Denison University founded an arboretum in the fall of 2011, and the tree location and species data had to be recollected by hand, because the comprehensive tree species and location data collected by an independent company was unusable for the arboretum’s purposes. The independent company collected tree data in 1998 and 2011 in a proprietary GIS format that could only be exported via .csv, and on top of that the location data was map specific (x/y) and specific to an unspecified scale. At the time I was part of an environmental studies course at Denison, and for an end project, which was independent from the arboretum, I wanted to study how tree growth rates varied with soil type. I needed to find a solution which would easily allow me to find trees to take measurements.
The first challenge I encountered was how to redo the x/y coordinate mapping system used by the independent company. I wanted Latitude/Longitude coordinates which I could program into Google maps for later use. I exported the GIS map to .csv, imported the .csv file to excel and then set about figuring out the maps scale.
Working with nothing but tree points, I first narrowed the data to tree species on campus which were the sole individuals of their species. This allowed me to unquestionably determine the latitude and longitude coordinates 2 trees (henceforth known as trees a and b) which I could use to do the math to batch locate all of the other trees on campus. The first step in the math was to set known location tree a as point 0,0 on a new x/y coordinate plane.
After this I determined the x/y distance of all other trees from tree a, the 0/0 point. Using the x/y distance of tree b from tree a combined with the latitude/longitude difference of tree a from tree b, I was able to create a transformation ratio which allowed me to convert the x/y coordinates of all trees (over 2000 in total) to latitude/longitude coordinates.
The latitude/longitude coordinates of all trees were intrinsically useful, because using a spreadsheet it was possible to find every tree on campus as long as you had a GPS unit. However, I wanted the data to be more visual and publically useful.
Google has a tool available through Google Drive called Fusion Tables. This tool allows a person to import .csv documents with latitude/longitude data onto Google Maps with the metadata intact. I saved my excel file as a .csv, and then imported to fusion tables. This generated a map which is usable on any smart mobile device of all trees on campus, with species and DBH information, and insect data.
Every tree was in the right location, and now this tree map is being used as a resource monitoring tool for Denison’s arboretum. I hope this is useful for some of you in the future!