User guide fixes (#665)

* DOC: Fix avalanche risk link

* DOC: Typo

* FIX: Path in Zonal user guide

- Fix coordinates to be of the same range as terrain
- Clearer visualization

* Scale coordinates, strengthen line in visulizaion

Author: DahnJ

examples/user_guide/1_Surface.ipynb

@@ -157,7 +157,7 @@
     "In geography, *slope* is the amount of change in elevation for an area in a terrain relative to its surroundings.\n",
     "\n",
     "Xarray-spatial's slope function returns the slope at each cell in degrees.\n",
-    "Because Xarray-spatial is integrated with Xarray and Numpy, we can apply standard Numpy filters. For example, we can highlight only slopes in the [avalanche risk](http://wenatcheeoutdoors.org/2016/04/07/avalanche-abcs-for-snowshoers/) range of 25 - 50 degrees. (Note the use of risky.data since these are DataArrays).\n",
+    "Because Xarray-spatial is integrated with Xarray and Numpy, we can apply standard Numpy filters. For example, we can highlight only slopes in the [avalanche risk](https://www.gravityprotection.co.uk/blog/slope-steepness-avalanche-risk.html) range of 25 - 50 degrees. (Note the use of risky.data since these are DataArrays).\n",
     "Stacking the resulting raster with the hillshaded and plain terrain ones from above gives an image with areas of avalanche risk neatly highlighted."
    ]
   },

examples/user_guide/2_Proximity.ipynb

@@ -7,7 +7,7 @@
     "# Xarray-spatial\n",
     "### User Guide: Proximity (Distance) tools\n",
     "-----\n",
-    "The Proximity tools let you perform analyses using one of three distance metrics: Euclidean (straight-line), Manhattan (with path obstacles, i.e., taxicab distance), and Great Cricle (distance on the surface of a sphere).\n",
+    "The Proximity tools let you perform analyses using one of three distance metrics: Euclidean (straight-line), Manhattan (with path obstacles, i.e., taxicab distance), and Great Circle (distance on the surface of a sphere).\n",
     "\n",
     "[Proximity Distance](#Proximity-Distance): Calculates the distance to the nearest of a set of target - or source - points for each point in the input raster.\n",
     "\n",

examples/user_guide/3_Zonal.ipynb

@@ -64,8 +64,8 @@
     "H = 600\n",
     "\n",
     "template_terrain = xr.DataArray(np.zeros((H, W)))\n",
-    "x_range=(-20e6, 20e6)\n",
-    "y_range=(-20e6, 20e6)\n",
+    "x_range=(-20, 20)\n",
+    "y_range=(-20, 20)\n",
     "\n",
     "terrain = generate_terrain(template_terrain, x_range=x_range, y_range=y_range)\n",
     "\n",
@@ -138,7 +138,7 @@
     "cvs = ds.Canvas(plot_width=W, plot_height=H, x_range=x_range, y_range=y_range)\n",
     "\n",
     "zones_agg = cvs.line(zone_df, 'x', 'y', ds.sum('trail_segement_id'))\n",
-    "zones_shaded = dynspread(shade(zones_agg, cmap=Set1), max_px=5)\n",
+    "zones_shaded = dynspread(shade(zones_agg, cmap=Set1), max_px=5, threshold=1)\n",
     "\n",
     "stack(illuminated_shaded, terrain_shaded, zones_shaded)"
    ]
@@ -195,7 +195,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -209,7 +209,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.9.10"
   }
  },
  "nbformat": 4,