GIS 295 Term Project Blog #3


When taking GIS 203 (Cartography), my final project was creating an orienteering map with GIS Desktop using the International Orienteering Federation (IOF) cartographic standards. The map’s purpose is to teach orienteering to first year Scouts in order to pass specific requirements.  As a result, the map is part of a two-page product containing information about calculating a bearing, estimating height, and space to enter control point information.

For GIS 295, I want to explore how to create the same map with the same features with a general purpose map creation tool such as ArcGIS Online and a specific orienteering map creation tool called Open Orienteering Map ( I plan to use the three blogs required to describe how the orienteering maps are created with each system – ArcGIS Desktop, ArcGIS Online, and Open Orienteering Map.

OpenOrienteeringMap V2.4 Description

OpenOrienteeringMap (OOM) is a custom version of Open Street Map created by Oliver O’Brien that uses many IOF cartographic specifications (IOFmapping). The purpose of OpenOrienteeringMap is to easily create orienteering maps using the OpenStreetMap spatial data set of the world and the map rendering toolkit Mapnik. The displayed view is dynamically created in one of four base map configurations as the user pans or zooms in or out in supported fixed-scale intervals. Scales 1:7000 and 1:14000 (zoom levels 16, 15) are most commonly used for orienteering maps. The displayed scale can be used to generate PDF files with associated features.

To view any region in North America, the “Global” button located at the top of the main frame must be selected to display everything but the UK and Ireland. The following shows the opening screen with the Global button selected (note that like, the first map displayed is always Europe:


Base Maps

Four base maps are available: Street-O, Street-O Xrail, Pseud-O, and Urban Skeleton. The Street-O map setting originates from the Street-O maps used for informal orienteering races in London and other areas around the UK. Only roads, tracks, paths, rivers/lakes and railways are shown; the maps are high-contrast (black on white) and have little color. The few colors that are on the map – for major roads, park land, and water features use the “official” ISOM standard colors for these features. The Pseud-O base map emulates the look and feel of standard orienteering maps, but in many regions, does not have the detail necessary in OSM. The rendering is done on-the-fly, but with caching. The two styles are available from zoom levels 12 to 18. Levels 15 & 16 roughly correspond to scales that would be used for conventional orienteering. The following screenshot shows a Street-O view of the Fraser Preserve in Great Falls:


The only difference in Great Falls is the open woodland designation for the non-park land regions, where they are shown as white in Street-O. The following screenshot shows a Pseud-O view of the Fraser Preserve in Great Falls:


The following screenshot shows an Urban Skeleton view of the Fraser Preserve in Great Falls:


Map Creation Procedure

Perform the following steps to create an orienteering map, control point clues, and generate the PDF files to be incorporated into a finished product:

  1. Select “Global” for North America and focus on the Fraser Preserve in Great Falls, Virginia, at 1:5000 scale.
  2. Select base map for “Pseud-O”
  3. Select Landscape or Portrait, click in the desired map center. If necessary, drag the blue marker to re-center the map. A frame will appear over the base map in portrait or landscape orientation.
  4. On the right, click the pencil edit icon to display the map title. I entered Camp Fraser Orienteering, then press OK.


5.  Select the next edit icon to modify the race instruction title:


6.  Click on the Start/End point on the map to display the following dialog:


7.  Click on the next Control point on the map to display the following dialog:


Enter the numbers and descriptions for each control point. Set the location of the number label by rotating the label angle control. Repeat for all the control points resulting in the following map:


8.  Click on “Save & Get PDF Map” button and the following message appears:


Click OK and save the automatically downloaded oom.PDF file located in the Download directory.

The completed map appears on screen within a map frame containing the control points:


9.  To retrieve the above map, enter the code 5668f7ca777e5 into the “Load saved map #:” and select the “Load” button.

10.  To delete the above map from the display, select the “Delete Map” button.

Output Options

For orienteering applications, the created map product will have to printed and used off-line. OOM makes PDF map file generation easy using the “Save and Get PDF Map” and “Show Clue Sheet” buttons.

