Geography 292: Geospatial Analysis with Web GIS

Chapter 5: ArcGIS Online is used for creating layers and web apps for the public, but ArcGIS Enterprise is used for building a private Web GIS. ArcGIS Enterprise is used in situations where there is a need for on-site Web GIS (no internet or government regulations), hybrid Web GIS (keep their own infrastructure), and functions only available with ArcGIS Enterprise due to security. Both ArcGIS Online and ArcGIS Enterprise can create multiple web layer types. A raster tile layer is commonly called a tile layer and delivers maps as image files. They are commonly used as basemaps. Vector tile layers deliver maps as grouped vector files in PBF. Vector data is usually smaller than raster data and can be generated much quicker. Map image layers can be drawn using tiles and are used much less today. They can be used for color-shaded relief and large datasets. Feature services can create feature tiles on demand. Map image layer requests are not reusable and run slowly. Raster and vector tile service requests are precached on the web server and are faster than map image layers. Feature layers are used for editing workflows and changing data. If the data is only used for visualization, use raster or vector tile layers. To use ArcGIS Pro to create web layers, you have to prepare your data using ArcGIS Pro, remove unused layers and complex symbols, and then share the web layer and verify it in your ArcGIS Online or Enterprise portal to confirm it is working correctly. When sharing to ArcGIS Enterprise, you can choose to reference registered data or copy all data.

Chapter 6: Spatiotemporal data moves or changes over time. It is categorized into four groups: moving, discrete, stationary, and change. Discrete data is something that “just happens,” such as crimes and earthquakes. The time value is stored in a single attribute field if it happens in a moment, and stored in two attribute fields if it has a start and end time. IoT is the network of devices embedded with sensors that allow them to collect and exchange data. These devices can be things like airplanes, lights, and security cameras. Enterprise IoT applications include smart cities and environmental quality monitoring. Consumer IoT applications include connected cars and smart homes. Geolocation provides context for the IoT ecosystem to understand values. ArcGIS Velocity and ArcGIS GeoEvent perform continuous data processing and analysis, and send alerts when specific conditions occur. ArcGIS Velocity introduces feed items, real-time analytic items, and big data analytic items. The poll method is where a client periodically polls the server to retrieve new data. The push method pushes data to a web client, which is good for analyzing real-time data. Mission is a real-time situational awareness product that helps coordination among a team. It is good for emergencies and military operations. Mission Manager is the web app where missions are created, and Mission Responder is a mobile app that allows location tracking and geomessaging.

Application: You can create a map comparing air quality and temperature, and then create an app that shows how air quality changes over the course of a year.

Chapter 5

In this chapter, I learned how Web GIS can be built not only on the public cloud using ArcGIS Online, but also through “on-premises” systems with ArcGIS Enterprise. On-premises means the system is locally hosted. This is especially useful when security or specific functionality is needed. I explored the similarities and differences between ArcGIS Online and ArcGIS Enterprise and found that they share more in common than they differ. I also learned about three main types of web layers (vector tile, raster tile, and map image) and when each type is most appropriate to use compared to feature layers. The tutorial in this chapter teaches how to connect ArcGIS Pro to portals as well as publishing the different web layers previously talked about. This chapter is useful even if I don’t plan on using on-premises Web GIS because most of this applies to online GIS as well!

Chapter 6

Chapter 6 is all about a very interesting concept: real-time GIS! This software is used to deal with and gather data from objects and events that move and change through time. Data can be generated via mobile phones, sensor networks, smart cities, and the IoT. The IoT was a concept I had never heard of before. It stands for the Internet of Things, and is a large sensor network that collects and exchanges data from any physical object that has sensors and network connectivity. Also in this chapter were different types of spatial temporal data. Dynamic data follows something that moves, like an airplane. Discrete data is happening events, like a car incident or an earthquake. Stationary data is collected from something that stands still but has fluctuating values, like wind speed at weather stations or street traffic speed. Change data is the final type discussed in the chapter, and tracks change or growth- like urban sprawl or or land cover changes. I really enjoyed reading about the variety of spatial temporal data that can be collected.

Future Application

Using spatial temporal data from a geodata base, you could make a raster tile layer or a map image layer to display the change in wooded growth outside a conservation area, or really anywhere to track the movements of deforestation. This would be helpful to monitor how widespread deforestation becomes, and how the surrounding landscape changes shape over time.

Chapter 5: 

Chapter 5 discusses something called ArcGIS Enterprise. This is another form of ArcGIS web services that allows the user to create high-performance WebGIS systems, but has key differences from ArcGIS Online. These differences make it useful for organizations or individuals who want to have more security and privacy. For example, ArcGIS Online has its data stored on a cloud managed by Esri. ArcGIS Enterprise is housed on a more customizable/private on-premises system that the organizations can control themselves. This ability also makes it possible to operate with limited or no internet access.  

