30 Day Map Challenge 2023
Day 1: Points
This map shows earthquake epicenters for some of the biggest quakes we've had in Utah. I created this map using earthquake and fault data from UGRC from 1850-2016. I also added the Magna earthquake from 2020 and its larger aftershocks.
Check out our hazards portal to learn more about risks near you!
The director of the UGS, Bill Keach, recently reached out to the Utah Legislature for more funding for an early earthquake warning detection system. My map here was featured in his presentation! Check out the full article below to learn more!
Day 2: Lines
I created this map using data from ESRI for the major US rivers and the National Weather Service for the smaller rivers. I manipulated the symbology to group local river systems, as defined by the National Weather Service in 2007.
Day 3: Polygons
As part of my master’s thesis, I compiled data and created geologic maps of each of my study areas. This often involved georeferencing and creating my own polygons of geologic unit data where GIS data was not available. It was important to understand the local geology to better identify major dust sources in these areas. I’m currently working on prepping this research and these figures for publication, so stay tuned!
The map below is one of 10 different maps of my study areas.
Day 4: A bad map
How many bad things can you identify in this map?
I created this map using address point data from UGRC, which represents every point in Utah with an official US Postal Service (USPS) address.
Day 5: Analog map
For this prompt I created both a digital and analog map of Iceland, shown side-by-side below for comparison. I recently took a watercolor class through the city and thought it would be fun to put my new painting skills to the test!
Day 6: Asia
As part of my undergraduate research, I worked on finding and translating maps and historical records from the Dutch East Indies (modern day Indonesia). We were interested in eyewitness accounts from large earthquake and tsunami events as far back as we could find, since modern earthquake analogs only go back until the 1930s. Lucky for us, the Dutch took detailed records while they were there!
On January 6, 1898 at 1pm, a large earthquake shook the island of Ambon, Indonesia. An eyewitness recounts the event in a letter to the Governor General of the Dutch East Indies, saying “Your Excellency, the words from my last telegram ‘The whole of Ambon has been destroyed’ were not an exaggeration.” Images taken before and after this event confirm this statement, showing extensive damages to Fort Victoria, the hospital, and other notable buildings throughout the city.
Because of its lush vegetation and topography, it’s difficult to identify where these still-active and very dangerous faults are located in Ambon. Using these historical documents and maps, we were able to find where these damaged buildings were located and determine an MMI (Modified Mercalli Intensity) based on damage observed in these photographs and descriptions given in the records. These findings will help us identify the most at-risk areas today so we can better prepare the people there for future events.
Eyewitness accounts and photographs were taken from Ambon - Voor en Na de Ramp, Kort Verslag over de Aardbeving te Ambon op 6 Januari 1898, and Natuurkundig tijdschrift voor Nederlandsche Indië. These documents provide a plethora of information on this previously unknown event. I also took my own photo of cracked walls in Fort Victoria from the 1898 quake while I was there visiting in 2019. We’re also working on publishing our research findings from here, so keep an eye out for that soon!
Day 7: Navigation
Since I ride the FrontRunner and TRAX at least once a week to get to work, I thought it would only be appropriate to make this map today.
I created this map using data from UGRC and referenced UTA routes.
Day 8: Africa
I created this map using public GPS collar data for African Buffalo in Kruger National Park in South Africa. Using data like this, parks can track the migration patterns of various animals in their park throughout the year. Here, we can see the African Buffalo population migrates as far as 60 km in a calendar year!
Day 9: Hexagons
Inspired by the game The Settlers of Catan, I made a version using different land types in Utah. The “settlements” represent the little block pieces used in the game.
Day 10: North America
This map displays all the national parks in Canada, the United States, and Mexico.
I made this map using data from the United States and Canadian National Park Services and Global Forest Watch for Mexico’s protected areas.
Day 11: Retro
One of my current projects is updating information on rockhounding sites in Utah. This often entails some research, then field checking these sites to make sure they’re still accessible, on public land, and have enough cool rocks for everyone to find! The map I made today is inspired by maps in the old rockhounding books I often reference. While some of the sites below are no longer viable, there are still plenty more to be found on our updated map!
Check out our current interactive rockhounding app! https://geology.utah.gov/apps/rockhounder/?page=Interactive-Map
Day 12: South America
My dad and brother created MissionCall.app. This app allows you to create custom guessing games and make predictions for where somebody might be called on their mission for The Church of Jesus Christ of Latter Day Saints. Today, I made my map using polygons created by my brother Wesley Mangum and integrated point data for all of the existing temples from The Church of Jesus Christ. Give this app a try with all the upcoming missionaries in your life!