  1. To view the generated PDF file when “Save and Get PDF Map” button selected, search for OOM.PDF in the download directory and display:


2.  Click the “Show clue sheet” button to display the seven generated control points:


3.  Click “Print clue sheet” to display the print prompt and output the file as a PDF.

4.  Incorporate the two PDF files into a complete orienteering document.


As evident from the above procedure, it is easy to create a usable orienteering map. The base map is at a small enough scale to map a small area. Many cartographic features, including trails, roads, control points, start/end point use IOF cartographic standard.   There are some things missing from the map however; 5 meter topographic lines, exact IOF-specified land features, and free text labeling. Since the Open Street Map doesn’t have topography, it would be too processor intensive to dynamically render topo lines.  Because of this dynamic rendering of the custom maps, a high-speed Internet connection is necessary.

Creating custom maps using the free OSM spatial data set and a private data set containing unique cartographic features makes OOM possible and a powerful paradigm. As a result, thematic, web-based mapping that addresses the needs of specialized communities is now possible.

Reference Summary:






Why Location, Location, Location Actually Matters

Kirk Goldsberry, a geographer from Penn State, was interested in finding ways to visually depict data about movement through space and time. He also was a big basketball fan who played all his life.  In 2011, Goldsberry had the idea of mapping the dynamic ebb and flow of the game based on recently developed baseball statistical analytics. Using data scraped from ESPN basketball statistics web pages containing shot statistics, he eventually compiled spatial coordinates for more than 700,000 successful shots taken from 2006 to 2011.  The final results were mapped as color-coded, square-foot pixels across the court (



This work led to a presentation made at 2012 Sloan Sports Analytics Conference, an annual gathering of statisticians and coaches at MIT.  NBA coaches saw the value of the spatial patterns generated.  A company called Stats teamed with Goldsberry to build a 3 camera-based system to track players and provided much more detailed information. In September 2013, Stats sold SportVU to the NBA for $100,000 per arena.  With the spatial patterns generated by this system, spatial data analytics at the basketball court (micro) scale is now possible.

Now the NBA has the statistics available at with their own version of shot maps, plus many detailed tables of every aspect of the game by player and team:


While there isn’t a public API provided by the NBA to access the statistics, there are web-scraping APIs available to retrieve the data programmatically, a much better alternative to the manual method Kirk Goldsberry used with  Micro-mapping articles and code samples are now available using the NBA statistics: The following map shows a Python language mapping utility written by Savvas Tjortjoglou (


This application takes mapping to a micro scale measured in feet, within a room, and not miles across counties, states, or countries.  As a result, new mapping applications are feasible to show spatial patterns as long as the data is available!



Greg Bacon Presentation

On Wednesday, November 11th, Greg gave an excellent presentation about the Fairfax County GIS office where he works as an analyst, that supports both county GIS users and the public.  He mentioned the specialized, web-based maps his office produces available online at the Fairfax Geo-Portal Page:(


I enjoyed reviewing the maps, especially the Comprehensive Map Plan, Walkway Maintenance (Greg specifically mentioned this map) and the Historic Imagery Viewer.  One area of Fairfax County I’m interested in is Tyson’s Corner, having worked there for almost 20 years.  The area is undergoing a significant transformation with the metro arrival and more residential housing being built. Tyson’s Corner is changing from a car-oriented, office and shopping center to a high-density, mixed-use area that hopefully will be increasingly pedestrian friendly.

The following screen shot from the Comprehensive Map Plan shows Tyson’s Corner zoning plan:


The following screen shots from the Geo-Portal Historic Imagery Viewer show the Tyson’s Corner intersection of Routes 123 and 7 in 1937, 153, and 1997:


Tysons1953HIV Tysons1997HIV

Tyson’s Corner redevelopment plans are ambitious, and a detailed description was written in the Washingtonian Magazine, April 2015 cover story issue, Capital of The Future. The following image shows a future high density, mixed-use, pedestrian-friendly scene:


It still is a challenge to walk around Tyson’s Corner. I used to use the only cross walk on Route 7 at West Park Drive when leaving my Forester at the Stohlman Subaru dealership for repair.  Walking safely is still limited to specific sections where sidewalks were present, but there were, and still are, many obstacles present.  The Geo-Portal Walkway Maintenance map shows the organizations responsible for sidewalks in Fairfax County and the following screenshot shows the pedestrian walkways in Tyson’s Corner:


