{"id":5102,"date":"2025-09-05T10:01:23","date_gmt":"2025-09-05T15:01:23","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=5102"},"modified":"2025-09-05T10:01:23","modified_gmt":"2025-09-05T15:01:23","slug":"walz-week-3","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2025\/09\/05\/walz-week-3\/","title":{"rendered":"Walz &#8211; Week 3"},"content":{"rendered":"<p><span style=\"font-weight: 400\">Chapter 4:<\/span><\/p>\n<p><i><span style=\"font-weight: 400\">Concepts &amp; Definitions<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping density: shows where the highest concentration of features is<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Defined area: mapping density graphically, using a dot map, or calculating a density value for each area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density surface: Created in GIS as a raster layer, each cell in layer has a density value<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cell size: how coarse or fine patterns will appear, smaller cell size = smoother surface but more cells which will require more processing and storage space; larger cell size faster but more coarser surface and subtle patterns may not be noticed<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Search radius: larger search radius = more generalized patterns in the density surface<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Contour lines: connect points of equal density value on the surface<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Notes<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density maps are useful for looking at patterns more than locations of single features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density map shows the measure of number of features using a uniform aerial unit to clearly see distribution<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping density useful for mapping areas like counties<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Dot maps can be an easy way to read a map if they are distributed throughout a defined area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density surface requires a lot of effort but gives the most detailed<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density by a defined area is usually a shaded map, using multiple color shades<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Dot maps can give a quicker sense of density in a place<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Dots can be any amount of value 1 vs 100 vs 1000 units<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">When creating a density surface, GIS will define a neighborhood around each cell center and then will automatically total the number of features that fall within it and assign that value to the cell<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cells are square<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Converting density units to cell units: 1 sq. km = 1000m * 1000m = 1 million sq. m: 1 million sq. meters \/ 100 cells = 10,000 sq. meters per cell; sqrt 10,000 m = 100 m (one side of cell)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS lets you specify the areal units for density values calculated, like square meters for wildlife animals<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can display a density surface using graduated colors<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400\">Chapter 5:<\/span><\/p>\n<p><i><span style=\"font-weight: 400\">Concepts &amp; Definitions<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Single Area: A defined singular area to monitor activity\/summarize information in it<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Multiple Areas: Like single area but looking at several of them to compare them<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous values: numeric values that vary across a surface; temp, elevation, etc..<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Count: Total number of features inside an area; number of fast food in a county<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Frequency: Number of features with a given value\/range of values, inside an area and displayed as a table, bar chart, or pie chart<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Sum: Overall total<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Average\/Mean: Total numeric attribute divided by number of features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Median: Value in middle of a range of values of an attribute<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Standard Deviation: Average amount values away from the mean<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Notes<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Data should consider how many areas you have, and type of features inside them<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Discrete features unique and identifiable (like locations or crimes)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous features represent geographic phenomena<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can use GIS to find out whether a feature is within an area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can create a boundary for linear features and discrete areas that may fall outside of a chosen area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can create a map showing the boundary of an area and features, good for seeing a few features inside\/outside a single area; would just need data<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS can combine area and features to create a new layer with attributes to compare two layers<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can symbolize locations or linear features with a single symbol or by category\/quantity<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">If mapping continuous data (soils or elevation), draw areas by category\/quantity and then draw a boundary to highlight it<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Geographic selection is a way to find out which features are within a certain distance of another feature<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Overlaying areas and features can let you find which discrete features are within areas and summarize them<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS splits category\/class boundaries where they cross areas and creates a new dataset within the areas that result<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can use GIS to summarize the values and create a map\/table of summary stats for each area<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400\">Chapter 6:<\/span><\/p>\n<p><i><span style=\"font-weight: 400\">Concepts &amp; Definitions<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Geodesic Method: Measuring distance using curvature of the earth<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Inclusive RIngs: Useful for finding how the total amount increases as the distance increases; like the total number of chicken diners within 1 mile versus 2 miles versus 10! Miles<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Distinct Bands: Used to compare distance to other characteristics, kind of like a range; number of beef stew shops between 1 miles and 2 miles<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Straight line distance: Can specify the source feature and distance and GIS will find the area\/surrounding features within that distance<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Spider Diagram: GIS draws a line between each location and nearest source; useful for comparing patterns between multiple sources<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Graduated Symbols: Symbols used for comparing course features based on quantity; symbols = number of locations near a source feature<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Notes<\/span><\/i><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Using GIS can tell you what\u2019s occurring in a set distance of a feature and traveling range<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To