Geography 292: Geospatial Analysis with Web GIS

(I thought this was posted already but it never did so I am rewriting it now)

Chapter 1:

This chapter had similarities to what I did in Geog 291, but was different since it is applied to ArcOnline. I started strong but quickly got confused when trying to upload the Redlands data. As I continued, I was able to familiarize myself with each of the tools and discovered there is a lot you can do. I think this chapter was well explained, but lacked some necessary pictures, I felt I needed to better understand what I was doing. As I navigated through 1.4 I ran into another issue, I was unable to complete step 11. I could not find the “select layer field of sort by”; anytime I clicked where it would be, it disappeared. I reviewed other students’ maps in our organization to see what they looked like since mine did not end up looking as it should.

Chapter 2:

For chapter 2 it focused on Smart mapping and storytelling with GIS. The first tutorial was to create a feature layer using geocoding. I had to download the data from the main website onto an external drive. The tutorials were relatively easy compared to the first chapter. In tutorial 2.2 I was able to stylize all of the needed arrows and colors however it didn’t look quite right. I ran into another problem in the third tutorial when trying to use expressions to calculate things. Towards the end of the chapter we created a story about US population change. I had trouble stylizing some things in the story but I believe it looks as it should. I didn’t run into very many problems in the last tutorial the chapter. Overall, the story i created conveyed the proper message asked by the book.

Application:

An application could be made about the population change in Delaware. I’ve heard from many people that Delaware has quickly became a very populated area in a short amount of time. I could create a story map showing how many people have moved here within the last ten years and where they chose to within the city.

 

Chapter 6 Spatiotemporal data and real-time GIS

This chapter introduces the concept of spatiotemporal data and the values and challenges of the Internet of Things (IoT) in relation to ArcGIS. Spatiotemporal data can be categorized into groups: Moving (live feeds of airplanes, buses cars etc.) Discrete (criminal incident, earthquakes), Stationary (wind speed and direction measurements at weather stations) and CHange(perimeters of wildfires, flooded areas). In spatiotemporal GIS data, the time value of an event can be a point in time or a duration of time. 

Application:

I was really interested in the idea of spatiotemporal data because this chapter was my first time hearing about it. When looking at the Delaware data from GIS 291, I think a good application would be one that is similar to my final from GIS 291, creating a spatiotemporal application that maps emergency incidents. By using available data, the application would display real time emergency incidents as moving or discrete events on a web map. This would include filters by incident type, time of day or severity. It would animate changes over time to identify got spots or trends in emergency services. This application could be deployed as a web app using ArcGIS Enterprise.

Chapter 3 

This chapter introduces Experience Builder and shows us the basics such as templates, themes, widgets, pages, windows, layouts, ect. It also talks about using Experience Builder to create web experiences. A widget is a JavaScript and HTML component that encapsulates a set of focused functions. Experience Builder provides basic and layout widgets. Tutorial 3:1 is about using Experience Builder to create a web app. It was interesting to learn how to create a simple ‘web experience’. I got a little stuck on tutorial 3:3, I could not find the statistics tab in the dynamic content window,  so I moved on to 3:4.  I was unable to complete 3:4. The beginning of the tutorial had me drag the table widget onto the page and then in the settings pane click ‘new sheet’. However, there was no “new sheet” button in the contents pane so I could not finish it. 

Chapter 4- mobile GIS

This chapter first starts off with an overview of mobile GIS.  There are lots of advantages to mobile GIS but because of the size of mobile devices, CPU speed, memory size, battery power, bandwidth and network are all limited.  The first tutorial is Design a survey for ArcGIS Survey 123. It was just making a survey. It was easy, except in step 13 it said to “click the Incident Type question, and click Set Rule icon”, which was impossible to do because there was no Rule icon where the book said it was going to be nor anywhere else I looked. This did not ruin the rest of the tutorial for me though. The next step was to download an app on my phone for the survey I just created. 4:3 was fine, but there was no “change style” button underneath the layer name that I could see, so I could not do that section. 

Chapter 1- get started with Web GIS
This chapter introduces the fundamentals of web GIS, outlining its benefits and key components. The basic components of a web GIS app are the base maps, operational layers, and tools. The chapter also emphasizes the power of web GIS to provide real-time data and accessibility across various devices and groups of people. It explains how cloud computing, web services, and APIs facilitate data sharing and integration. The first tutorial was easy once I got going. One of the first things I had to do was make a web map made from data downloaded from the ArcGIS website. Then we had to create an instant web app using a template.

