{"id":5036,"date":"2025-09-05T22:11:52","date_gmt":"2025-09-06T03:11:52","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=5036"},"modified":"2025-09-05T22:11:52","modified_gmt":"2025-09-06T03:11:52","slug":"inderhees-week-3","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2025\/09\/05\/inderhees-week-3\/","title":{"rendered":"Inderhees- Week 3"},"content":{"rendered":"<p><b>Chapter 4 \u2013 Mapping Density<\/b><b><br \/><\/b><span style=\"font-weight: 400\">This chapter focuses on map density which is useful when it comes to figuring out the location or concentration of an individual feature to figure out where lost reside. This can turn data into a visualization on a map.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Why map density?<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">It makes it easier to compare different areas due to the way it is shown on the map. They are especially useful when it comes to data of a large area.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Deciding what to map<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To map density an area is shaded based on density value or a density surface is created. What is being mapped out helps to decide which to use.\u00a0 You can either map features which might be locations\u00a0 or feature values which could be a number of features.\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Two ways of mapping density<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Defined area- mapped graphically using a dot map. A dot map is used to represent the density of individual locations summarized by defined areas. This also makes the map easier to read.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density surface- Typically in the GIS as a raster layer. Each cell in the layer would get a density value. This provides the most information but also is a lot of work to create\/ read.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping density for defined areas<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To calculate density, you first add a new field to the feature data table. Then, you calculate the density value for each polygon by dividing the value you&#8217;re mapping by the polygon&#8217;s area. If the units for the area and density don&#8217;t match, you&#8217;ll need to include a conversion factor in your calculation. This will typically be shown as a shaded map.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">With a dot density, you decide how many of a particular feature each dot will represent. The GIS then calculates the number of dots to draw within each area by dividing the total count in that area by the value of a single dot.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Creating a density surface<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS defines a neighborhood around each cell. The total is then divided by the area around the cell then that value is given to the cell. The smaller the cell size the smoother the surface will be. The larger the radius the more generalized the patterns will be. There are 2 calculation methods. The results depend on how the map was created.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Chapter 5 \u2013 Finding What&#8217;s Inside<\/b><\/p>\n<p><span style=\"font-weight: 400\">This chapter focuses on spatial selection and overlay analysis. This is a fundamental task in GIS that allows you to identify parts of features that fall within a boundary.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Why Map What&#8217;s Inside?<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This type of analysis is used to determine which features, such as points or lines, are located within another feature. It can also be used to find which portions of a feature are contained within another. Allowing to combine data from different layers to answer a specific question.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Defining Your Analysis<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Before starting what is trying to be achieved needs to be determined. Are you simply trying to count the number of features inside an area or do you need to create a new layer that combines data from both the inside features and the boundary area?<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Three Ways of Finding What&#8217;s Inside<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Drawing Areas and Features: Sometimes the simplest way to find what&#8217;s inside is to draw a new area or feature on a map and then visually see what falls in it. While not precise a great starting point.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Selecting Features Inside an Area: A more precise method that uses select features based on their location relative to another layer. Quick way to get a count without changing the underlying data.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Overlaying Areas and Features: Advanced technique that combines the geometry and attributes of two or more layers to create a new one. The new layer contains the combined information and more complex analysis.\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Chapter 6 \u2013 Finding What&#8217;s Nearby<\/b><\/p>\n<p><span style=\"font-weight: 400\">This chapter focuses on proximity analysis, a set of tools that help you figure out the distance or travel cost from a feature.<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Why Map What&#8217;s Nearby?<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Determining what is nearby is not always as simple as measuring a straight line. Due to proximity analysis nearby can be defined a few different ways. Helps to account for barriers like mountains or rivers where with a simple straight-line measurement would be ignored.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Defining Your Analysis<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">What is trying to be achieved needs to be determined first whether that be the closest feature, trying to avoid something etc.The answers to these questions will determine which proximity tool is used.