Midterm
Introduction
For my project I chose to do an ArcGIS map that allows you to click through different moose sightings in the Rocky Mountain National Park, CO during 2022. Aside from showing the date it was observed, scientific & common names, and photos, the pop ups will also show the moose’s relative distance to water (using a living atlas layer).
I’ve embedded the map (make sure to click cancel), but here’s the link too- Map
Source
The raw dataset I used was: Wolf and Moose sightings in North America .
This dataset is a collection of wolf and moose sightings all over North America dating back to the 1980’s. It includes a lot of metadata such as date observed on, time zone, location, link to iNaturalist, Image URL, location coordinates, and scientific & common names.
Processes & Web Design Decisions
This dataset had a huge amount of data that I felt was overwhelming. I decided to focus on one specific location and one specific year. I choose Rocky Mountain National Park in Colorado because it is close to home and I chose 2022 as the year because it was recent data. Doing this, allowed me to make the dataset smaller and more centralized.
First I turned the dataset into an excel sheet. Then, I used OpenRefine and used its “text filter” feature to filter the data so that It only showed me moose that were located in Rocky Mountain National Park in the year 2022.
This is the filtered dataset I used: Moose sightings in Rocky Mountain National Park 2022
After inputting the new filtered dataset into ArcGIS I configured the pop-ups to show just the date observed, the time zone, image URL, scientific & common name, as well as have the image show, this way the pop up was not too crowded and showed what I thought was most important.
I changed the icon of each point to either a black or brown moose, each representing a different species of moose, in order to show to the viewer that there are more than one species and also there there are less Shiras moose sighted there in 2022.
Additionally, I added a living atlas layer that displays the relative distance to water (updated 2020) of the moose (unfortunately you have to calculate it yourself by multiplying the number of pixels by 250). I chose to add this layer because I though it would be interesting to see if moose like to hang out near water.
Significance
By adding this atlas layer and putting a visual representation of the moose and their coordinate locations, we can see things that weren’t apparent when looking at the data itself. It is easier to see where most moose gather geographically. Also you can determine whether or not they like to gather closer to water and the difference in numbers between species of moose. Being able to visually see these correlations and interact with the map is something that is super important to digital humanities projects and sets them apart from data science.
A potential pitfall to my approach is that by focusing on one year, it is harder to tell trends over time about the species population as a whole in that area. For example, it would be cool to see if there has been more or less sightings in Rocky Mountain National Park compared to any other year.