Chapter 2 – smart mapping and storytelling with GIS
This chapter continues discussing feature layers and web apps by first introducing feature layers and the different ways to style them using smart mapping. The tutorials for chapter two were also very straightforward and easy. The first one was just editing names from data imported from Microsoft excel. I got a little stuck on 2:2. When making the style for the map of the top 50 US states, the data for 2020 and 2010 was switched (the directions were to style the Census 2020 data with the theme “above and below” but there was no option for the 2020 data) . 2:3 had some coding, but it was easy to follow.

Chapter 7 mainly talks about 3D web maps, and how they can be used to create more immersive and interactive data visualizations. There are two main types of web scenes, photorealistic which is exactly what it sounds like, 3D maps that are very similar to the real world feel of an area. Conversely, there are cartographic 3D maps which are used to make a better visualization of more traditional map elements. In either case, textures, surfaces, and features of 3D web scenes can be used to help users have a better understanding of the area through more evident spatial relations and scale. I also learned about Lidar, which is a laser technology that is used for sensing and the creation of 3D maps, and how it can specifically be used to map elevations and man-made structures. Additionally, tools within Web GIS like Web AppBuilder give everyday users the ability to build web apps with widgets like Query and Filter without the requirement of coding knowledge, making data visualization and map creation much more accessible. Finally, chapter 7 discussed the growing role of more immersive technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR), as well as indoor GIS and the concept of the metaverse, this highlights how GIS is growing into more engaging, game-like digital environments. One application of a web scene environmentally could be to create a forest canopy web scene for Delaware County. Using Lidar elevation data and time-enabled layer, this type of app could help to visualize forests and green spaces in our community and their shift due to urbanization. This resource would be useful for awareness of our impact and to help with further planning.

Chapter 6 discusses spatiotemporal data, which is information that is attached to a specific time and location, and it really highlights the real-world applications for this type of data using web GIS. I thought it was cool that this data can be helpful in such a wide range of fields like emergency response, environmental monitoring, and business operations. Another big part in this chapter is the Internet of Things (IoT), an extensive network of devices that includes things like traffic cameras and air quality monitors that are continuously transmitting data. It reinforces how this continuous live data is fed into real-time GIS systems, which can be used to track patterns and movement over time. Tools like ArcGIS Dashboards and time-enabled layers help visualize and animate this data, making it easier to monitor and understand dynamic systems. I found it eye-opening how easily this technology integrates into everyday life, from smart homes to tracking vehicles. It is both very interesting to me, and just a bit unsettling. This technology clearly has the potential for a lot of good and helpful uses, but could also be used for unfortunately bad purposes. One application for this type of technology and data mapping that would be interesting to me is sometype of wildlife tracking dashboard of Delaware County. This could be accomplished using real-time data from gps collars, trail cameras, and sensors. It could show animals movements over time and display weather patterns and human activity. It would be a very useful tool for determining how animals move based on other changing conditions.

Application One

For my first, application, I created a mobile tool to trach communicable disease cases in Delaware. However, this tracker allows people to go to the case location and upload any photos or other observations that be important for the outbreak. I had no issues creating the tool and adding a map, however it would not let me publish it for an “unknown error” but I was able to get some screenshots in the preview mode, which are below!

 

Application Two

Application two actually uses the data from the survey to create a live communicable disease dashboard! Because I could not publish the survey, sadly there was no fake data that I could add to the dashboard to create cases. However, a screenshot is below. The map is designed to have a pinpoint for each case, as well as a pie chart for overall cases and then a gauge for TB causes so that TB is highlighted due to recent TB outbreaks in the US. https://owugis.maps.arcgis.com/apps/dashboards/d4b18541a860435a9edf8d1bdca81bf9#mode=edit

Data Inventroy

Address Point: represents all certified addresses in Delaware County. These addresses are updated daily and the updates are published once a month. 

Annexation: annexations and boundaries since 1853, annexation just means territory here. 

Building outline: this set is of building outlines and structures for all structures in Delaware county. It was last updated in 2023. 

