Geography 292: Geospatial Analysis with Web GIS

My first app is a map of the U.S. which displays forest cover percentage by state. It is a 3D extrusion map, and each state is elevated based on forest coverage. https://owugis.maps.arcgis.com/home/webscene/viewer.html?webscene=e3fd8f2b7db14c5384b62e80ccff4afb

The second map I made was made in experience builder and shows campsite availability at Delaware State Park.  This map is more of a proof of concept, as I could not find exact coordinate data for each site and decided to do only 25 of the 214 to not make the map too cumbersome. It contains real-time editable data based on site availability that could be changed by park workers, and includes a list of sites and their availability as well as a filter function based on availability. https://experience.arcgis.com/builder/?id=85b5145b3d8a468a882d661ff3eef2ac

 

For the first application I finally finished a geographical profile of the Jack the Ripper murders of 1888. This was a very hard project for me to do as many of the addresses listed as the crime scenes are on streets that have different names in the present day at best and no longer exist at worst. I did my best to find any geographical information on the crime scenes but given the fact I am working with a large scale map, any errors would likely be relatively minor, (getting building numbers wrong, ETC.) something that was very helpful in creating this was the pop ups which helped me label the crime scenes, write details on the victims, and attach photos/drawings of the crime scenes.

https://owugis.maps.arcgis.com/apps/mapviewer/index.html?webmap=82b656f6de5a44adafeca2ca3932199d

My second application was a more fun one, it was tracking the path of the Zeppelin L-59 on its famous journey from Bulgaria to German East Africa in 1917. (Though the flight was unsuccessful due to an abort message being sent.) Here I had a lot more freedom to indulge in the many features of ArcGIS online, such as physically drawing L-59’s flight path, adding data points where L-59 was built, where her hanger was, and her approximate destination. Working this really put into perspective just how far the Zeppelin had traveled and I had so much fun with this I might even get my own personal ArcGIS account to track other long distance airship flights.

https://owugis.maps.arcgis.com/apps/mapviewer/index.html?webmap=ea6c9d0aad494e12b60c1893f57a1a58

My first application I found data using the atlas on live stream gauges in rivers and streams all across the United States. I opened this map and found there was a lot of data useful and able to change from things I learned specifically chapter 2. I messed around with changing the color of different water levels making red high or flooded level and blue low or regular level. I could also change the size of the bubble to how high the water level is.  I also added an attribute of USA Short-Term Weather Warnings to show where water levels may rise because of a storm. This map can be useful to fisherman any where around these rivers and streams. For example if a fisherman wants to see the water level of Alum Creek at the present time and compare it to the level of the Olentangy River they can click on the river location and see the exact height at that given time. 

 

https://owugis.maps.arcgis.com/apps/mapviewer/index.htmlwebmap=ce1547fd4cd0426398301663978dc896

The second application is making a map that charts the location of a fish catch and other information like weight, size, location, and any other description about the fish you want. This could be useful for tracking a fishing tournament when you are trying to track where the biggest fish were caught. It can be used by a tournament director for tracking lots of fishermen’s weights over a period of time. It could also be used by an individual fisherman who just wants to find out where he catches most of his fish. Using chapter 6 I used gauges on a dashboard to display the sum weights of different areas where a fish was caught. There is also the original map of the locations of the fish catches on the dashboard. This is just an example I made up using hypothetical fish catches in the pond in front of Meek Aquatic Center. 

https://owugis.maps.arcgis.com/apps/dashboards/5ca290f675a64cacab1f327622bfe4dd#mode=edit

My first App was based around the content covered in chapter 3, which had the option to utilize both 3D and 2D maps within the same application in order to visualize the information in multiple different ways. I created a section widget and added two separate maps within it, with one being 2D and the other being 3D. The topic I chose to base my maps on was the distribution of lanternflies, an invasive species of planthopper, throughout the eastern side of the U.S. To create some differentiation between the 3D and 2D map, I added 3D terrain to display the dispersal among different levels of elevation. 