Another key concept from chapter 5 was tile caching and tile layering. Caching is a method of storing pre-rendered map tiles at different scales so they can be retrieved and displayed quickly to users, instead of rendering the map from scratch each time a user interacts with it. This helps improve the performance of web maps by significantly reducing the load time. When discussing tile layering, the chapter refers to many different types of layers that are used for different purposes. For example, Raster and Vector files. I was already very familiar with the concept of raster and vector from my background in graphic design. I knew that raster files are made up of pixels and tend to lose quality when scaled up. Vector files are composed of mathematical paths/points that allow them to maintain sharpness and clarity at any size. I never thought about how these could also be applied to GIS tile layers. Raster tiles could be great for static map imagery, but they can lose quality when zooming in. Vector tiles are more flexible as they maintain good clarity at different scales, making them generally more efficient for interactive maps. 

Chapter 6: 

Chapter 6 introduced spatiotemporal data. Meaning data that can be tied to a specific location and continuously changes over time. You can track and collect spatiotemporal data from certain things that often change over time, like moving vehicles, weather patterns, or pedestrian movement. Because these things are constantly changing, they need to be continuously updated. This chapter introduces Real-time GIS as a solution. Real-time GIS utilizes spatiotemporal data, as it can continuously collect and process the incoming spatiotemporal data so users can monitor changes as they happen. A key distinction can be made between two types of spatiotemporal data: point-in-time data and duration-of-time data. Point-in-time data captures an observation at a specific moment, like where an object or event is located at one exact timestamp. These data points of collective events can be compared to each other. Duration-of-time data captures how an object or event changes over a continuous interval of time, observing the start to finish. 

Chapter 6 also discusses the Internet of Things (IoT). This refers to the existing network of devices that are embedded with sensors, software, and other technologies that allow them to exchange data with other devices and the internet. Together, these “things” (smartphones, household appliances, vehicles, etc) contain a vast amount of raw data, especially spatiotemporal data. This network of devices/data can be utilized by GIS applications and turned into useful real-time geographic information systems. The example the chapter used to show this concept, being smart cars, allowed me to understand this concept better, as I often see this system being used in my day to day commute without thinking about its connection to GIS until now. 

Application: 

   An application based on ideas from Chapters 5 and 6 could be to create a traffic monitoring system for the area using available spatiotemporal data. I could collect publicly available data on vehicle movement at major intersections and roads from traffic sensors, and note the location/ time to track how traffic patterns change. This data would then be managed and stored in an ArcGIS Enterprise system, where it can be privately organized and efficiently accessed without the internet for analysis.

Chapter 5: 

This chapter introduces another different form that ArcGIS Web can take, called ArcGIS enterprise, which has been described to be a more private platform of ArcGIS Online. I have noticed that there are key differences between ArcGIS Online and ArcGIS enterprise, such as the database that they run on. ArcGIS online’s data is kept on an online ESRI cloud, while ArcGiS enterprise is maintained on a more user-managed structure. This type of format can be used for organizations, such as governmental programs, that require a non-public cloud or no internet connections. I find it interesting that there is also a hybrid version of GIS that is offered as well that provides personal layers while continuing access to ArcGIS online layers. Through the chapter I had also learned that ArcGIS enterprise is also an on premise tool, which makes sense when considering the lack of internet accessibility that the platform provides. Additionally, it runs on a geospatial content management system called Enterprise portal, which helps to create different types of hosted layers, host web-mapping apps, search for GIS content, and manage your organization’s utility services. There is also an ArcGIS server that helps to host different types of web services, which is quite cool. For ArcGIS online and ArcGIS enterprise alike, there is a way for organizations to collaborate by sharing content in groups. I believe that I remember reading about the hierarchical sharing system within one of the earlier chapters. The chapter had also touched upon visual data aspects, such as the vector and raster layers. 

Chapter 6:

Chapter 6 discusses the concept of real-time ArcGIS, which is intended for data that changes on a regular basis and needs to be continuously updated. It makes sense that this platform has been developed as more advancements get created in favor of electronic field data collection, as a database must be created to compensate for it. One type of data type that is housed on real-time ArcGIS is spatiotemporal data, which is data generated from sensors or simulated models, which can consistently generate more data which needs to be entered into the dataset. Spatiotemporal data seems to collect data on factors that change over time, such as transportational objects, events occurring, or environmental changes. That type of data can be further separated into two types, point in time and duration of time. The difference is that point in time observes collective events that occur and when they happen, while the duration of time looks more at the whole start to finish of a continuous event. It also delves into Iot, which is a network of objects attached to sensors that can exchange data at a regular rate. This seems to primarily refer to technological data such as planes and other automobiles. It was interesting to see how much technology tracking is integrated into different aspects of my life that I don’t usually think about. It leaves me wondering what other types of data are being collected from my daily activities. 

