Chapter 4<\/b><\/p>\n
In this chapter, I learned about another way to map data through GIS called mapping by density. You should map by density when you are looking for patterns of individual features or mapping with areas of different sizes because it allows you to see where features are concentrated. There are two ways of mapping density: by defined area and by density surface.\u00a0<\/span><\/p>\n You should map by defined area if you want to compare areas with defined borders. Although GIS can calculate the density of each area for you, it is important to ensure all feature units match. Shaded fill maps or dot maps are common ways to display density maps defined by area. If you want to see the concentration of points or line features, however, you should map by density surface. When mapping by density surface, there are several parameters that affect how GIS calculates density surface. Cell size determines how coarse or fine the patterns will appear and search radius affects how generalized the patterns in surface density will be. The two ways GIS can calculate the density are the simple method and the weighted method. Overall, I learned how to efficiently create an effective density map through the use of GIS.<\/span><\/p>\n Key Concepts\/Definitions<\/b><\/p>\n Shaded fill map: Uses a range of colors to display density. Density is treated as a ratio. Density value applies for the entire polygon, the actual density at a specific location may vary.<\/span><\/p>\n Dot Density Map: Each dot represents a specified number of locations. The dots are randomly distributed, so they do not represent the actual feature locations. The closer together the dots are, the higher density of features in that area.\u00a0<\/span><\/p>\n Simple Calculation Method: Counts only the features within the search radius of each cell. Results in a series of rings that overlap each other.<\/span><\/p>\n Weighted Calculation Method: Gives more mathematical weight to the features closer to the center of the cell. Every cell in the layer is counted and assigned a value. Results in a smoother, more generalized density surface.<\/span><\/p>\n Chapter 5<\/b><\/p>\n This chapter introduced me to all of the information I needed to know about mapping what\u2019s inside. This type of mapping is used to monitor what is occurring inside of an area or to compare several areas based on what\u2019s inside each. GIS can find out whether an individual feature is inside an area, list all the features inside an area, find out the number of features in an area, or get a summary of what\u2019s inside a boundary based on a feature attribute.<\/span><\/p>\n The three ways of mapping what\u2019s inside include drawing areas and features, selecting features inside of an area, and overlaying the areas and features. When creating these maps, it is important to use symbols, boundaries, labels, and colors to help distinguish or emphasize visual aspects of the map. I have found this detail to be emphasized throughout the book. Although the first two methods seemed pretty straight forward to me, overlaying the areas and features proved to be more complicated. When you are overlaying and have discrete features, you can use the same analysis as in geographical selection or you can summarize by area. When you are overlaying and have continuous features, however, you use the vector or raster model. Additionally, when overlaying you may end up with slivers. To offset them, you should merge them into one of the larger adjacent areas. When analyzing the results of these maps, you should use the summary statistics such as counts, frequency, sum, average, median, or standard deviation.<\/span><\/p>\n Key Concepts\/Definitions<\/b><\/p>\n Drawing Areas and Features: Creates a map showing the boundaries and features. Good for the visual approach of seeing whether one or more features are inside or outside a singular area.<\/span><\/p>\n Selecting Features Inside of an Area: Specifies the area and layer containing features. GIS selects a subset of features inside the area. Good for getting a list or summary of features inside a single area and finding what\u2019s in a given distance of a feature.<\/span><\/p>\n Overlaying the Areas and Features: GIS combines the area and the features to create a new layer with attributes of both or compares two layers to calculate the summary statistics of each. Good for finding which features are in several areas or how much of something is in one or more areas.<\/span><\/p>\n Slivers: Borders that are slightly offset.<\/span><\/p>\n Chapter 6<\/b><\/p>\n In this chapter, I was introduced to the concept of mapping what\u2019s nearby. This type of mapping was particularly interesting to me because I recognized its use in many different fields. Mapping what\u2019s nearby identifies the area and the features inside that are affected by a certain event and determines if an area is suitable for a specific use. Data in mapping what\u2019s nearby is measured using distance or cost. Cost, also known as travel costs, could be the amount of time, money, or energy expended. Before mapping, you should decide whether the map would be suitable for the planar or geodesic method and if you should use inclusive rings or distinct bands. To map what\u2019s nearby, you can measure a straight line distance, distance or cost over a network, or cost over a surface. When measuring distance with a straight line, there are several methods that can be used such as creating a buffer, selecting features within a distance, distance between feature to feature, and creating a distance surface. Distance or cost over a network consists of the measurement of segments in geographic networks within the travel parameters. Lastly, calculating cost over a geographic surface shows the rate of change in distance or cost from the feature. The method you use depends on the data and how you intend to portray the map. Overall, throughout this book, I learned that many of these different maps have the same principles behind them. Knowing how to properly differentiate each type of map, utilize coloring, identify features or categories, define boundaries, and analyze summary statistics are all factors in creating effective maps in GIS.<\/span><\/p>\n Key Concepts\/Definitions<\/b><\/p>\n Straight-line Distance: Use for defining an area of influence around a feature, creating a boundary, or selecting features within a distance. Measures distance.\u00a0<\/span><\/p>\n Distance or Cost Over a Network: Use for measuring travel over a fixed infrastructure. Measures distance or travel costs.<\/span><\/p>\n Cost Over a Surface: Use for measuring overland travel and calculating how much area is within the travel range. Measures travel costs.<\/span><\/p>\n Planar Method: When you are assuming the earth\u2019s surface is flat. Area of interest is relatively small.<\/span><\/p>\n Geodesic method: When you take the curvature of earth into account. Area of interest encompasses a large region.<\/span><\/p>\n Inclusive rings: Show how the total amount of features increases as the distance increases. Distinct bands: Show the differences between feature amounts and different distances.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Chapter 4 In this chapter, I learned about another way to map data through GIS called mapping by density. You should map by density when you are looking for patterns of individual features or mapping with areas of different sizes because it allows you to see where features are concentrated. There are two ways of mapping density: by defined area and by density surface.