https://experience.arcgis.com/experience/48b3ae5f797f46d1a84316a1e34e651e

I had made the second app pulling from concepts covered in the tutorial of chapter 6, which covered the bases of real time data tracking on ArcGIS. The data I decided to cover was centered around deer road kill reports in Washington, which are tracked by salvage permit holders. I thought it would be interesting to see if the rate of reports changed in the presence of a predator, so I also added a dataset displaying the different recorded wolf packs around the state. In reference to chapter 6’s content, I made sure that both the wolf and deer road kill datasets had tracking timelines that continue into the present, which means that they are updated regularly. In order to flesh out the map a bit more, I added highway markers and popular scenic roads. I thought it would also be cool to add cameras as well, showing different highways in a zone with higher rates of deer kills. 

https://owugis.maps.arcgis.com/apps/instant/atlas/index.html?appid=0b4175d9e182488f83fc9255e1c87ae9&webmap=3dde4572a5ca44e3890bfe1826b89f9c

For my first app, I followed the chapter tutorials to create an app to help users see the overlap between invasive plant species and park boundaries across Ohio! Using the Overlay Layers tool, I was able to identify specific ‘Conflict Zones’ where native habitats are most at risk, and highlighted them. I think this app can be very helpful in showing exactly where invasive species are crossing into parkland. It also turns a complex problem into a simple map to look at for park rangers and volunteer groups!

Application 1: https://arcg.is/0SueCv1

For my second application, I made a 3D Web Scene. I used Esri 3D Buildings to model the urban canopy of Delaware, Ohio. The goal was to visualize how sunlight and shadows interact with Delaware’s urban landscape. Using the Daylight and Shadow tool, I was able to show the overlap of building height and orientation with  solar energy accessibility, and how it affects it. This project applies a lot from the 3D visualization techniques in Chapter 7. I think this app could be benifical to show planners the ‘shadow gaps’ that urban buildings create, and maybe it could help them try and consider installing sustainable energy infrastructure in the future. 

Application 2: https://owugis.maps.arcgis.com/apps/instant/3dviewer/index.html?appid=a76ba7597ebf48018758f9217bacb9a7 (When opening the app, click on the small sun icon in the bottom right to see the shadow animation cycle through the Winter Solstice.)

 

This is my first application, a survey based on people’s knowledge and likeliness of living in certain states. This was really fun and pretty straightforward to complete. I liked creating the maps and choosing which states to put in for the questions. https://arcg.is/0Oq4HD0

This is my second application, a story based on the nature preserves in the Columbus area. There are a few different areas of the map highlighted so try and zoom in on different areas. https://storymaps.arcgis.com/stories/3b7b3d90a80b4c3aa966c9983b25abb9

Chapter 7:

3D web maps are called web scenes or 3D scenes. Photo-realistic scenes try to make objects look as accurate as possible. Cartographic are often used for display information like population density and zoning laws.

Surfaces: continuous measurement, typically elevation, often referred to as digital elevation model (DEM), digital terrain model (DTM)- bare ground, or digital surface model (DSM)- ground surface and objects on it.

Features: On, above, or below surfaces. May be 2D or 3D. Operational layers of the 3D map.

Textures: covers of 3D features

Atmospheric effects: lighting, fog, etc

3D object scene layers: represent and visualize 3D objects

Building scene layers: shows complex digital models of buildings that you can interact with – materials, properties, locations.

Point scene layers: cached point scene layers are thinned so that certain details are only visible at certain zoom levels to display large amounts of point data that wold take too long as a point feature layer

Voxel scene layers: multidimensional spatial and temporal data in 3D volumetric visualization

I struggled for a minute to find where Elevation mode and Absolute Height could be configured in the Style pane because they are now under Layer Properties rather than Layer Style. Once I figured out where those were, figuring out where everything else is was pretty intuitive.

My computer is really struggling with the 3D scenes, especially the last one since someone has put a giant helicopter in the publicly edited scene.

Application:

A potential application of chapter 7 is to create a tour of where I grew up, since I’d like to show my friends, but it’s too far away for me to bring them there in person. I would use the OpenStreetMap Style 3D Basemap and add paths and way-points that show pictures that I have of some of my favorite places.