Condo: All condo polygons within Delaware county. 

Dedicated ROW: lines that are designed Right-of-Way. This data is updated daily and published monthly. Consists of all dedicated road right of way polygons in the county. 

Delaware County contours: 2018 two foot contours, topography of the county?

Delaware County E911 Data: Uses address point data to reverse geocode coordinates to determine the closest emergency services location. Updated daily and published monthly. 

Farm lot: identifies farm lots in both US Military and Virginia Military Survey Districts. 

GPS: all GPS monuments that were established in 1991 and 1997. 

Hydrology: All major waterways in Delaware County. 

MSAG: master stress address guide. Used political jurisdictions in the townships, cities, and villages within the county.  

Map sheet: all map sheets within Delaware county. 

Municipality: all municipalities within Delaware county. 

Original township: has all boundaries of the townships within the county before tax districts change their shapes. 

PLSS: public land survey system polygons are used for the US Military and the Virginia Military Districts for Delaware county. 

Parcel: represents all cadastral parcel lines within Delaware County. These geometries are maintained by the Delaware County Auditor’s office. 

Precinct: consists of the voting precincts for Delaware county under the data of the Board of Elections

Recorded document: recorded documents in Delaware County Recorder’s Plat Books, Cabinet/Slides and Instruments Records that would not be represented by the subdivision plats that are active. This is used to track down miscellaneous documents within the county. 

School district: school district boundaries within Delaware County. 

Street centerline: center of pavement in public and private roads within Delaware County. This was developed by address information. 

Subdivision: subdivision and condo records for Delaware County. 

Survey: shapefiles of point coverage that are representative of surveys of land within the county. 

Tax district: tax districts defined by the Delaware County Auditor’s Real Estate office. 

Township: data of 19 townships that make up Delaware County. 

Zipcode: all zipcodes within Delaware country defined by the 2000 census, the postal service, and the tax mailing addresses.

 

 

Chapter 7 introduced 3D web maps, or web scenes, and showed how they make interpreting and analyzing data more intuitive and engaging. I liked learning about different scene elements like surfaces, textures, and atmospheric effects, and I thought the texture features made maps much easier to understand. The chapter also introduced Lidar, which uses laser-based point clouds to measure elevation and other features. I explored how to use Web AppBuilder to create interactive web apps with themes and widgets without coding, and I found it helpful to see how different tools like Query and Filter widgets can make apps more dynamic. I also found it fascinating how 3D technologies like VR, AR, and indoor GIS are being used to create detailed, immersive maps.

An app idea would be to use 3D maps to show in my home time Louisville, Kentucky and maybe show some patterns with Derby participants since the Derby is coming up. People up here at school most likely have never been and it would be fun to show people how huge it actually is at home.

Chapter 6 introduced spatiotemporal data, which connects information to both time and location, and showed how it’s used in real life GIS. I found it interesting how real-time data can support emergency response, environmental monitoring, and business operations. The chapter explained different types of spatiotemporal data, the role of IoT devices, and tools like ArcGIS Dashboards and time-enabled layers. It was really helpful to see how live data can be visualized and animated to track changes over time.

In Chapter 3, I learned about the ArcGIS Experience Builder, which lets you create custom web experiences with flexible layouts and interactive widgets. It’s really useful when a standard web app doesn’t meet your needs. The tutorials were helpful, but it took some time to get used to working in a web-based environment after using local software all semester. I liked how the Experience Builder can make GIS more accessible even for people with little experience.

Chapter 4 focuses on how mobile devices are becoming the main platform for Web GIS. I thought it was really interesting that GIS can even work on wearable devices like Apple Watches. I also liked how the chapter introduced different Esri mobile apps and explained them clearly. The idea of rapid data collection and the shift toward mobile GIS made me realize how important it is to access data quickly and easily, especially in the field.

One application would be a wildlife tracking app where users can log wildlife sightings (species, location, time, photo) directly from their mobile devices. Using Web GIS, the data could be mapped in real-time to help conservationists monitor animal populations, migration patterns, or even invasive species. The Experience Builder could make it easy for users to view maps, contribute data without needing coding experience, and even get alerts if they are near sensitive habitats. This would help connect everyday people to environmental research while building a large, useful dataset for scientists.