\u00a0 You should map by defined area if you want to compare areas with defined borders. Although GIS can calculate the density of each area for you, it is important to ensure all feature units match. Shaded fill maps or dot maps are common ways to display density maps defined by area. If you want to see the concentration of points or line features, however, you should map by density surface. When mapping by density surface, there are several parameters that affect how GIS calculates density surface. Cell size determines how coarse or fine the patterns will appear and search radius affects how generalized the patterns in surface density will be. The two ways GIS can calculate the density are the simple method and the weighted method. Overall, I learned how to efficiently create an effective density map through the use of GIS. Key Concepts\/Definitions Shaded fill map: Uses a range of colors to display density. Density is treated as a ratio. Density value applies for the entire polygon, the actual density at a specific location may vary. Dot Density Map: Each dot represents a specified number of locations. The dots are randomly distributed, so they do not represent the actual feature locations. The closer together the dots are, the higher density of features in that area.\u00a0 Simple Calculation Method: Counts only the features within the search radius of each cell. Results in a series of rings that overlap each other. Weighted Calculation Method: Gives more mathematical weight to the features closer to the center of the cell. Every cell in the layer is counted and assigned a value. Results in a smoother, more generalized density surface. Chapter 5 This chapter introduced me to all of the information I needed to know about mapping what\u2019s inside. This type of mapping is used to monitor what is occurring inside of an area or to compare several areas based on what\u2019s inside each. GIS can find out whether an individual feature is inside an area, list all the features inside an area, find out the number of features in an area, or get a summary of what\u2019s inside a boundary based on a feature attribute. The three ways of mapping what\u2019s inside include drawing areas and features, selecting features inside of an area, and overlaying the areas and features. When creating these maps, it is important to use symbols, boundaries, labels, and colors to help distinguish or emphasize visual aspects of the map. I have found this detail to be emphasized throughout the book. Although the first two methods seemed pretty straight forward to me, overlaying the areas and features proved to be more complicated. When you are overlaying and have discrete features, you can use the same analysis as in geographical selection or you can summarize by area. When you are overlaying and have continuous features, however, you use the vector or raster model. Additionally, when overlaying you may end up with slivers. To offset them, you should merge them into one of the larger adjacent areas. When analyzing the results of these maps, you should use the summary statistics such as counts, frequency, sum, average, median, or standard deviation. Key Concepts\/Definitions Drawing Areas and Features: Creates a map showing the boundaries and features. Good for the visual approach of seeing whether one or more features are inside or outside a singular area. Selecting Features Inside of an Area: Specifies the area and layer containing features. GIS selects a subset of features inside the area. Good for getting a list or summary of features inside a single area and finding what\u2019s in a given distance of a feature. Overlaying the Areas and Features: GIS combines the area and the features to create a new layer with attributes of both or compares two layers to calculate the summary statistics of each. Good for finding which features are in several areas or how much of something is in one or more areas. Slivers: Borders that are slightly offset. Chapter 6 In this chapter, I was introduced to the concept of mapping what\u2019s nearby. This type of mapping was particularly interesting to me because I recognized its use in many different fields. Mapping what\u2019s nearby identifies the area and the features inside that are affected by a certain event and determines if an area is suitable for a specific use. Data in mapping what\u2019s nearby is measured using distance or cost. Cost, also known as travel costs, could be the amount of time, money, or energy expended. Before mapping, you should decide whether the map would be suitable for the planar or geodesic method and if you should use inclusive rings or distinct bands. To map what\u2019s nearby, you can measure a straight line distance, distance or cost over a network, or cost over a surface. When measuring distance with a straight line, there are several methods that can be used such as creating a buffer, selecting features within a distance, distance between feature to feature, and creating a distance surface. Distance or cost over a network consists of the measurement of segments in geographic networks within the travel parameters. Lastly, calculating cost over a geographic surface shows the rate of change in distance or cost from the feature. The method you use depends on the data and how you intend to portray the map. Overall, throughout this book, I learned that many of these different maps have the same principles behind them. Knowing how to properly differentiate each type of map, utilize coloring, identify features or categories, define boundaries, and analyze summary statistics are all factors in creating effective maps in GIS. Key Concepts\/Definitions Straight-line Distance: Use for defining an area of influence around a feature, creating a boundary, or selecting features within a distance. Measures distance.\u00a0 Distance or Cost Over a Network: Use for measuring travel over a fixed infrastructure. Measures distance or travel costs. Cost Over a Surface: Use for measuring overland travel and calculating how much area is within the travel range. Measures travel costs. Planar Method: When you are assuming the earth\u2019s surface is flat. Area of interest is relatively small. Geodesic method: When you take the curvature of earth into account. Area of interest encompasses a large region. Inclusive rings: Show how the total amount of features increases as the distance increases. Distinct bands: Show the differences between feature amounts and different distances.<\/p>\n","protected":false},"author":2413,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-7338","post","type-post","status-publish","format-standard","hentry","category-course-student-work"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7338","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/users\/2413"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=7338"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7338\/revisions"}],"predecessor-version":[{"id":7339,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7338\/revisions\/7339"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=7338"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=7338"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=7338"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}