{"id":3144,"date":"2026-04-10T22:17:04","date_gmt":"2026-04-11T03:17:04","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-292\/?p=3144"},"modified":"2026-04-10T22:17:04","modified_gmt":"2026-04-11T03:17:04","slug":"moore-week-4","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-292\/2026\/04\/10\/moore-week-4\/","title":{"rendered":"Moore Week 4"},"content":{"rendered":"

Chapter 5:\u00a0<\/span><\/p>\n

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.\u00a0\u00a0<\/span><\/p>\n

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.\u00a0<\/span><\/p>\n

Chapter 6:\u00a0<\/span><\/p>\n

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.\u00a0<\/span><\/p>\n

Chapter 6 also discusses the Internet of Things (IoT). This refers to the existing network of devices<\/span> that are <\/span>embedded with sensors, software, and other technologies that allow them to exchange data with other devices and the internet. Together, these \u201cthings\u201d (smartphones, household appliances, vehicles, etc) contain a vast amount of raw data, especially <\/span>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.\u00a0<\/span><\/p>\n

Application:\u00a0<\/span><\/p>\n

\u00a0 \u00a0An 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.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Chapter 5:\u00a0 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.\u00a0\u00a0 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.\u00a0 Chapter 6:\u00a0 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.\u00a0 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 \u201cthings\u201d (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.\u00a0 Application:\u00a0 \u00a0 \u00a0An 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.<\/p>\n","protected":false},"author":2368,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3144","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3144","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/users\/2368"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/comments?post=3144"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3144\/revisions"}],"predecessor-version":[{"id":3145,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3144\/revisions\/3145"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/media?parent=3144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/categories?post=3144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/tags?post=3144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}