GIST 5300 Midterm Project - Analyzing Glacier Loss and Tourism Patterns
Student: Jonathan Munroe
Course: GIST 5300 - Web Mapping and Internet GIS
Date: October 23, 2025
Assignment: Midterm Assessment
This project examines the relationship between glacier retreat and park visitation at Glacier National Park from 1966 to 2015. Using web GIS technologies including Leaflet maps and Plotly charts, I will analyze the correlation of glacier loss and tourism patterns.
This dataset contains precise measurements of glacier surface areas in Glacier National Park across four time periods: 1966, 1998, 2005, and 2015. The data was collected by the U.S. Geological Survey using aerial photography and satellite imagery to track glacier retreat over a 49-year period. This dataset is significant because it provides quantifiable evidence of climate change impacts in the park, showing an average ice loss of over 30% across all glaciers. Each data point includes glacier coordinates, area measurements for each time period, and calculated ice loss percentages, making it ideal for temporal analysis and spatial visualization.
This dataset tracks annual visitor counts at Glacier National Park's various entrance points over the same time period as the glacier measurements. Collected by the National Park Service, it includes total visitor numbers and entrance-specific data with geographic coordinates for each access point for the summer busy season (Jun-Aug). This dataset is significant because it reveals a dramatic 161% increase in park visitation during the same period when glaciers were rapidly disappearing. Visitation by entrance was unavailable for 1966, and data for some entrances is incomplete for other years. I had to personally calculate the yearly values since the data was availble for entrance by month.
These datasets are valuable to analyze because they cover the same time periods(1966, 1998, 2005, 2015) and the same geographic area, enabling direct temporal and spatial correlation analysis. They can provide insight for environmental tourism trends and the greater implications of the climate crisis.
The map below shows the locations of glaciers and park entrances. Glaciers are color-coded by their ice loss percentage, and you can click on markers to see detailed information.
Map Legend: Red circles = high ice loss (>50%), Orange = moderate loss (30-50%), Yellow = low loss (20-30%), Green = minimal loss (<20%)
1. Temporal Correlation Analysis: Calculated the Pearson correlation coefficient between total glacier area and annual visitor numbers across the four time periods (1966, 1998, 2005, 2015) to quantify the relationship between ice loss and tourism growth.
2. Time Series Visualization: Created dual-axis line charts to visually compare glacier area decline with visitor number increases over time, allowing for clear identification of trends and inflection points.
3. Spatial Analysis: Mapped the glacier locations with entrance points to see which park areas are most affected by ice loss and how this relates to where visitors can access them.
4. Percentage Change Analysis: Calculated the total percentage changes in both glacier area and visitor numbers to show how big the changes really are.
Why I chose these methods: These seemed like the best ways to handle data that changes over time while also showing where things are located. The correlation gives me actual numbers to back up my findings, while the charts make it easier to see what's happening. Together they help me understand if there's really a connection between disappearing glaciers and more tourists.
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