CRS exercises moved to 06

ynsxx · May 26, 2018 · 5c29dec · 5c29dec
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diff --git a/05-geometry-operations.Rmd b/05-geometry-operations.Rmd
@@ -1191,43 +1191,6 @@ data(ndvi)
 ch = st_combine(random_points) %>% 
   st_convex_hull()
 ```
-<!-- CRS CONVERSION -->
-<!-- 1. vector reprojection exercise (e.g. modification of proj4) -->
-1. Create a new object called `nz_wgs` by transforming `nz` object into the WGS84 CRS.
-    - Create an object of class `crs` for both and use this to query their CRSs.
-    - With reference to the bounding box of each object, what units does each CRS use?
-    - Remove the CRS from `nz_wgs` and plot the result: what is wrong with this map of New Zealand and why?
-```{r, eval=FALSE, echo=FALSE}
-st_crs(nz)
-nz_wgs = st_transform(nz, 4326)
-nz_crs = st_crs(nz)
-nz_wgs_crs = st_crs(nz_wgs)
-nz_crs$epsg
-nz_wgs_crs$epsg
-st_bbox(nz)
-st_bbox(nz_wgs)
-nz_wgs_NULL_crs = st_set_crs(nz_wgs, NA)
-nz_27700 = st_transform(nz_wgs, 27700)
-par(mfrow = c(1, 3))
-plot(st_geometry(nz))
-plot(st_geometry(nz_wgs))
-plot(st_geometry(nz_wgs_NULL_crs))
-# answer: it is fatter in the East-West direction
-# because New Zealand is close to the South Pole and meridians converge there
-plot(st_geometry(nz_27700))
-par(mfrow = c(1, 1))
-```
-1. Transform the `world` dataset to the transverse Mercator projection (`"+proj=tmerc"`) and plot the result.
-What has changed and why?
-Try to transform it back into WGS 84 and plot the new object.
-Why does the new object differ from the original one?
-```{r, echo=FALSE, eval=FALSE}
-# see https://github.com/r-spatial/sf/issues/509
-world_tmerc = st_transform(world, "+proj=tmerc")
-plot(st_geometry(world_tmerc))
-world_4326 = st_transform(world_tmerc, 4326)
-plot(st_geometry(world_4326))
-```
 1. Generate and plot simplified versions of the `nz` dataset.
 Experiment with different values of `keep` (ranging from 0.5 to 0.00005) for `ms_simplify()` and `dTolerance` (from 100 to 100,000) `st_simplify()` .
     - At what value does the form of the result start to break-down for each method, making New Zealand unrecognizable?
@@ -1303,22 +1266,6 @@ ggplot(data = us_states_sfc_mirror_sf) +
   geom_text_repel(data = us_states_sfc_mirror_labels, mapping = aes(X, Y, label = name), size = 3, min.segment.length = 0) +
   theme_void() 
 ```
-1. Transform the continuous raster (`cat_raster`) into WGS 84 using the nearest neighbor interpolation method. 
-What has changed?
-How does it influence the results?
-```{r, echo=FALSE, eval=FALSE}
-con_raster = raster(system.file("raster/srtm.tif", package="spDataLarge"))
-con_raster_wgs84 = projectRaster(con_raster, crs = wgs84, method = "ngb")
-con_raster_wgs84
-```
-1. Transform the categorical raster (`cat_raster`) into WGS 84 using the bilinear interpolation method.
-What has changed?
-How does it influence the results?
-```{r, echo=FALSE, eval=FALSE}
-wgs84 = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
-cat_raster_wgs84 = projectRaster(cat_raster, crs = wgs84, method = "bilinear")
-cat_raster_wgs84
-```
 1. Subset the point in `p` that is contained within `x` *and* `y` (see section \@ref(clipping) and Figure \@ref(fig:venn-clip)).
     - Using base subsetting operators.
     - Using an intermediary object created with `st_intersection()`.

diff --git a/06-reproj.Rmd b/06-reproj.Rmd
@@ -579,3 +579,59 @@ Chapter 6 for this free online book is recommended reading --- see [rspatial.org
 <!-- note1: in most of the cases reproject vector, not raster-->
 <!-- note2: equal area projections are the best for raster calculations -->
 <!-- q: should we mentioned gdal_transform? -->
+
+## Exercises
+
+<!-- CRS CONVERSION -->
+<!-- 1. vector reprojection exercise (e.g. modification of proj4) -->
+1. Create a new object called `nz_wgs` by transforming `nz` object into the WGS84 CRS.
+    - Create an object of class `crs` for both and use this to query their CRSs.
+    - With reference to the bounding box of each object, what units does each CRS use?
+    - Remove the CRS from `nz_wgs` and plot the result: what is wrong with this map of New Zealand and why?
+```{r, eval=FALSE, echo=FALSE}
+st_crs(nz)
+nz_wgs = st_transform(nz, 4326)
+nz_crs = st_crs(nz)
+nz_wgs_crs = st_crs(nz_wgs)
+nz_crs$epsg
+nz_wgs_crs$epsg
+st_bbox(nz)
+st_bbox(nz_wgs)
+nz_wgs_NULL_crs = st_set_crs(nz_wgs, NA)
+nz_27700 = st_transform(nz_wgs, 27700)
+par(mfrow = c(1, 3))
+plot(st_geometry(nz))
+plot(st_geometry(nz_wgs))
+plot(st_geometry(nz_wgs_NULL_crs))
+# answer: it is fatter in the East-West direction
+# because New Zealand is close to the South Pole and meridians converge there
+plot(st_geometry(nz_27700))
+par(mfrow = c(1, 1))
+```
+1. Transform the `world` dataset to the transverse Mercator projection (`"+proj=tmerc"`) and plot the result.
+What has changed and why?
+Try to transform it back into WGS 84 and plot the new object.
+Why does the new object differ from the original one?
+```{r, echo=FALSE, eval=FALSE}
+# see https://github.com/r-spatial/sf/issues/509
+world_tmerc = st_transform(world, "+proj=tmerc")
+plot(st_geometry(world_tmerc))
+world_4326 = st_transform(world_tmerc, 4326)
+plot(st_geometry(world_4326))
+```
+1. Transform the continuous raster (`cat_raster`) into WGS 84 using the nearest neighbor interpolation method. 
+What has changed?
+How does it influence the results?
+```{r, echo=FALSE, eval=FALSE}
+con_raster = raster(system.file("raster/srtm.tif", package="spDataLarge"))
+con_raster_wgs84 = projectRaster(con_raster, crs = wgs84, method = "ngb")
+con_raster_wgs84
+```
+1. Transform the categorical raster (`cat_raster`) into WGS 84 using the bilinear interpolation method.
+What has changed?
+How does it influence the results?
+```{r, echo=FALSE, eval=FALSE}
+wgs84 = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
+cat_raster_wgs84 = projectRaster(cat_raster, crs = wgs84, method = "bilinear")
+cat_raster_wgs84
+```