find stuffy nearby, can measure using a straight line distance<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To define \u2018nearby\u2019, can be based on a set distance specified or travel to from feature to another; can also include travel cost<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Time would be an example of a cost, like going from a heavy traffic area to a store<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Effort could also be a type of travel cost; effort for a fish to swim upstream<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For measuring distance, have to consider if it\u2019s a flat plane or use the curvature of the earth; small areas distances should be flat plane, larger should be done using the geodesic method<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can specify the source locations and distance along a linear feature<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To create a buffer, specify source feature and then the buffer distance, GIS will draw a line and circle around the desired distance; can have different sizes of buffers around different features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can create distance ranges, each cell can have that unique value and can then display that value using colors<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can create a boundary manually by drawing a line around selected segments or have GIS create the boundary; manually drawing boundaries give more flexibility but may take more time<\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Chapter 4: Concepts &amp; Definitions Mapping density: shows where the highest concentration of features is Defined area: mapping density graphically, using a dot map, or calculating a density value for each area Density surface: Created in GIS as a raster layer, each cell in layer has a density value Cell size: how coarse or fine patterns will appear, smaller cell size = smoother surface but more cells which will require more processing and storage space; larger cell size faster but more coarser surface and subtle patterns may not be noticed Search radius: larger search radius = more generalized patterns in the density surface Contour lines: connect points of equal density value on the surface Notes Density maps are useful for looking at patterns more than locations of single features Density map shows the measure of number of features using a uniform aerial unit to clearly see distribution Mapping density useful for mapping areas like counties Dot maps can be an easy way to read a map if they are distributed throughout a defined area Density surface requires a lot of effort but gives the most detailed Density by a defined area is usually a shaded map, using multiple color shades Dot maps can give a quicker sense of density in a place Dots can be any amount of value 1 vs 100 vs 1000 units When creating a density surface, GIS will define a neighborhood around each cell center and then will automatically total the number of features that fall within it and assign that value to the cell Cells are square Converting density units to cell units: 1 sq. km = 1000m * 1000m = 1 million sq. m: 1 million sq. meters \/ 100 cells = 10,000 sq. meters per cell; sqrt 10,000 m = 100 m (one side of cell) GIS lets you specify the areal units for density values calculated, like square meters for wildlife animals Can display a density surface using graduated colors &nbsp; Chapter 5: Concepts &amp; Definitions Single Area: A defined singular area to monitor activity\/summarize information in it Multiple Areas: Like single area but looking at several of them to compare them Continuous values: numeric values that vary across a surface; temp, elevation, etc.. Count: Total number of features inside an area; number of fast food in a county Frequency: Number of features with a given value\/range of values, inside an area and displayed as a table, bar chart, or pie chart Sum: Overall total Average\/Mean: Total numeric attribute divided by number of features Median: Value in middle of a range of values of an attribute Standard Deviation: Average amount values away from the mean Notes Data should consider how many areas you have, and type of features inside them Discrete features unique and identifiable (like locations or crimes) Continuous features represent geographic phenomena Can use GIS to find out whether a feature is within an area Can create a boundary for linear features and discrete areas that may fall outside of a chosen area Can create a map showing the boundary of an area and features, good for seeing a few features inside\/outside a single area; would just need data GIS can combine area and features to create a new layer with attributes to compare two layers Can symbolize locations or linear features with a single symbol or by category\/quantity If mapping continuous data (soils or elevation), draw areas by category\/quantity and then draw a boundary to highlight it Geographic selection is a way to find out which features are within a certain distance of another feature Overlaying areas and features can let you find which discrete features are within areas and summarize them GIS splits category\/class boundaries where they cross areas and creates a new dataset within the areas that result Can use GIS to summarize the values and create a map\/table of summary stats for each area &nbsp; Chapter 6: Concepts &amp; Definitions Geodesic Method: Measuring distance using curvature of the earth Inclusive RIngs: Useful for finding how the total amount increases as the distance increases; like the total number of chicken diners within 1 mile versus 2 miles versus 10! Miles Distinct Bands: Used to compare distance to other characteristics, kind of like a range; number of beef stew shops between 1 miles and 2 miles Straight line distance: Can specify the source feature and distance and GIS will find the area\/surrounding features within that distance Spider Diagram: GIS draws a line between each location and nearest source; useful for comparing patterns between multiple sources Graduated Symbols: Symbols used for comparing course features based on quantity; symbols = number of locations near a source feature Notes Using GIS can tell you what\u2019s occurring in a set distance of a feature and traveling range To find stuffy nearby, can measure using a straight line distance To define \u2018nearby\u2019, can be based on a set distance specified or travel to from feature to another; can also include travel cost Time would be an example of a cost, like going from a heavy traffic area to a store Effort could also be a type of travel cost; effort for a fish to swim upstream For measuring distance, have to consider if it\u2019s a flat plane or use the curvature of the earth; small areas distances should be flat plane, larger should be done using the geodesic method Can specify the source locations and distance along a linear feature To create a buffer, specify source feature and then the buffer distance, GIS will draw a line and circle around the desired distance; can have different sizes of buffers around different features Can create distance ranges, each cell can have that unique value and can then display that value using colors Can create a boundary manually by drawing a line around selected segments or have GIS create the boundary; manually drawing boundaries give more flexibility but may take more time<\/p>\n","protected":false},"author":2322,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-5102","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\/5102","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\/2322"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=5102"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5102\/revisions"}],"predecessor-version":[{"id":5103,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5102\/revisions\/5103"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=5102"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=5102"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=5102"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}