On November 8, The Washington Post published an article about a group of UVA School of Architecture students assessing Tyson’s walkability:  They encountered many obstacles and plan to monitor pedestrian accessibility as redevelopment progresses.  The following map shows the temperature measured along the route they took in 2014:


Dynamic, Static Maps from the Washington Post web site


The Washington Post web site contains a great example of both static and dynamic maps in an article used to display US energy sources (coal, natural gas, oil, nuclear, hydro, wind, and solar) for 2015. “Mapping How the United States Generates its Electricity” was created July 31, 2015 by John Muyskens, Dan Keating and Samuel Granadosand and accessible using the following link:

The light gray, dynamic US map contains geographically distributed, colored coded (by power source) circles indicating the generating plant sizes in megawatts, which are defined by two legends. Moving the mouse across the states displays a pop-up, numeric list of power sources by state.  This map gives the reader the overall distribution of all generating facilities with the color coded sources showing a pattern of predominate use.

A second dynamic visualization tool allows the reader to select a power source and display a state-by-state comparison using a 50-state, color coded, bar chart in descending order. This shows which sources are dominate across each state in terms of percentage electricity generated, not from a geographic perspective.


A series of seven maps show the distribution of electrical generating capacity by source with additional details provided by an accompanying paragraph. Using the same gray background and color coded symbology, these maps show in detail the geographic distribution of power source.  As a result, patterns such as solar powered plants mostly in the southwest are clearly evident, but there are a surprising large number present in the northeast. The adjacent text discusses general power source specific generating details and trends.  This combination of static and dynamic maps allows the user to get a very detailed assessment of US electrical generating capacity.

Mystery of the Missing Base Map Data!

After we all had trouble loading base map data in class #2, I tried with my HP Windows 7 laptop at home with no luck using IE and Firefox (via GIS server) after logging into

This week I was in a training class at the AWS Herndon office using a Windows 10 on an Intel NUC PC with Chrome, Firefox, and MS Edge (new Win 10 browser replacement for IE). I was able to log in with all browsers, but could not load any base map or layers with any of them!

Given the different Internet network links and browsers I’ve tried, I believed I was doing something wrong loading this content into a map! I’ve got to review the videos to review the procedure. There was no Internet delay at home or at AWS like we experienced at class.

On Saturday morning, after breakfast, I was in the kitchen with my first generation iPad, which I use for reading e-books and web surfing. I went to because I couldn’t recall the NOVA-specific URL. To my surprise, a default base map appeared after clicking the Map link! I could display any base map selection and even apply additional layers from the “Search” for layers. I was doing all this while not signed in, just from

After trying this on my iPad, I duplicated the above with my HP laptop on As soon as I logged in with the ID and password set for, the base map disappeared and I couldn’t select any other. As a result, I believe the base map problem lies with the NOVA-specific version of

After logging out and going back to, I created a simple base map and saved it to my account name. I could then log into my NOVA account, recall the map, change base maps and add layers. We may have to save a “dummy” map to prime the account with some data that allows us to create a real map!

Assignment 1

My name is Paul Devine and a graduate of the NOVA GIS certificate program. NOVA has been my main resource of continuing education and I’ve earned over 60 credits over 20+ years taking programming, database, and networking courses. I’ve worked as a software engineer for over 30 years and during that time, raised four children (two boys and two girls) with my wife Jill. During that time I’ve worked for several companies including Denro, TASC, SAIC, and CTA Space Systems.

This picture was taken for the company newsletter

The picture above is a me at 25 years old at my first job working for Denro in standing front of the air traffic control communications system racks to be shipped to Hill AFB.  The scope-looking device on the right is one of two Tektronix logic analyzers the company owned and used to debug the Z80 assembly language running on the system’s distributed processor boards. This picture was taken for the monthly newsletter.  As an entry level software engineer, I learned about and practiced system engineering processes equivalent to CMMI level 3 before we had the terminology describing as such.

According to ESRI, a Geographic Information System lets us visualize, analyze, and interpret data to understand relationships, patterns, and trends.

I was part of a software development team at SAIC maintaining a GIS extension called GeoRover (, an analyst productivity package for ArcGIS Desktop. The extension uses a COM object interface to access the ArcGIS SDK which performs the actual mapping of specified data.