This map shows Carleton campus, the Arboretum land, and farm lands and deeds as they stood in 1941.
https://contentdm.carleton.edu/digital/collection/Arb/id/3931/rec/26
process
The process of overlaying the old map onto the current map was challenging. Although the map in 1941 has a familiar overall shape, the labels are almost unrecognizable. The most prominent features are the Lyman Lakes and the river extending throughout the map. Those were easy to set control points on, but others were harder to pinpoint. For example, most farmlands have transformed into sports and recreational fields.
Possibilities
Because the map of Carleton grounds in 1941 shows many available farmlands, Carleton could use the map for planning and infrastructure development. Historical data can contain spatial reference information by creating a geo-rectified map. One of the many uses of a geo-rectified map is feature extractions, such as buildings and streets, and distance measurements for planning and analysis purposes.
Understanding where things are and where events occur can help to analyze the relationships between places. For example, opening a new store requires determining the best possible location for the store. The decision-making process will include factors such as demographics and economic data to aid in evaluating the relationships between people and surrounding areas. The next step is plotting some factors from the data sheets onto the geo-rectified map. There is a story in every map with further analysis.
Problems
Geo-referencing can lead to positional error because plotting each point and line on the map is an approximation. The resulting coordinate values contain errors and produce inaccurate dimensions. Some best practices to avoid human error are consistent naming, checking data sources and metadata, and selecting identifiable control points. These practices allow for a more accurate mapping.
Spatial DH Projects
After seeing the spatial DH projects, I understand that geo-rectification and geo-referencing are essential for making arguments about spatial data. Research areas that attempt to answer non-geographic questions shouldn’t use these methods. Geo-rectification and geo-referencing are excellent for displaying many data points and telling a coherent story.