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Three Ways of Finding What&#8217;s Nearby<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Using Straight-Line Distance: Most straightforward method. Measures the shortest distance between two points. A common tool for this is creating a buffer.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Measuring Distance or Cost Over a Network: This method calculates travel distance or time along a network. This is more accurate for real-world scenarios where travel is limited to specific paths.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Calculating Cost Over a Geographic Surface: Complex method that calculates distance or cost based on a raster layer where each cell has a value representing the cost of moving across it.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Chapter 4 \u2013 Mapping DensityThis chapter focuses on map density which is useful when it comes to figuring out the location or concentration of an individual feature to figure out where lost reside. This can turn data into a visualization on a map. Why map density? It makes it easier to compare different areas due to the way it is shown on the map. They are especially useful when it comes to data of a large area. Deciding what to map To map density an area is shaded based on density value or a density surface is created. What is being mapped out helps to decide which to use.\u00a0 You can either map features which might be locations\u00a0 or feature values which could be a number of features.\u00a0 Two ways of mapping density Defined area- mapped graphically using a dot map. A dot map is used to represent the density of individual locations summarized by defined areas. This also makes the map easier to read. Density surface- Typically in the GIS as a raster layer. Each cell in the layer would get a density value. This provides the most information but also is a lot of work to create\/ read. Mapping density for defined areas To calculate density, you first add a new field to the feature data table. Then, you calculate the density value for each polygon by dividing the value you&#8217;re mapping by the polygon&#8217;s area. If the units for the area and density don&#8217;t match, you&#8217;ll need to include a conversion factor in your calculation. This will typically be shown as a shaded map. With a dot density, you decide how many of a particular feature each dot will represent. The GIS then calculates the number of dots to draw within each area by dividing the total count in that area by the value of a single dot. Creating a density surface GIS defines a neighborhood around each cell. The total is then divided by the area around the cell then that value is given to the cell. The smaller the cell size the smoother the surface will be. The larger the radius the more generalized the patterns will be. There are 2 calculation methods. The results depend on how the map was created. Chapter 5 \u2013 Finding What&#8217;s Inside This chapter focuses on spatial selection and overlay analysis. This is a fundamental task in GIS that allows you to identify parts of features that fall within a boundary. Why Map What&#8217;s Inside? This type of analysis is used to determine which features, such as points or lines, are located within another feature. It can also be used to find which portions of a feature are contained within another. Allowing to combine data from different layers to answer a specific question. Defining Your Analysis Before starting what is trying to be achieved needs to be determined. Are you simply trying to count the number of features inside an area or do you need to create a new layer that combines data from both the inside features and the boundary area? Three Ways of Finding What&#8217;s Inside Drawing Areas and Features: Sometimes the simplest way to find what&#8217;s inside is to draw a new area or feature on a map and then visually see what falls in it. While not precise a great starting point. Selecting Features Inside an Area: A more precise method that uses select features based on their location relative to another layer. Quick way to get a count without changing the underlying data. Overlaying Areas and Features: Advanced technique that combines the geometry and attributes of two or more layers to create a new one. The new layer contains the combined information and more complex analysis.\u00a0 Chapter 6 \u2013 Finding What&#8217;s Nearby This chapter focuses on proximity analysis, a set of tools that help you figure out the distance or travel cost from a feature. Why Map What&#8217;s Nearby? Determining what is nearby is not always as simple as measuring a straight line. Due to proximity analysis nearby can be defined a few different ways. Helps to account for barriers like mountains or rivers where with a simple straight-line measurement would be ignored. Defining Your Analysis What is trying to be achieved needs to be determined first whether that be the closest feature, trying to avoid something etc.The answers to these questions will determine which proximity tool is used. Three Ways of Finding What&#8217;s Nearby Using Straight-Line Distance: Most straightforward method. Measures the shortest distance between two points. A common tool for this is creating a buffer. Measuring Distance or Cost Over a Network: This method calculates travel distance or time along a network. This is more accurate for real-world scenarios where travel is limited to specific paths. Calculating Cost Over a Geographic Surface: Complex method that calculates distance or cost based on a raster layer where each cell has a value representing the cost of moving across it.<\/p>\n","protected":false},"author":2326,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-5036","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\/5036","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\/2326"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=5036"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5036\/revisions"}],"predecessor-version":[{"id":5148,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5036\/revisions\/5148"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=5036"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=5036"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=5036"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}