Map Data Sources
I couldn’t complete a project without injecting spatial awareness somewhere. I felt it was extremely important for this project to have maps and data to give important context not only to WWII and the Holocaust, but to European boundaries in general. Americans don’t tend to prioritize geography, let alone geography from 80 years ago. WWII happened “over there,” but we don’t bother to learn about these regions, to be curious about their cities, mountains, and rivers, and hence do not forge empathy for their situation. Even from the First World War, national boundaries in Europe were constantly changing. Western Europe resembled much as it does today, but Germany and Eastern Europe boundaries could change month-by-month. Understanding the placement of these countries is an important building block to the rest of the stories.
WWII Boundaries
As I was searching for map boundaries from WWII, I found this incredible dataset from Stanford University’s Spatial History Lab published in 2010: “Building the New Order: 1938-1945.” The author provided GIS shapefiles of borders on a nearly month-by-month timeline through this period. The project’s goal was to “represent WWII boundaries through an animation that demonstrates how borders changed over time…they can be presented dynamically and in greater depth than static mediums.” My goal was much simpler, to capture one representative snapshot of what the borders and German-influence looked like at one of the more dire times of the war. I chose April 1944 as a base for my map because it shows the breadth of German and Axis-occupation, and in particular, the General Government (German-occupied Poland), and the Italian Social Republic (German-occupied northern Italy) and Allied-occupied southern Italy.
Nazi Camps and Ghettos
One of my advisors suggested showing the breadth of Nazi camps and ghettos across Europe to provide context to what the Jews, rescuers, and others being persecuted were up against right outside their door. The Holocaust Geographies was limited in its scope. The USHMM has older map graphics on their website of these locations, which are very informative, but not georeferenced. I emailed to inquire about a dataset or spreadsheet of the points on these maps (the dots had to come from somewhere). They replied that there isn’t one, but their staff are in the process of digitizing the Encyclopedia of Camps and Ghettos, 1933-1945. That would certainly not be competed in my timeframe so I rolled up my sleeves and got to work.
My workflow involved georeferencing the above map graphics in QGIS to the best of my ability, and then heads-up digitizing the point locations. These are not intended for any analysis or decision-making. They are for general awareness only and will not be distributed. Only the major concentration and extermination camp locations were verified (more below). My process in QGIS:
Raster Menu > Georeferencer
Add Raster graphic.
Have country boundaries base layer in QGIS.
Use Add Point button in Georeferencer to click at somewhat known point on the raster. A new window pops up so click on its From Map Canvas button, that window will automatically minimize and take you to QGIS, click on the same point in QGIS. Click on OK button on Enter Map Coordinate window.
A new row will appear with its Residual number, which will be calculated after georeferencing.
Go around the raster graphic and QGIS and click on at least 10 points. Use the zoom and pan tools to move around.
Click on the Settings of the Georeferencer.
Transformation type: Thin Plate Spline
Resampling method: Nearest neighbour
Target SRS: ESRI 102013 - Europe Albers Equal Area Conic
Output raster: Verify folder and name of new TIF
Click on Start Georeferencing button
Minimize the Georeferencer window
Move the layers in QGIS to see how well the process worked.
The Residual numbers should be low (i.e. <1). Delete numbers that are too large and try finding a better location to reference.
To start a new raster graphic, click the File menu > Reset Georeferencer
Major Concentration, Extermination, and Euthanasia Camps
These camps were also chosen from the USHMM map graphics, but I searched their names and exact locations in both Google Maps and OpenStreetMap to cross-reference. In each case there was a memorial site and/or museum location for the camp victims, which I then found in the OpenStreetMap raster base layer in QGIS. I digitized the location, added the name and camp type to its attribute table.
Gino Bartali’s Cycling Routes
One of Bartali’s famous routes as he worked as a courier for the Assisi Network is from Florence to Assisi. This has since become a well-known route for Bartali fans, with small tour companies offering to take cyclotourists on the route, and other more fit cyclists doing to ride in one day as Bartali would do. I found the GPX route in RideWithGPS and brought it into QGIS where I edited it to navigate through the narrow streets of Assisi.
The route from Assisi to Terontola is a combination of the “Ciclopellegrinaggio Terontola-Assisi, Gino Bartali Postino per la Pace” ride that Ivo put together, and my own exploration around Lake Trasimeno to Terontola.
I [HEART] Mapbox
None of these data could be displayed without the phenomenal work of Mapbox developers who put together Mapbox Studio and Map Stories - and they’re FREE (when you’re small potatoes like me). The cartographic goodie-bag of base layers in Mapbox Studio just floors me every time. I don’t have to worry about label scaling or highway shields or terrain or satellite imagery….it’s all there. And I can upload my own datasets and tweak their settings on my own. I’ve brought these map styles into several applications and they’re always flawless.
The other Mapbox application is their Map Stories. I’ve always wanted to create a map-based scrolling story, and this was so easy to set up. I watched one of their extremely helpful videos and read over a little documentation, then this “non coder” was able to tweak an HTML and Javascript page to create four Map Stories for my project.
THANK YOU MAPBOX!!