Chapter 5<\/b><\/p>\n
In this chapter, I learned about the components and techniques used in ArcGIS Enterprise. ArcGIS Enterprise is similar to ArcGIS Online, but Enterprise allows you to work on a private server while Online does not. Notable software components of ArcGIS Enterprise include portal, server, adaptor, and data source. These components perform functions together to run Enterprise such as managing content, creating accessible geographic information, providing security, and storing configured data. The chapter then shifted to giving an overview of the different map layers such as raster tiles, vector tiles, map image layers, and feature tiles. While I remembered the function of these layers from GEOG 291, it served as a useful refresher. Additionally, I appreciated the inclusion of the table recommending which layer to use when you have certain types of data. The tutorial of this chapter involved working with both ArcGIS Online and ArcGIS Pro. I learned how to add a portal connection, publish a vector and raster layer from ArcGIS Pro to ArcGIS Online, and got further acquainted with StoryMaps. I thought this tutorial was useful because it connected web GIS to desktop, which some people don\u2019t have access to.<\/span><\/p>\n Application Idea: The assignment for this chapter just requires us to publish a raster layer and vector layer and compare the layers side by side. I would choose to make the layers with data from the previous tornado pathways in Kentucky. It also tells us to have a brief description of the differences between raster and vector tile layers. Raster tile layers are most appropriate for basemaps or maps with data that do not change a lot over time. They can provide advanced placement, symbology, imagery, and elevation data. Vector tile layers contain the geometries. The size of a vector tile is usually smaller than that of a raster tile because they are generated based on data density and resolution preference. The map style of a vector tile layer can be customized without having to regenerate tiles.<\/span><\/p>\n Chapter 6<\/b><\/p>\n This chapter introduces the concept of spatiotemporal data. Spatiotemporal data examines the where and when events occur and includes observations of objects and events that move or change through time. This type of data can be categorized into four groups: moving, discrete, stationary, and change. Seeing that all spatiotemporal data happens through time, the value of time is very important. Depending on the data at hand, time can be either measured at a point or a duration. The other part of spatiotemporal data is the physical objects themselves you are measuring. The internet of things (IoT) is the network of physical objects embedded with sensors and network connectivity that enable objects to collect and exchange data. The chapter also included a variety of graphs and charts in this section, which were very helpful in explaining the concepts. Lastly, I was introduced to a variety of apps associated with spatiotemporal data such as ArcGIS Velocity, ArcGIS Dashboards, and ArcGIS Mission. For the tutorial, the first exercise had me work with various features of Dashboards. While I didn\u2019t run into any problems since I was already familiar with the app, I did find the script section a bit challenging. The second exercise allowed me to create a time-enabled feature layer, which I really enjoyed the presentation of.<\/span><\/p>\n Application Idea: For this chapter, I would create a map showing how the percentage of land used in the United States has changed over time. To do this, I would symbolize the land used for agriculture with a unique color and create a time-enabled feature layer to show the change over decades. I could also create a dashboard from this data with the time scale map as the central focus, a chart displaying the percent change in land used for agriculture, and a list showing the states with the greatest percent change.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Chapter 5 In this chapter, I learned about the components and techniques used in ArcGIS Enterprise. ArcGIS Enterprise is similar to ArcGIS Online, but Enterprise allows you to work on a private server while Online does not. Notable software components of ArcGIS Enterprise include portal, server, adaptor, and data source. These components perform functions together to run Enterprise such as managing content, creating accessible geographic information, providing security, and storing configured data. The chapter then shifted to giving an overview of the different map layers such as raster tiles, vector tiles, map image layers, and feature tiles. While I remembered the function of these layers from GEOG 291, it served as a useful refresher. Additionally, I appreciated the inclusion of the table recommending which layer to use when you have certain types of data. The tutorial of this chapter involved working with both ArcGIS Online and ArcGIS Pro. I learned how to add a portal connection, publish a vector and raster layer from ArcGIS Pro to ArcGIS Online, and got further acquainted with StoryMaps. I thought this tutorial was useful because it connected web GIS to desktop, which some people don\u2019t have access to. Application Idea: The assignment for this chapter just requires us to publish a raster layer and vector layer and compare the layers side by side. I would choose to make the layers with data from the previous tornado pathways in Kentucky. It also tells us to have a brief description of the differences between raster and vector tile layers. Raster tile layers are most appropriate for basemaps or maps with data that do not change a lot over time. They can provide advanced placement, symbology, imagery, and elevation data. Vector tile layers contain the geometries. The size of a vector tile is usually smaller than that of a raster tile because they are generated based on data density and resolution preference. The map style of a vector tile layer can be customized without having to regenerate tiles. Chapter 6 This chapter introduces the concept of spatiotemporal data. Spatiotemporal data examines the where and when events occur and includes observations of objects and events that move or change through time. This type of data can be categorized into four groups: moving, discrete, stationary, and change. Seeing that all spatiotemporal data happens through time, the value of time is very important. Depending on the data at hand, time can be either measured at a point or a duration. The other part of spatiotemporal data is the physical objects themselves you are measuring. The internet of things (IoT) is the network of physical objects embedded with sensors and network connectivity that enable objects to collect and exchange data. The chapter also included a variety of graphs and charts in this section, which were very helpful in explaining the concepts. Lastly, I was introduced to a variety of apps associated with spatiotemporal data such as ArcGIS Velocity, ArcGIS Dashboards, and ArcGIS Mission. For the tutorial, the first exercise had me work with various features of Dashboards. While I didn\u2019t run into any problems since I was already familiar with the app, I did find the script section a bit challenging. The second exercise allowed me to create a time-enabled feature layer, which I really enjoyed the presentation of. Application Idea: For this chapter, I would create a map showing how the percentage of land used in the United States has changed over time. To do this, I would symbolize the land used for agriculture with a unique color and create a time-enabled feature layer to show the change over decades. I could also create a dashboard from this data with the time scale map as the central focus, a chart displaying the percent change in land used for agriculture, and a list showing the states with the greatest percent change.<\/p>\n","protected":false},"author":2413,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3592","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3592","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\/2413"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/comments?post=3592"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3592\/revisions"}],"predecessor-version":[{"id":3593,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/posts\/3592\/revisions\/3593"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/media?parent=3592"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/categories?post=3592"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-292\/wp-json\/wp\/v2\/tags?post=3592"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}