Something Spatial: Administrative Data & Interactive Maps

The map has come to precede the territory.

Working with interactive mapping introduces challenges not typical to static mapping. In the process of creating the Cambridge Housing Authority’s interactive map of public housing developments, I ran across some unexpected accuracy issues. Specifically, this project aimed to provide basic information about available public housing developments for potential residents. The most basic fact about these developments concerns where they are located. Yet, beyond particular scales of the map, the point data used to represent location became skewed. Being familiar only with the location of the central office, I was only made aware of this inaccuracy thanks to some property managers who actually worked at the development sites.

This problem stems from the reliance on administrative data at the agency level. Because the agency isn’t concerned with the use of the exact geographic location of its public housing developments, it relies on a list of street addresses – something that’s pretty obvious for administrative purposes. However, when dealing with map-making, especially in an interactive environment where not every detail is intimately known to the map-maker, it’s possible for users to notice slight inaccuracies in the data that the map-maker would not otherwise see. Clearly, addresses will point someone to the right place for navigation, but in an interactive setting in which users can zoom in to the exact location of the street address, they are only shown a street corner and never an actual building.

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In the image above, the data provided the same address for two very different properties. When the addresses were geo-coded, the two sites were given the same coordinates, effectively hiding the Washington Elms property behind Newtowne Court. Additionally, at this scale, the geo-coded point barely relates to the location of the actual property.

This problem led me to consider alternative ways of generating high-detail point data for interactive environments. To be sure, it is entirely possible to limit the extent to which the user can zoom, preventing the necessity of any additional research, but that’s no fun, anyway. Clearly, public housing developments appear as polygons at close zoom levels. Using City of Cambridge parcel data, I was able to generate a map of the actual lots in which the properties were built. Then, I provided this as a layer on my map:

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Beyond a particular zoom level, the application will switch this layer on, so that the user has a stronger idea of where the properties are actually located. However, to avoid additional complexity, it’d probably be acceptable to generate centroids of the parcels, and match those points to the property data.

This underscores some of the challenges with using administrative data found in public agencies. Addresses will undoubtedly point someone in the right direction (they wouldn’t be addresses, otherwise!), but in terms of representing locations on a map at various scales, geo-coded addresses may not be accurate enough.

Something Spatial: Visualizing Density

No doubt, the technology needed to generate maps is becoming increasingly more user-friendly through an assortment of web-based map-making technologies like Tile Mill, Leaflet, Google Maps, Google Fusion Tables, and CartoDB. With these technologies, anyone can upload geo-referenced data and share interactive maps with friends, co-workers and the public.

For some, especially cartographers, this new trend is stepping on some toes within traditional academia. Eric Steiner – of Penn State fame – makes a salient observation about this phenomenon:

“Traditional cartographers today might say some form of, ‘Kids these days, they don’t know the rules,'” says Eric Steiner, a former president of the North American Cartographic Information Society. “I hear that sometimes at conferences. People lament that there’s this huge influx of people doing cartography who aren’t cartographers.” By “cartographer,” they mean someone who is skilled in trade techniques like projection (transforming a globe into a flat map) or who knows how to interpret line weights. Instead, new cartographers are increasingly software engineers or developers using programming languages like JavaScript and Python. Steiner, himself a graduate of Penn State’s prestigious cartography program, sees the plurality of technique as beneficial. Whether a map is good or bad shouldn’t be based on the narrative of the individual making the map, he says, but rather on the map’s ability to evoke, inspire and question.

Despite these new possibilities, there are still some limitations to how far one can get with these services. Although they provide the most basic answers in spatial analysis – representation of location – there is still some difficulty in answering more interesting spatial questions, like determining the extent to which certain spatial phenomena cluster. Being able to represent clustering – and the extent to which it is occurring – can enhance the power of the “citizen geographer.”

Map Box offers a tutorial that suggests a method for visualizing clusters. With the open-source (read: free) QGIS software, users can generate “heat maps,” or kernel density maps. In this case, QGIS can generate a special raster file (called “.GeoTIFF”) optimized for web, which can then be used in beginner-friendly software like Tile Mill. However, the author suggests an even simpler method, which uses opaque circles around data points:

The effect is less dramatic, although it suggests a simple way to conduct cluster analysis.

The geniuses at the Politecnico di Milano use a similar method for visualizing clustering of restaurants:


Here, clustering is captured merely by generating buffers around points in space, and setting opacities to those buffers. This is not only visually pleasing, it allows for some sense of clustering.

Using data from my own research, I used ArcGIS’s kernel density spatial analyst tool to generate rasters of how banks in Cambridge cluster:

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Clearly, this approach to cluster analysis is not as accessible as Tile Mill, but it is interesting when comparing this method to the method suggested by Tile Mill and the Politecnico di Milano:

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These two images show the workflow for this approach to cluster analysis. In the first image, I used Arc to generate buffers. Then I exported those buffers (with their associated points) into Adobe Illustrator, where I was able to manipulate opacity and color.

