new jersey geographer

The property of a randomly chosen "John Smith"

Mecklenburg County (Charlotte), North Carolina is currently facing an information-sharing predicament. POLARIS, their county-wide interactive web map, currently serves up property ownership information as part of the real property and tax records in the county databases. The county is looking to remove the ability to search by owner to locate land records, mainly because the police are concerned that criminals may use the system to target officers’ homes. I appreciate the concern for the safety of the police force, however theoretically anyone could target anyone else using public records. Just because you have a hammer doesn’t mean you’re going to start hitting people with it. Intentionally crippling a web service and reducing accessibility should always be seen as a major step backwards. (more…)

Over the course of 2009, I got involved with OpenStreetMap. If you haven’t used OSM, I suggest you check it out. It’s being updated and used throughout the world, from mapping campuses in New Jersey to aiding the relief efforts in Haiti.

So, during 2009, I had noticed that on OSM, the State of Georgia had land use data. I started to look into how Georgia was so lucky. OSM relies on user contributions, so some savvy user must have added all of those polygons to the map. I contacted that savvy user to find out more. Liber pointed me to some of the methods he and others have used to import GIS data into OpenStreetMap. I was unsatisfied with the existing software, so I looked into the OSM API and wrote my own code to export directly from ArcGIS into the .osm file format.

ExportToOSM.py is my crack at programming an export utility. I wanted something that would export multipolygons from ArcGIS as OSM multipolygon relations and would produce a file free of redundant nodes. I used an earlier version of my script to export the buildings on Rowan’s campus. After fixing a few issues – namely the multipart polygons (take a look at Evergreen Hall, still need to punch in the interior courtyard as a doughnut hole) – I began developing a plan to export NJ’s 2002 Land Use data to OSM.

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New Jersey is a great state to be a GIS specialist, consultant, or student. There is a wealth of GIS data available throughout the state, and that massive amount of data is getting easier to use.

The Office of GIS in the State’s OIT department has made available several statewide layers via WMS. If you’re not familiar with WMS, the gist of the service is that a remote server renders a georeferenced image of map that can be used in your GIS software, whether it’s desktop GIS like ESRI’s ArcMap, or server-side GIS, like TileCache and OpenLayers. Having a WMS service available is an incredible resource. Where the 2007 aerial photographs span several DVDs (just having the 4 MrSID tiles that cover Rowan University requires 23MB of space*), being able to download just the portion of the aerials at the scale you need is wonderful. Coupled with the fact that it renders faster than drawing from tiles over the Rowan network is outright amazing.

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I recently became involved in OpenStreetMap. After watching it from the sidelines for the past year, I recently started contributing to the map. I wrote a python script to export lines and polygons from ArcGIS to OSM. You can see the results of the script by zooming into Rowan University, where I’ve exported the campus buildings and uploaded them. I’ve also been working to get the various cycle routes throughout the State into OSM. Cycle routes are managed by a myriad of local and state entities, and considering DOT informed me that they do not keep any GIS records of the bike routes or facilities, OSM seems like a natural repository for volunteers to collect and share cycle route data.

I’m also planning a course exercise using OSM. I’m going to encourage students to print out their neighborhood using Walking Papers, recording any updates or fixes, then modifying the OSM data via Potlatch or JOSM. Though it will likely be offered as an extra credit assignment initially, I’m hoping I’ll be able to integrate it and other elements of OSM into my courses in the future.

If you have an interest in mapping or GIS, you should check out OpenStreetMap. Sign up for an account, and start updating in your neighborhood. If you’re in New Jersey, I’ve updated OSM’s wiki with links to the cycle maps to be added, as well as instructions on how to add features to OSM using the State’s 2007 aerial photography. If you’d like to collaborate with me on sharing information via OpenStreetMap, let me know. You can follow me on OpenStreetMap here.

Steven Johnson, author of The Ghost Map, gave a 10 minute talk at TED on the 1854 cholera outbreak in London.

Steven Johnson’s take on the outbreak is an amazing read. If you have just a passing interest in geography or disease control, you’ll enjoy this book.

Over on MetaFilter today, there is a great post filled with links to interactive maps detailing various aspects of the recession and the eventual rebound in the economy. In looking through these maps, I’m irked by the cartographic conventions employed by some of them. Google Maps has started a dangerous trend: representing everything possible as a point on a map.

For example, take Richard Florida’s “The Shaping of America” interactive map in The Atlantic. The map relies on points of varying size to show the number of patents, the population and income levels for selected US cities. The size and color of the point is an indicator of the city’s performance relative to the surrounding “metro average.” There’s no definition of what these “metro areas” are. They are not delineated on the map. The boundaries of the city are also not reflected.

Why is this a problem? While not having the city outlined is concerning, the truly egregious flaw is that the theme of the map is dependent on a ratio without well-defined boundaries. Take, for instance, Trenton, New Jersey. Trenton is slightly north of the geographic center of New Jersey, however it is routinely grouped with “South Jersey” and is rarely grouped in “Central Jersey.” The parts of the State that identify themselves as “Trenton Metro” are limited to adjacent municipalities, if that. So what is the “metro area” of Trenton? Is Princeton included in Trenton? That would absolutely set Trenton above average for all three indicators mapped.

