Harvesting GIS Data for Comparative Realestate 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. So naturally, geographic information systems (GIS) can help us if we want to improve our understanding of value of properties by integrating new information about context. This tutorial will introduce some spatial databases and some GIS techniques that should help us evaluate properties in the Boston area.
Spatial Data
Superior information is one of the greatest advantages in a market. There is vast amounts of useful information available in GIS form from public agencies and commercial sources. This tutorial will only scratch the surface of the wonderful spatial data that is available. For an overview of GIS data resources take a look at the page, About GIS Data from the Design School's GIS manual.
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For this tutorial, we have brought together several easy-to-obtain GIS layers:
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GIS Techniques
Having information is valuable; especially when we can find or create patterns that improve our understanding of opportunity and risk. GIS has many capabilities in this regard; this tutorial can only scratch the surface. The object of this tutorial is to associate information from a table of compariative sites with information about context. To carry this out, we will use several GIS techniques. You can read about these specific techniques the ArcMap user guide, Using ArcMap.pdf. If you want to learn more about GIS, consider taking a GIS Class.
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The specific techniques we will use, and the appropriate page numbers in the user-guide are listed below:
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Details
These steps will help you unpack the tutorial dataset and get your feet wet with GIS-assisted real estate analysis.
- Download the tutorial data set
- Open the prepared map document and explore the GIS data
- Use Address Geocoding to spot your sites
- Use spatial joins to associate independent spatial data sets
- Bonus Create a 'walking distance' buffer around schools and join this with your sites.
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, c:\temp\realestate. Note that if your files are in a directory other than this, this demonstration will not work!
Open the prepared map document and explore the GIS data
For your convenience, we have prepared an ArcMap document, Map1.mxd, which 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. The explicit techniques we will use for exploring GIS data are covered in chapter 3 of Using_ArcMap.pdf
About census data for understanding residential population and housing characteristics of a neighborhood, there is no better data source than the US Census. The decennial census of population and housing has thousands of separate columns that can be used to compare neigborhoods by criteria from income to commuting times. At the GSD, you have access to the complete census for the past 4 decades on our network. For more information on the census, see About Census Data from the GSD's GIS manual.
The Census Transportation Planning Package: is a rather obscure product of the census that focuses on the places people work, what they do there and their commutes. This data typically comes out 5 years after the census. For a list of the attribute fields in the sample of CTPP data included with this tutorial, click here.
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.
- Double click the file Map.mxd that came with your tutorial data set. This should open ArcMap and display a map of Boston.
- Zoom in and out on the map
- 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.
- Identify features on the map by pointing at them.
- Look at your data in layout view and export a graphic map as an .emf format graphic that can be placed in a word-processing document.
- To find your table of sample properties, comp 2004 first click on the Source tab at the bottom of your maps's table of contents. YOu will find the table in the table of contents under c:\temp\realestate\comp_data
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. You can learn more about this from the page, Address Geocoding from the GSD's GIS manual.
- Right-click on your table of addresses, comp2004 and choose Geocode Addresses
- If you are asked to find an Address Locator file, you can find an appropriate one within the Streetmap folder within the Realestate folder that you initially downloaded.
- Accept the defaults from this menu.
- The result will be a map of point locations.
- Keep in mind that there are three types of errors that routinely
happen with address geocoding:
- Ommissions 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.
- After Geocoding, try an interactive rematch to see if you can fix the addresses that don't match.
- 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 ion each layer. You can read all about spatial joins on page 390 of Using_ArcMap.pdf.
- Perform a spatial join between your censusinformation and your geocoded sites. See Picture
- Examine the attribute table.
- 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.
We hasten to note here that the association of a comp 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 spatiial 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. You can read all about buffers in
- Create a buffer or buffers around your schools layer
- 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.