Applications: 

A possible idea that could be pulled from chapter 5 could be to test water quality at different locations of a body of water, which wouldn’t necessarily need on sight GIS data management, as water testing may need to occur within a lab. From within that lab, data could be analysed and entered into a GIS database, in order to visualize the areas in which different types of water quality traits differ, and their adjacence to urban areas. I found coming up with an application from chapter 6 to be quite smooth, as it is a type of data that can have such a wide variety of uses. One of the possible applications could be to collect data based on how many cars pass through areas with notably high deer populations, possibly combining another dataset containing deer sightings in order to form a more full picture. The purpose of this could be to understand which areas infrastructure designers should invest in highway fences, in order to lessen the rate at which deer-related crashes occur.

Week 5 went with no issues, a very simple chapter, but definitely a useful tool for moving data into the cloud and formatted correctly. It describes using Vector and Raster tile layers, which is which, and what use cases each are best suited for. I only wish that the tutorial didn’t require ArcGIS. Week 6 was also pretty self-explanatory, though I had issues getting the actual slider to work when playing the data. When I moved it myself, it would show a change, but it didn’t show any data on its own. Though it was interesting to work with temporal data and see how it could be mapped.

 

I had an idea to show population growth over time with different forms of transportation. There would be multiple tabs for each. Cars would be measured by the number of cars on the road, Trains would be recorded by track mileage, and planes would be measured by the number of flights.

Chapter 5

This chapter introduces ArcGIS Enterprise, its components, and its supporting platforms to build a private WebGIS. ArcGIS Enterprise and organizational subscriptions to ArcGIS Online are complementary implementations of Web GIS. They provide similar functionalities, such as a portal website. ArcGIS Enterprise on Kubernetes is a new deployment option that accompanies Windows and Linux as supported operating systems for ArcGIS Enterprise using microservices and containerization to provide a cloud-native architecture. Map image layers can be drawn dynamically by the server or by using tiles from a cache. Map image layers and feature layers are appropriate for visualizing operational layers. Feature services can generate feature tiles on demand when requested by newer ArcGIS client apps which enable web clients to display more features from the service and provide faster load time by generalizing complex geometries for display. Standards specify the interface that different vendors should use and are an important way to achieve interoperability among different vendors. You can publish web layers using ArcGIS Online and ArcGIS Enterprise web pages directly or using ArcGIS Pro to visualize, analyze, compile, and share GIS data in 2D and 3D environments. 

 

Chapter 6

This chapter introduces the basic concepts of spatiotemporal data, the values and challenges of loT, and the ArcGIS products that can meet these challenges. The chapter also teaches how to use real-time layers in web maps, create dashboard apps with actions and Arcade-based formatting, create time-enabled layers, and animate time-series data. Spatiotemporal data comes from many sources ranging from manual data entry to data collected using observational sensors or generated from simulation models. Spatiotemporal data includes observations of objects and events that move or change through time such as when and where an observation took place and what activity was observed. loT is the network of physical objects embedded with sensors and network connectivity that enable these objects to collect and exchange data. The science community, the US federal government, and the private sector have embraced the loT to support the creation of systems and products ranging from enterprise applications to consumer applications. An important application of the loT is the smart city which integrates loT technology to make more efficient use of physical infrastructure.

Chapters Five and Six were done rather smoothly and at this point I felt comfortable enough to work on what I hope will be a great final project to fully sum up how I am learning web GIS. I know I wanted to do a geographic profile of Jack the Ripper in my last GEOG class and here I am finally doing it. I find the web GIS to be easier to use then the software GIS and I am already on the first stages of creating an information layer.

One concern I do have is that I am having a rather hard time creating pop ups that have distinct information about these events, to the point where I fear I will have to create a different layer for each point on the map. If I could only give each point it’s own title and brief description. I felt like editing the features of points on the map was significantly easier in the software then it is here.

Chapter 3 went well without issue. It describes how to use the Experience builder and some of the major working parts of it. The widgets made a lot of sense and I liked how they showed so many different and useful ones.  I found the UI of the experience builder to be a bit confusing, but I think it was due to something with my perception and not the app itself. I think this is a very versatile tool that will really help with communication and making maps more accessible to non-cartography nerds. I know I really would have appreciated a website like this in middle-school if I had known about it. 

