plotting techniques. If you'd like to explore some Additional Resources based on previous Spatial Data chapters, the [Raster Tools](Additional%20Resources%20-%20Raster%20Tools.Rmd) article is also available.

vignettes/articles/3.2-AuxiliaryTables.Rmd.orig

@@ -249,4 +249,4 @@ ggplot() +
 
 ```
 
-\*\*Congratulations!\*\* You completed \*\*Chapter 2: Auxiliary Tables\*\*. Here, you accessed NatureCounts auxiliary tables using the `nc_query_tables` function. You also created basic data summaries and maps using rNest and ecodistricts data.
+**Congratulations!** You completed \*\*Chapter 2: Auxiliary Tables\*\*. Here, you accessed NatureCounts auxiliary tables using the `nc_query_tables` function. You also created basic data summaries and maps using rNest and ecodistricts data.