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<!DOCTYPE html>

<head>

<title>Beware the Canadians!</title>

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<a class="navbar-brand" href="index.html">GEO 503: Spatial Data Science</a>

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<li>

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<a href="Syllabus.html">Syllabus</a>

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<a href="Schedule.html">Schedule</a>

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Content

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<a href="CourseContent.html">About Course Content</a>

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<li class="dropdown-header">Module 1: Introduction to R</li>

<li>

<a href="00_CourseIntroductionFrame.html">00 Course Introduction</a>

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<a href="01_Rintro.html">01 First Steps</a>

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<a href="02_graphics.html">02 Graphics</a>

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<a href="03_DataWrangling.html">03 Data Wrangling</a>

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<li>

<a href="03b_DataWrangling.html">03 Data Wrangling 2</a>

</li>

<li class="dropdown-header">Module 2: Spatial Analyses</li>

<li>

<a href="04_Spatial_with_sf.html">04 Spatial Data with sf</a>

</li>

<li>

<a href="05_Raster.html">05 Spatial Raster Data</a>

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<li class="dropdown-header">Module 3: Advanced Programming</li>

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<a href="06_CreatingWorkflows.html">06 Creating Workflows</a>

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<a href="07_Reproducibile.html">07 Reproducible Research</a>

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<a href="08_WeatherData.html">08 Weather Data Processing</a>

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<a href="09_RemoteSensing_appeears.html">09 Satellite Data Processing</a>

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<a href="11_ParallelProcessing.html">11 Parallel Processing</a>

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<a href="12_DynamicVisualization.html">12 Dynamic Visualization</a>

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<a href="13_SDM_Exercise.html">13 Species Distribution Modeling</a>

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Resources

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<a href="GitSSHNotes.html">Setting up Github</a>

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</div>

<h1 class="title toc-ignore">Beware the Canadians!</h1>

<h3 class="subtitle"><em>Working with Spatial Data and the sf package</em></h3>

</div>

<h1>Reading</h1>

<ul>

<li>The <a href="https://r-spatial.github.io/sf/" target="blank">Spatial Features Package (sf)</a></li>

</ul>

</div>

<h1>Background</h1>

<p>Up to this point, we have dealt with data that fits into the tidy format without much effort. Spatial data has many complicating factors that have made handling spatial data in R complicated. Big strides are being made to make spatial data tidy in R.</p>

</div>

<h1>Objective</h1>

<p>You woke up in the middle of the night terrified of the Canadians after a bad dream. You decide you need to set up military bases to defend the Canada-NY border. After you tweet your plans, you realize you have no plan. What will you do next?</p>

<li>Generate a polygon that includes all land in NY that is within 10km of the Canadian border and 2) calculate it’s area in km^2. How much land will you need to defend from the Canadians?</li>

</ol>

</blockquote>

</div>

<h1>Tasks</h1>

<ul>

<li>Reproject spatial data using <code>st_transform()</code></li>

<li>Perform spatial operations on spatial data (e.g. intersection and buffering)</li>

<li>Generate a polygon that includes all land in NY that is within 10km of the Canadian border and calculate the area</li>

<li>Save your script as a .R or .Rmd in your course repository</li>

</ul>

<p><a href="scripts/CS_05_nocomments.R" target="_blank"><i class="fa fa-file-code-o fa-1x" aria-hidden="true"></i> Download starter R script (if desired)</a></p>

Show Hints

</button>

<p>The details below describe one possible approach.</p>

<h2 id="libraries">Libraries</h2>

<p>You will need to load the following packages</p>

<pre class="r"><code>library(spData)

library(sf)

library(tidyverse)

# library(units) #this one is optional, but can help with unit conversions.</code></pre>

<pre class="r"><code>#load 'world' data from spData package

data(world)

# load 'states' boundaries from spData package

data(us_states)

# plot(world[1]) #plot if desired

# plot(us_states[1]) #plot if desired</code></pre>

<h2 id="steps">Steps</h2>

<li><code>world</code> dataset

<li>transform to the albers equal area projection:</li>

</ol>

<pre class="r"><code>albers="+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs"</code></pre>

<li>use <code>st_set_geometry()</code> to specify that the <code>geom</code> column contains the <code>geometry</code>. This will also rename the column from <code>geom</code> to <code>geometry</code> to make it easier to use <code>ggplot()</code></li>

<li>filter the world dataset to include only <code>name_long=="Canada"</code></li>

<li>buffer canada to 10km (10000m)</li>

</ol></li>

<li><code>us_states</code> object

<li>transform to the albers equal area projection defined above as <code>albers</code></li>

<li>filter the <code>us_states</code> dataset to include only <code>NAME == "New York"</code></li>

</ol></li>

<li>Create a ‘border’ object

<li>use <code>st_intersection()</code> to intersect the canada buffer with New York (this will be your final polygon)</li>

<li>Plot the border area using <code>ggplot()</code> and <code>geom_sf()</code>.</li>

<li>use <code>st_area()</code> to calculate the area of this polygon.</li>

<li>Convert the units to km^2. You can use <code>set_units(km^2)</code> (from the <code>units</code> library) or some other method.</li>

</ol></li>

<li>Do not worry about small waterways, etc. Just use the two datasets listed above.</li>

</ol>

</div>

<p>Your final result should look something like this:</p>

<p>Important note: This is a crude dataset meant simply to illustrate the use of intersections and buffers. The two datasets are not adequate for a highly accurate analysis. Please do not use these data for real military purposes.</p>

Extra time? Try these extra activities…

</button>

<p>Build a leaflet map of the same dataset.</p>

</iframe>

</div>

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