 

Chapter 4 had a lot of good information in it too. It talks about all the uses that mobile devices have in GIS, specifically for surveys, collaborative maps, and AR experiences. I think the surveys are a super useful tool, but I find the editable feature layers the most interesting. I think giving the opportunity to coworkers, partners, or volunteers in the community to work on maps with you is an important tool to be used. However, the downside is that you may have people working on maps in different styles when you need one coherent language.

Chapter 5: Caching and On-Premises Web GIS

ArcGIS Enterprise is more user-managed than ArcGIS Online and allows for the use of on-premises GIS, which may be helpful for organizations operating with limited internet connection. The chapter refers to ArcGIS Enterprise services as being “deployed,” which I think is a good word in this context. It also allows operations to remain more private and limited to the specific organization, while also utilizing ArcGIS data and basemaps (through hybrid Web GIS). The ArcGIS Portal compiles the various types of ArcGIS data and shares it within the designated organization. It serves as the “connector” between ArcGIS Online and the organization’s ArcGIS Enterprise. ArcGIS Server allows for the use of geographic information by the organization.

This chapter also describes the differences between different web layers hosted by ArcGIS Online and ArcGIS Enterprise. I appreciated the refresher on vector and raster layers: vector layers contain more specific data typically based on density, while raster layers are more complete image files like basemaps. Raster layers are best for unchanging data, and they take up more storage, while vector layers may frequently change, but are lighter in terms of storage. Also, ArcGIS Online uses caching, which involves returning to previous requests on the web server to generate tiles, reducing response time and improving user experience. The raster and vector layers are precached, so they are already stored in the database and can be accessed quickly. At the end of the description portion of this chapter, there were a lot of helpful flowcharts and tables detailing the requirements and ideal uses of each type of layer.

In the embedded version of the maps in Tutorial 5.3, the left side is the raster map, and the right side is the vector map. The vector map has noticeable higher-resolution lines and labels, and the raster map data disappears when you zoom in enough.

Figure 4.1: side-by-side of vector (left) and raster (right) tile layers. An indication of which is which comes from the disappearance of raster data at a zoomed-in extent. When saving the raster data, we kept it rather coarse to reduce the amount of storage required for the layer.

 

Chapter 6: Spatiotemporal Data and Real-Time GIS

As the name suggests, spatiotemporal data is data that changes through time. Different types of spatiotemporal data include moving data, discrete data, stationary data, or change data. Real-time GIS utilizes spatiotemporal dat and can either focus on point-in-time data (one field) or duration of time (two fields: one for start time, one for end time). When working with spatiotemporal data, it is important to consider systems of time data, such as measurement and reference systems, representations, and temporal resolution (time interval of sampling).

Another neat aspect of widely disseminated spatiotemporal data is the Internet of Things (IoT). This chapter refers to the IoT as an “ecosystem,” which I think is a neat (and pretty accurate!) way to refer to the massive web of time-based information that is utilized by any GIS-based service. The IoT contains a lot of raw data that GIS applications turn into useful information. An example that the chapter uses is smart cars, and how routing, maps, and road conditions are all utilized by the car for a smooth and safe driving experience.

Figure 4.2: the completed emergency dashboard after Tutorials 6.1 and 6.2. As I was working on this, it was updating and the open incidents number went down!

Chapters 5 and 6 from Getting to know Web GIS focus on caching, on-premises Web GIS, and the role of spatiotemporal/real-time data in GIS applications. While these concepts are more technical, they highlight an important shift in how GIS systems manage and deliver large amounts of data efficiently. These chapters emphasize how Web GIS supports dynamic and scalable data processing. Backtracking to the key term caching, particularly with tile layers, which improves performance by storing pre-built map images. Instead of generating maps every time a user interacts with them, cached layers allow for faster loading and smoother user experiences. This is especially important for large datasets or applications with many users. In contrast, on-premises Web GIS (ArcGIS Enterprise) allows organizations to manage their own data and infrastructure, offering greater control over security and customization compared to cloud-based systems like ArcGIS Online.

Chapter 6 introduces real-time GIS and spatiotemporal data, which adds both space and time into analysis. This allows users to track changes as they happen, such as traffic patterns, weather events, or sensor data. The ability to process and visualize real-time information shows how GIS is becoming more predictive and responsive, rather than just descriptive. An application of these ideas using my own data could involve tracking places I visit over time, such as study locations or travel patterns. By incorporating timestamps and location data, I could create a map that shows how my movement changes over days or weeks. Using cached layers would ensure the app runs efficiently, while real-time updates could make the data more interactive and relevant. These chapters also left me with questions about when to use cloud versus on-premises systems, and how to balance performance with data accuracy when working with real-time information.