Day 13: Choropleth
Today I decided to go simple with a population density map of Utah. To make things a little more interesting, I used the Multiply Layer Blend tool and combined the census data with a Utah hillshade basemap.
Day 14: Europe
After living for a year and a half in the Netherlands as a missionary, this country has my heart! I decided to make a map showing windmolens (windmills) throughout this beautiful country.
Day 15: OpenStreetMap
Happy GIS day! Today I made a map showing parking at BYU. I used OpenStreetMap as a reference to create these polygons and set it as the basemap.
Day 16: Oceania
Today’s map was inspired by early explorers in the pacific ocean. I referenced a map created by Te Ara - The Encyclopedia of New Zealand to draw the paths of each of these explorers.
Day 17: Flow
For this prompt, I created a model to output watershed boundaries and calculate streams based on any given threshold value. I delineated the watershed by filling in the sinks in the DEM and calculating flow direction and flow accumulation. With this information I was able to output the watershed boundaries and calculate streams. As you can see below, the threshold value would need to be adjusted before it more accurately depicts the streams actually found in the canyon.
Day 18: Atmosphere
Today I decided to be a little more abstract with the prompt. Having attended the BYU football game today, I decided to look at the ‘atmosphere’ of football stadiums across the country. According to supertailgate.com, these are the top 25 loudest stadiums in the US. The #1 Stadium, Tiger Stadium at LSU, even managed to register an earthquake on the Louisiana Geological Survey seismograph in 1988!
I also went with a white and blue symbology to represent BYU. Go Cougs!
Day 19: 5-minute map
I created today’s map using dominant vegetation species data from UGRC. With the data already uploaded into ArcGIS Pro, I was able to manipulate the symbology and create the map layout here in 5 minutes.
Day 20: Outdoors
Each year I hike Mount Timpanogos on the Aspen Grove Trail with my dad and brother. So far I’ve hiked it 11 times! This hike is 16 miles round trip and around 5,000 feet of elevation gain. I love this hike and the time I have to spend with my family.
I made today’s map using trail data from UGRC.
Day 21: Raster
Dust storms are an increasingly prevalent problem in Utah. Dust emitted from playas has a variety of potentially harmful effects on the environment and human health, causing diseases such as valley fever, asthma, and pneumonia in humans, earlier snowmelt and decreased runoff from mountain snowpack, and carries many organisms and metals that can affect air quality and water resources. Understanding dust sources will help us mitigate the hazard moving forward.
To identify areas mostly likely to be dust sources, we considered soil type, slope, and vegetation cover using NDVI. We expect soils with smaller grain sizes, like silts and clays, to be more available for wind transport. Similarly, we expect large, flat regions with no vegetation to have the greatest potential for dust production.
I created a model with ModelBuilder in ArcGIS Pro that uses a 30m DEM, polygon soil data from UGRC, and Landsat 8 imagery from EarthExplorer to identify likely dust sources. Twelve Landsat 8 images (RED and NIR) were taken from Summer 2020, mosaicked in ArcGIS Pro, and used to calculate NDVI. The 30m DEM was used to identify slopes <5%, and the resulting NDVI, slope, and selected soils were reclassified and weighted against each other for the final output shown here.
Day 22: North is not always up
I made today’s map using public data from IBCAO and NOAA. At the North Pole, every direction is pointing south, so which direction is north?
Day 23: 3D
Another view of my favorite hike up Mt. Timpanogos!
Day 24: Black & White
Today I decided to do my hometown of Springville, Utah. I created this map using road and parcel data from UGRC.
Day 25: Antarctica
I made today’s map using data from SCAR Antarctic Digital Database.
Day 26: Minimal
Today’s map was inspired by minimalist maps I’ve seen on Etsy and in home decor. I used data from the Alaska Department of Transportation Open Data for the streets and parcels. I really love throwing together simple maps like this!
Day 27: Dot
I’ve been blessed to have so many opportunities to travel and study all around the world. Each of these “dots” represents a place I’ve visited or a place I’m hoping to go in the future! I’ve traveled to more places than I can remember in Utah, so I’ve just highlighted a few here on the inset map.
Day 28: Is this a chart or a map?
For today’s map I referenced elevation and distance data from AllTrails for the Mount Everest trail via South Col. I created this chart (or map?) on Excel and made a custom layout on GIMP. If you need a good laugh, I recommend reading through the reviews on AllTrails for this particular hike (link below).
Day 29: Population
Today’s map was made using world population data in a public database from Nordpil.
Day 30: My Favorite!
My favorite is GIS! I’ve loved exploring both the art and science aspects of GIS, combining research and models with fun cartographic elements to tell a story. These last 30 days have been so much fun for me! I feel so lucky that I get to do this for work. Thanks to everyone who took the time to look at my maps!