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Cultivating Spatial Intelligence

Data and Tools for Comparitive Real Estate Analysis

The most hackneyed cliche in the real estate business is that the three most important factors in the value of land are Location, Location, and Location. When comparing two properties that have similar physical makeup, aspects of the context of the property may provide useful information regarding differences in value. This tutorial explores some of the ways that we may pull together geographic information about the context of properties. Such information comes is a by-product of government administration at the federal, state and local levels. Geographic data extend our traditional table-based information systems (such as spreadsheets) with two-dimensional references that let us find relationships between properties and information about what may be close by. Geographic Information Systems allow us to explore these relationships visually by making maps, and more systematically through associative operations that we can use to add new information concerning context.

References:


Data Layers and Sources

Here is a tour of some of the data layers included with our demo dataset. These appear as layers in our GIS map document. You can lean more about these sources by reading the readme files in each of the folders in your downloded dataset.

Associative Procedures

All of the source layers pictured above are associated because of the spatial references imbedded as attributes of each feature. Your assignment has been to collect observations about properties, that may help to explain the effects of supply and demand. Numbers of bedrooms, nathrooms, etc, are interesting ways including their street address and zip code. This information can be turned into geographic coordinates by associating the address information with our streets layer -- a process known as Address Match Geocoding. Once we have established an explicit location for each of the comps, we can associate each property with our other spatial information.

Download the tutorial data set

The data set and a prepared ArcMap document has been assembled as realestate.zip. Right-click to save this file, and then extract it to a new directory on your local hard drive.

Open the prepared map document and explore the GIS data

For your convenience, we have prepared an ArcMap document, Map2010.mxd, in the map_documents folder. This map pulls together our GIS layers, and sets up an environment for address matching. This will make it easy to explore and get an understanding of GIS data.

References

  1. Double click the file Map2012.mxd that came with your tutorial data set in the folder Map_Documents . This should open ArcMap and display a map of Boston.
  2. Zoom in and out on the map
  3. Open the attribute table for one of the census tracts layers. Select a tract on the map and observe how a row in the table is selected.
  4. Identify features on the map by pointing at them with tie Identify Tool.
  5. Look at your data in layout view and export a graphic map as an .jpg format graphic that can be placed in a word-processing document.
  6. To find a table of last year's comparable properties, comp 2009 first click on the List by Source icon at the top of your maps's table of contents. YOu will find the table in the table of contents under c:\temp\realestate\comp_data

About census data

The US Census is a useful source of information covering demographic and housing charactaristics. The American COmmunity Survey includes information about housing ternure, educational attainment, household income, home value and rents and many other variables. For more information on the census, see About Census Data from the GSD's GIS manual. Our sample dataset has a sample of data from the 2005-2009 American Community Survey, aggregated to census blockgroups. You can find several laters made from these data in the Census group layer in the table of contents. If you right-click on one of these layers and open the attributr table, you will see that the column names are all codes. Click Here to see a data dictionary explaining these codes.

About Streets and Context Data

The streets data, used for address-match geocoding, and other context information used in this demo dataset is available for the entire U.S. on the GSD network, To find out how to make this sort of a database for another place, see Beginning a GIS Databse from the GSD's GIS manual.


Use Address Geocoding to spot your sites

The magic of GIS is that new information can be created from the association of data from different sources provided that each database uses a geographic or projected coordinate system. Map coordinate systems are a deep subject and understanding them is not required for this demonstration, but if you are curious, you could look at the page Map Coordinate Systems from the GSD's GIS manual.

In our case, our real estate data is referenced by street address, a spatial referencing system that is much less structured than simple coordinates. Luckily, there is a method for estimating the coordinate position of street addresses using an intermediate street dataabase.

Reference

  1. Use the Add Data button to add the excel spreadsheet real_estate/comp_data/2012/comp_2012.xlsx. Note that once you have selected the excel spreadsheet, you will be offered a coice to open the first worksheet, or a data range that has been named Export to ArcMap. Open the latter.
  2. Click the Source tab at the bottom of your table of contents.
  3. Right-click on your table of property addresses, comp2010.xlsx and choose Geocode Addresses
  4. If you are asked to find an Address Locator file, Use US Streets GeoCode Service
  5. In the next dialog, click Advanced Geometry Options and for Spatial Reference choose Use Map's Spatial Refeernce
  6. The result will be a map of point locations.
  7. Keep in mind that there are three types of errors that routinely happen with address geocoding:
    • Omissions due to incorrect, unconventional or improperly formed addresses.
    • Completely Erroneous Locations for the same reasons as above.
    • Errors of Precision due to inaccuracies in the streets database, and the logic of the geocoding process, addresses that are geocoded correctly will be in the correct block, but better precision should not be expected.
  8. After Geocoding, try an interactive rematch to see if you can fix the addresses that don't match.
  9. Explore your new spatial database!

Use a spatial join to associate census information with your sites

We've seen how GIS can be used to make maps that juxtapose and reveal patterns in various data sets visually. Now we will take a step into how GIS can use spatial patterns to create new infomation in tabular form. This new information may be used to make more interesting maps, or as the subject of other automated analysis techniques. In this case, we will look at a technique known as a spatial join whereby the GIS can associate attributes from one data layer with the objects in another layer, based on the spatial juxtaposition or proximity of the objects in each layer.

References:

  1. Right-Click your geocoded points and choose Joins and Relates > Join
  2. Perform a spatial join between your censusinformation and your geocoded sites. See Picture
  3. Examine the attribute table.
  4. If you would like to export this new information to work with in excel or some other application, choose Data -> Export from the Options menu at the bottom right of the table.

The association of a property location with the census blockgroup that it happens to be located inside is likely to be ignorant of other areas that may be just accross the street. There are better ways of understanding context than this, but none are so easy to explain in a one-hour demonstration!

Use a spatial join to calculate the association between your comp sites and the nearest school

The spatial join between census data and comp locations worked via a direct juxtaposition of a comp location within a census blockgroup. A spatial join can also provide information about the closest facility to a point. We can use this method to find the closest school, laundromat or coffee shop. In this case, the attributes added to each comp location will include the distance to the nearest school location.

Bonus: Create a 'walking distance' buffer around schools

Time permitting, we will extend this GIS demonstration to show how GIS can be used to create a new geographic pattern which, in turn, can be used to create yet more information! What if 'Walking Distance to Schools' was a criteria that we suspect may be correlated with the value of our sites? We have a schools layer, and we can use this, along with some assumptions about 'Walking Distance' and a techniquue called Buffering to create a totally new geographic pattern that we can use in our analysis.

References

  1. Choose Buffer from arcmap's Geoprocessing Menu.
  2. Create a buffer or buffers around your schools layer
  3. Join information about school walking distance with your sites table

Of course, this model of accessibility to schools is not one that every mother would want to use. And, of course, there are much more complicated ways of forming associations like accessibility considering the difficulty of crossing certain types of streets, etc that GIS can model.

Make Some Maps

There are various ways to get your maps out of ArcMap. The easiest is to turn layers on and off to get the stuff you want to show arranged in a clear way and then simply use File->Export Map to export a jpeg file that you can insert into your word document. If you want to get fancy with Scalebars and Legends, etc. You can choose View->Layout to switch to layout view. Here you can use the various options from the Insert menu to add scalebars, north arrows and stuff like that. YOu can also use the buttons on the Draw Toolbar to add titles and captions to your maps.

References

Once you have got a map that you like, use File->Export Map to export to a jpeg or a PDF. Note that if you are exporting yourt maps to PDF, you should be sure to choose OptionsFormat tab, click Embaed all Document Fonts.

And thats all there is to it!