The way Arc exports into Illustrator is not always intuitive. Be aware that Arc tends to group layers oddly, and in order to manipulate the vectors, you must select the layer group, expand the group tree completely, and uncheck the eyeball icon (visibility). This will select the vectors and allow you change formatting.

Compared to the kernel density analysis, the second method is obviously weaker in its accuracy. For serious insight into clustering, it is necessary to use algorithmic techniques like kernel density. However, for the purpose of “citizen geography,” the second method more easily captures a sense of how things cluster visually. They both seem to suggest three high-density clusters, with surrounding clusters of weaker density.

How can public agencies use technology to better serve the underserved?

When confronted with the realization that low-income populations by and large do not utilize traditional banking systems, many commentators assume that a lack of physical access to such institutions is to blame. However, according to policy analysts, access to such services is equitably distributed across neighborhoods of varying incomes. Thus, in combatting high rates of the “unbanked” – or those without banking accounts – policymakers and practitioners may consider other avenues for connecting low-income communities to mainstream financial services through mobile banking and other mobile technologies.

In fact, spatial access to banking among low-income residents was never a serious issue to begin with. According to a report published by the Brookings Institute, “low-income neighborhoods have about as much access to bank and credit union branches as middle- and higher-income neighborhoods.” Yet, according to a 2009 F.D.I.C. survey, the percentage of the unbanked is on the rise at a steady rate.

Again, this complicates the picture. Undoubtedly, non-bank financial services like check-cashing and payday lending cost many communities millions of dollars a year. According to a study by MassINC, these communities lose a “combined $72 million lost to check cashing,refund anticipation loans, and EITC associated economic activity.” Yet, the Financial Service Centers of America (FISCA), a trade organization representing the alternative financial services industry, argues that in order to have a non-interest bearing account, customers must maintain a minimum balance of $155.49 to avoid a fee and pay an average monthly service fee of $2.26.

However, a look at the available banking options adds some explanation to these averages. The Policy and Technology Lab (PTLab) at the Cambridge Housing Authority conducted research on how public housing residents bank. With a list of every bank and credit union in Cambridge, the PTLab was able to identify a diversity of banking options, many of which include no-fee, no-minimum balance options (with certain restrictions). For example, Eastern Bank offers a free checking option with a $25 minimum to open:
However, the range of these services is somewhat biased towards benefiting middle- and upper-income residents. For example, a quick look at Eastern Bank’s checking account services shows a Premier Checking account which requires a $25,000.00 balance to maintain. Thus, the FISCA averages skew the diversity of options available in mainstream banking, which provide reasonable low-risk services for low-income communities. Regardless, it is important to understand that many non-bank, alternative financial services are beneficial to many folks, especially those who purposefully avoid banking:

Cambridge Banks Eastern Bank
Account Name Free Checking eZ Checking Economy Savings Statement Savings and Passbook Savings
Type Checking Checking Savings Savings
Minimum Balance to Open $25 $50 $10 $10
Monthly Fees $0 $10 $1 $3 or $2 with direct deposit
Waiving the Monthly Fee N/A Yes – if enrolled in eStatements & make 15 purchases or maintain monthly balance of $1,500 No Minimum daily blanace of $250
Online Banking X X X X
Mobile/Text Banking X X X X
Online Bill Pay X X X X
Insufficient Funds $35 $35 $35 $35
Overdraft Fees $35 $35 $35 $35

Returning to the theme of technology and access, the New York Times published a piece on how some who want mainstream financial services are entirely shut out of the system. One Michigander stated that because of a bad credit report, he was unable to access these services for years:

The costs of not having a bank account for seven years — the longest amount of time that a negative report remains in the databases — can quickly add up. David Korzeniowski, 23, said an employee at a bank in Lansing, Mich., had told him that an overdrawn account reported to ChexSystems very likely scuttled his chances of a checking account until 2016.

Thus, the complexity of access and banking is considerable when determining research questions and policy solutions. One promising avenue is that of mobile technology, and how public agencies can use this technology to improve financial literacy. According to a report by the Federal Reserve Bank of Boston:

The relatively high prevalence of mobile phone and smartphone use among younger generations, minorities, and those with low levels of income—groups that are prone to be unbanked or underbanked— makes mobile phones a potential platform for expanding financial access and inclusion.

With that said, public agencies should consider how to better promote themselves and access to services through mobile technology. One simple means would be to update websites for public agencies such that they’re mobile-friendly. This technology, called responsive design, enables websites to automatically respond to the screen resolution of the user and reorganize content so that it is legible and navigable. The strategy adopts a single stylesheet containing various settings for a number of potential environments. Considering the prevalence of mobile devices among low-income communities, responsiveness in web design is a must for adequate outreach. For example, the Cambridge Housing Authority is including this feature in re-designing its website because many of its residents only browse on a mobile device according to surveys.

With the Affordable Care Act’s required phase-in of state health exchanges, public health departments should consider the mobile-friendliness of their exchange websites. As of now, the Massachusetts Health Connector is not mobile-friendly, making an already complicated system more difficult to navigate.