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I recently created a set of activities based on using web-based GIS tools to teaching spatial thinking using drive-time buffers, and another set of activities that use viewsheds.   Another type of spatial analysis computes and summarizes data from points, lines, or polygons, and is called “zonal statistics.”  To easily use an application of zonal statistics, use this map to summarize population in specific areas.

Calculating the population of the Atlanta area with zonal statistics tool.

After accessing the map, click "Summarize Population" in the  lower left section of the map and then draw a polygon that encompasses Atlanta, Georgia.

What is the population of the Atlanta area?  Why is your result likely to be different each time you draw the polygon?  How does the population of an area of similar size in rural Georgia compare to the population of Atlanta?  How does the population of an area of similar size in rural Wyoming compare to rural Georgia?  Compare your counts to areas of similar sizes in the Ganges River basin in India, or to an area in the Sahara Desert.  Why is the base data that is being used for the population counts critical to the specific results you receive from these calculations?  Test the results over the ocean:  Do the counts total zero?

How might you be able to use this tool in teaching and learning about issues of map projections, data quality, zonal statistics, and other spatial concepts?
I recently posted a set of activities based on using web-based GIS tools to teaching spatial thinking using drive-time buffers.  Viewsheds are another type of buffer.  Viewsheds indicate how much terrain is visible from specified locations.  Viewsheds are important not only in planning scenic overlooks along trails and highways, but help in everyday decisions such as siting optimal locations for cell phone towers, determining how much terrain would be in shadow if a certain high-rise were to be constructed, helping plan safe roadway curves, and much more.  Open this map to create your own viewsheds.

Teaching spatial concepts with viewsheds.

This map service shades the terrain viewable within 5 miles of your chosen point.  Say you are interested in taking photographs in San Francisco but you only have 2 hours to do so, during your airplane’s layover at SFO.  You want to be as efficient as possible, choosing locations that allow you a magnificent view.  Click in several locations on the map and observe the viewshed after each location. Your viewshed should be greater if you click on one of San Francisco’s many hills.  For example, I created the viewshed shown here using the above link.

Judging from the shape of the viewshed, at this point would you be standing on a south-facing hillside or a north-facing hillside?  Next, click on the Golden Gate Bridge (leading northward from San Francisco on US 101).   Why is the 5 mile viewshed so much greater in area at this location? What is the viewshed from Fisherman's Wharf? From Telegraph Hill?  From the Financial District in the streets amongst the tall buildings?

How might you be able to use these viewshed tools in your teaching?
Teaching spatial concepts and analysis can be effectively done with web-based GIS tools.  One type of spatial analysis involves the use of buffers--areas that show proximity to mapped features.  One kind of buffer is a “drive time” or “service area” buffer, which can be used to calculate and display the amount of time required to walk, bicycle, or drive to or from a certain location.  This developer map is also useful for teaching  to create some buffers, in this case, drive time.

1-2-3 minute drive time buffers

Click on a location in the city of Lawrence, Kansas and wait a moment for the drive time buffer to appear.  Ask the students:  Why aren't these buffers a perfect circle?  Click on Interstate Highway 70 and note the differences between the buffer along this limited access highway versus a buffer along city streets.  Click on a point just north of the river and note the effect of the river that blocks quick access to areas south of it.

These drive time buffers depend not only on the street location and density, but they have intelligence beyond street location:  They take into account one-way streets, stop signs and stop lights, traffic volume, speed limit, physical barriers, and terrain.  Pan the map to a rural area outside Lawrence and click on the map in that location.  What is the difference in the amount of terrain someone could reach in 1, 2, and 3 minutes from a rural area versus that from an urban area?  Why do these differences exist? Pan to the location where you live and calculate drive time buffers in different locations in your own community.

For an application of this concept in analyzing access to a specific type of business, access this map showing pizza restaurants that are within a 3 minute drive of the location you select.  Click on various locations and note the differences in the buffer and the resulting selected restaurants.  This service uses a Yahoo! Local Search to calculate its drive time, but also note that terrain is still important.  In other words, yes, physical geography still matters!

Both of these live maps and the services they provide are easy to use, fascinating, and can foster much good discussion about the practical application of spatial thinking and analysis.

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