My first application is a guide to volunteer opportunities at environmentally-focused organizations around the Northwest Ohio area. Since I am from this region, I’ve spent a lot of time with these organizations, and I wanted to compile an accessible list for people who might be new to the area and have an interest in environmental action or volunteering. This could also be helpful for high school or college students looking to build their resumes and create relevant professional connections.

https://owugis.maps.arcgis.com/apps/instant/attachmentviewer/index.html?appid=367f2301ee7a4af083e8730b9f86bd83

My second application takes heavy inspiration from the United States Population and Population Density web scene that we worked on in Tutorial 7. I did something similar and made a 3D extrusions map with the total population of each US state. I created slides with snapshots of different parts of the country so as to see more closely some of the population discrepancies between states.

https://owugis.maps.arcgis.com/home/webscene/viewer.html?webscene=239e11a0bc464c07bb5f02a2bbbccdb8 

In chapter 7 of the textbook Getting to know Web GIS, the main focus was on 3D web scenes in ArcGIS and how they expand traditional 2D mapping into a more realistic experience. Instead of just looking at flat maps, 3D scenes allowed me and other users to visualize height and depth more clearly. These 3D scenes are called web scenes, which can include different types of layers such as feature layers, scene layers, and elevation surfaces. It was somewhat interesting to learn about the difference between photorealistic scenes and cartographic scenes. In scenes that are photorealistic, the use of imagery is applied in attempt to mimic the real world.  On the other hand, cartographic scenes use symbols driven by data. These symbols can include color and height, further representing information such as population density. This makes 3D useful not just for visualization, but also for analysis. The chapter also explained different scene layer types, with each scene layer helping users’ model entire landscapes and buildings. Some of the scene layer types discussed were 3D object layers (buildings), point clouds (LiDAR data), and integrated mesh layers (from drone imagery). These allow GIS users to model entire cities, buildings, or landscapes in detail. Moving on to the actual tutorial part of the reading, it showed how to actually build a 3D scene in Scene Viewer by adding layers (with the addition of styling them) and editing features. I liked how you can interact with the scene: rotate it, measure distances, and even simulate sunlight and shadows. The textbook made a connection between 3D GIS and newer technologies like VR, AR, and the metaverse. This link was interesting to me because it shows how GIS is expanding beyond just maps into immersive environments. This system is ever evolving and will be in use for years to come. I think 3D GIS makes maps way easier to understand, especially for things like cities or buildings. Seeing height differences visually is more intuitive than trying to interpret numbers on a 2D map.  At the same time, it feels more complex than 2D mapping. There are more settings (like elevation modes, z-values, and symbol configuration), which can be confusing at first so many buttons! However, once you get used to using this application, it becomes a powerful tool you can keep handy.

Application Idea 
One application idea for this chapter’s content would be creating a of a local park using my own collected data. For example, I could map trees, benches, and buildings as point and polygon layers, then use extrusion and 3D symbols to make them realistic. I could also include underground features like pipes or utilities if data is available. This would help visualize how space is used and could be useful for planning improvements or studying environmental patterns.

 

Chapter 5:

Raster tile layers are large and can take a long time to render, but once they are created, they are an important piece that works well as a base for other projects.

Vector tile layers are smaller and can be updated easier because it generates tiles based on data density.

Map image layers are mostly used for large datasets that need server-side rendering.

Map layers aren’t reusable because it’s rare for two map requests to cover the same data. All map requests read from the database and generate after the request, so they take the most time. Raster and vector tiles don’t read from the database because they are already cached or generated on the web server, so they are faster. Feature tile requests must be generated the first time they are requested, but will then be cached in the web server and faster to load.

Raster layer: the labels don’t rotate to stay upright, it is less clear, and it doesn’t display when zoomed too far. Vector layer: the labels stay upright when the map is rotated, it is clearer , and it displays at closer zoom levels.

Chapter 6:

Spatiotemporal data is observations of objects and events that change over time.

Moving: something that moves such as live feeds of vehicles.

Discrete: something that “just happens” such as earthquakes, geotagged feeds, criminal incidents.

Stationary: stands still but values change such as wind speed and direction from a weather station, highway traffic speed.

Change: change or growth such as perimeters of wildfires and floods.

Application based on 5 & 6:

I could make an application that tracks when the trees around campus drop their leaves, grow new leaves, grow flowers, grow fruit, drop fruit, etc. Pairing it with a gauge noting how many are flowering, growing fruit, etc. a list of what types of trees they are, and a map that shows where they are on campus.