Map depicting just a few of the boundaries for Trenton, NJ

Now consider the New York Times Immigration Explorer. The Times has been cranking out some amazing maps lately and this one is no exception. This temporal, thematic map is rendered using Flash. It shows the 3,000 or so counties within the US with great detail and clarity. Ethic groups as a percentage of total population are reflected on a chloropleth map while the overall population is shown using dots of varying size. We’re back to the dot map, but it’s very different from the Google Dot Map above. The dots are sized in proportion to the total population, not an ill-defined sample. Also, the Flash interface allows the user to manipulate the base size of the dots, which allows the user to discern differences in population in the most sparsely inhabited regions.

Immigration Explorer would still convey its intended message if the cartographers behind it employed a dot map like the Shaping of America. Considering the data is explicitly by county, a point map could be used without introducing ambiguity. However, considering the geographies represented by the Shaping of America map are not well-defined, we are left guessing what we’re actually trying to represent with those dots.

Google Maps (and KML, the language for user-defined data in Google Earth) supports lines and polygons. Granted, there are more hoops to jump through to get vector data into Google Maps, but there are ways to do it. Maps that really require representation using polygons should not be constructed using points & Google Maps. Using Google Maps isn’t what’s important. Making sure your map delivers its intended message is essential.

Starting with Kenya, Google is allowing users to download the base data collected through the Map Maker service, as either KML or Shapefile format. Google’s licensing allows for only non-commercial use. Hopefully, this data will support some of the non-profit mapping efforts taking place on the continent. The license also restricts (or at least, severely limits) competition with services provided by Google. This puts OpenStreetMap in an odd position – OSM is restricted from incorporating the data into its own service. Considering OSM has been around since 2004 and Map Maker only 2008, and seeing how many people in over 100 countries have been offering Google data, OSM needs to better align (or contrast) itself with the work Google is doing. One of the reasons I believe Map Maker has gathered the amount of user-generated content in the past year is that Map Maker is incredibly easy to use and if you do run into issues, there is clear and concise help. This is compared to the OSM Beginner’s Guide. Now, I understand that OSM is geared towards a more technical audience than the Map Maker service, but OSM needs to spend more time fostering a community outside of the devoted submitters. What is going to prevent Google from offering up a GIS service akin to the Virtual Earth on ArcGIS platform currently being offered by ESRI and Microsoft? A service built on TA/Navteq data, enhanced with local knowledge? A service that is available now from OSM, but much easier to use? Providing base data for Kenya is just the beginning.

Mikel Maron has some more thoughts about OSM and Map Maker, as well as some comparison screenshots. (Via Mapperz)

Currently on Rowan’s homepage is an article on the Geography Department’s work on bring GIS to the greater university community. The article focuses on our recent web mapping work; specifically the Land Use Change viewer and NJ State Atlas.  I’m quoted several times in the article, so I’m excited about that.

Direct link to the full article: http://www.rowan.edu/today/news/index/FS/118

I recently requested from the NJ Lottery a list of all the big prize winners, from 1988 to 2008. The winner’s location information is reported by ZIP Code, so I now have a map of the winners plotted out across the state and region.

Among the values mapped for each ZIP code area are the number of winners within, the total amount won, and a location quotient value that highlights areas where the number of winners in each ZIP code is far greater than the average distribution of winners throughout the state. Clicking on the map will highlight the ZIP code area selected, provide a summary of the statistics I have recorded, and allow you to see the entire list of winners by game, amount won and date.

So, here’s the Top 5 ZIP codes by number of winners, total amount one, and by location quotient ratio. The links will bring you to the Geography of Luck page.

Number of Winners

• 07002: 222
• 07083: 178
• 08753: 161
• 07111: 152
• 07055: 146

Amount Won

• 07070: $180,832,210.10
• 08221: $129,030,839.52
• 07010: $97,466,773.00
• 07002: $82,966,249.31
• 07090: $65,758,689.67

Location Quotient

• 07842: 22.2007 (2 winners in a ZIP code of 47 people for a total of $1,374,417.60 won.)
• 07428: 17.6869 (2 winners in a ZIP code of 59 people for a total of $20,000.00 won.)
• 07970: 15.4585 (8 winners in a ZIP code of 270 people for a total of $318,703.00 won.)
• 08036: 14.6081 (7 winners in a ZIP code of 250 people for a total of $288,700.44 won.)
• 07846: 9.6618 (1 winner in a ZIP code of 54 people for a total of $20,000.00 won.)

The location quotient is the (number of winners in ZIP/total number of winners)/(number of people in ZIP/total number of people).

I’m still working on some additional functionality, so if you think of any way I can improve this (or any other map on NJ State Atlas), please let me know in the comments, or by leaving feedback on Get Satisfaction. This project is done entirely in my spare time, so please be understanding if something is broken or not-quite-yet-perfect.

This page has a visualization of the sheer size $1 trillion dollars would occupy using $100 bills. The images are rendered using SketchUp, one of my favorite applications.

I came across this link while browsing BoingBoing, and one of their comments I feel sums up much of what I feel nicely:

I love how the cost of making and sharing this diagram is still $0.00 no matter how big the problem.