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Practice activity

Practice activity

If you have installed Python locally, launch JupyterLab by running:

conda activate sds

and

jupyter lab

Where are buildings in Eastern Oregon?

checkerboard

In this activity, we will combine several vector datasets to investigate the spatial distribution of buildings in Eastern Oregon. The building footprints can be downloaded from here. This a subset of buildings from the dataset produced by Microsoft using AI. See the GitHub page for more information about the data. The other datasets we will need is the highways dataset which can be downloaded from here and the Census tracts dataset which can be downloaded from here. A “tract” is a subdivision used by the Census Bureau that is smaller than a county and usually contains between 1,200 and 8,000 people.

Task 1 (10 points)

Load the building dataset.

  • a) How many rows and columns does this file have?

  • b) What is the coordinate reference system of this file?

  • c) What type of geometries does this file contain? (i.e. points, lines, or polygons?)

Load the Census tracts dataset

  • e) How many rows and columns does this file have?

  • f) What is the coordinate reference system of this file?

  • g) What type of geometries does this file contain?

Load the highways dataset.

  • h) How many rows and columns does this file have?

  • i) What is the coordinate reference system of this file?

  • j) What type of geometries does this file contain?

Task 2 (5 points)

  • Reproject all three files to UTM Zone 11N (EPSG:32611)

Task 3 (5 points)

  • Perform a spatial join (i.e. sjoin) between the building footprints and the tracts GeoDataFrames so that each building has the attributes of the tracts GeoDataFrame.

  • Which county (COUNTYFP) in Eastern Oregon contains the most buildings? Looking for a name here (not a number).

Note

We can find the name of the county that corresponds to the COUNTYFP code here

  • Which county (COUNTYFP) in Eastern Oregon contains the least buildings?

Task 4 (5 points)

  • a) Produce an interactive plot (i.e. using explore()) showing buildings in Wheeler County

Task 5 (10 points)

  • a) Produce a new GeoDataFrame that only contains highways within Harney County (i.e. using sjoin()).

  • b) Produce another new GeoDataFrame containing only the buildings within Harney County.

  • c) Buffer the Harney Highwway GeoDataFrame by 1/2 mile.

Note

The buffer() function is useful for this.

  • d) Set the active geometry of the Harney Highways GeoDataFrame as the new buffer column.

Note

We can use set_geometry() to do this.

  • e) Group the buffered polygons into a single MultiPolygon using the dissolve() function. There should only be one row after performing this step.

  • f) What percentage of buildings in Harney County are within 1/2 of the highway?

Note

May have to drop the index_right columns before running this function.

  • g) Make a plot of buildings in Harney County that are within 1/2 mile of the highway using explore().

Important

Save your notebook to your local course folder and submit assignment (in .pdf format) to Canvas by the deadline.

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