{"id":5043,"date":"2025-08-29T21:11:56","date_gmt":"2025-08-30T02:11:56","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=5043"},"modified":"2025-08-29T21:11:56","modified_gmt":"2025-08-30T02:11:56","slug":"becker-week-2","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2025\/08\/29\/becker-week-2\/","title":{"rendered":"Becker Week 2"},"content":{"rendered":"<p><span style=\"font-weight: 400\">Chapter 1- Mitchell<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS grown enormously since 1999<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">New sources- lidar and drones<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Shared more openly and widely<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">More people<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">ArcGIS Living Atlas of the World<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS uses:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping where things are<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping the most and least<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping density<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Finding what\u2019s inside<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Finding what\u2019s nearby<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping change<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>GIS Analysis<\/b><span style=\"font-weight: 400\">&#8211; process for looking at geographic patterns in your data and relationships between features<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Process For Analysis Steps:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Frame the Question<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">What info do you need<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Question form- be specific<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">How will analysis be used, and by who?<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Understand Your Data<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Type of data and its features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Method you use could require you to obtain additional data (or change its format)<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Choose a Method<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Almost always multiple methods for obtaining needed information<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Decide which method fits your question and research best<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Process the Data<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Once method is selected, use GIS to perform it<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Look at the Results<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Multiple ways of displaying results: maps, tables, charts<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Decide what is new\/valuable to add to your display<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Decide whether your information is valid or useful; then adjust accordingly<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Understanding Geographic Features<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Types of Features:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Geographic features are discrete, continuous phenomena, or summarized by area<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Discrete: location can be pinpointed<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous Phenomena: can be found or measured anywhere, blanket entire area being mapped<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Interpolation-<\/b><span style=\"font-weight: 400\"> GIS using sample points to assign values to the areas in between them<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous data can also be areas enclosed by boundaries (everything within boundary must be same type)<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features Summarized by Area: counts or density of individual features within an area (ex: number of businesses in each zip code)<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Data value applies to the whole area and not a specific place within it<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Lots of data (especially demographic data) is sorted by area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS can be used to aggregate data that lies within similar areas<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ways of Representing Geographic Features<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Vector<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Each feature is a row in a table<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Shapes defined by x,y locations<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features can be discrete locations or events, lines, or areas<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Lines represented as series of coordinate pairs<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Areas defined by borders and represented as polygons<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Vector data analysis often times involves summarizing attributes in layer\u2019s data table<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Raster<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features represented as matrix of cells in continuous space<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Each layer represents one attribute<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Analysis is combining layers to create new layers<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cell size affects results of analysis\/map quality<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cell size should be based on original map scale and minimum mapping unit<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Discrete features and data summarized by area usually use vector model<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous categories either vector or raster<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous numeric values are raster<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Map projection<\/b><span style=\"font-weight: 400\">&#8211; translate locations on the globe onto flat surface<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Distort shape of features being displayed<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS systems usually already have their databases in the same coordinate system and projection<\/span><\/li>\n<\/ul>\n<p><b>Understanding Geographic Attributes<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Attribute Values<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Categories<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Groups of similar things that help you organize your data<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Category values can be represented as numeric codes or as text (abbreviated)<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ranks<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Put features in order from high to low<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Used when direct measures are difficult or quantity represents multiple factors<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Counts and Amounts<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Total numbers<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ratios<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Show relationship between two quantities<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Created by dividing one quantity with another for each feature<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Evens out differences between large and small areas<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Proportions- <\/b><span style=\"font-weight: 400\">what part of a total each value is<\/span><\/li>\n<\/ul>\n<ul>\n<li><b>Density- <\/b><span style=\"font-weight: 400\">distribution of features or values per unit area<\/span><\/li>\n<\/ul>\n<p><b>Working With Data Tables<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Three common operations: selecting, calculating, summarizing<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Selecting<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Select features to work with subset or assign new attribute<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">In form of logical expression (code)<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Calculating<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Calculate attribute values to assign new values to features in the table<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Summarizing<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Could be mean, frequency, total, etc.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400\">Chapter 2- Mitchell<\/span><\/p>\n<p><b>Why Map Where Things Are?<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To see where\/what an individual feature is<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">However looking at distribution of features allows patterns to form<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can show you where to take action, or what areas meet your criteria<\/span><\/li>\n<\/ul>\n<p><b>Deciding What To Map<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To look for geographic patterns, map features in a layer using different symbols<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Information Gained From Mapping<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Where features are\/aren\u2019t<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Locations of different features to look for patterns<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Make sure map is appropriate for audience<\/span><\/li>\n<\/ul>\n<p><b>Preparing Your Data<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Make sure features being mapped have geographic coordinates<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS databases have coordinates assigned, incoming info must have coordinates (street address or latitude-longitude)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">When mapping by type, each feature must have an identifier for its type<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Many categories are hierarchical<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Sometimes a single code can indicate multiple types (major type and subtype)<\/span><\/li>\n<\/ul>\n<p><b>Making Your Map<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To create, tell GIS your features and their symbols<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Mapping a Single Type<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Draw all features using same symbol<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can use this to find differences in the feature to explore further<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>What The GIS Does<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Stores location as pair of coordinates or set of coordinate pairs<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Individual locations: GIS draws symbol for that specific point<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS can also draw lines for line features, also draws area outlines<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Using a Subset<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can map features in subset based on specific category values<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Usually done for individual locations (linear features would often be incomplete)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For continuous data, you would be leaving out context of surrounding areas<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Mapping By Category<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Draw features by using different symbol for each category value<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>What the GIS does<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Stores category value for each feature in table<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Separately stores specified symbols<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features might belong to multiple categories<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Sometimes useful to make multiple maps with different categories to compare<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Display no more than seven categories on one map (also affected by distribution of features and map scale)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Hard to distinguish categories on maps with small features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For large maps, multiple categories can distort trends and make it harder to find differences between categories<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Conversely, important not to have too few categories on smaller maps (don\u2019t leave out info)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">If more than 7 categories, group the categories<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The way categories are grouped can influence readers\u2019 perception (categorize carefully!)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ways to group categories:\u00a0<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Assign each record two codes\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">create table containing one record for each detailed code with its corresponding general code<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Assign same symbol to various detailed categories that are apart of a general category<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Symbols used to display data are important to display it properly<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For areas\/raster layers: display similar categories in different shades of same color<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">For linear features: use different widths\/patterns (text labels could also be useful)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Maps more meaningful when they contain recognizable features, put reference features in light colors<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Reference feature<\/b><span style=\"font-weight: 400\">&#8211; feature on map that makes the area identifiable<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Some GIS software provides base maps with reference features<\/span><\/li>\n<\/ul>\n<p><b>Analyzing Geographic Patterns<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Play with map scale to try and find identifiable patterns in features<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Exceptions can reveal further causes\/areas of further interest<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Use statistics to more scientifically find relationships between different features<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400\">Mitchell- Chapter 3<\/span><\/p>\n<p><b>Why Map The Most And The Least<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Find places that meet criteria to take action or see relationships between places<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping based on quantities adds additional info<\/span><\/li>\n<\/ul>\n<p><b>What Do You Need To Map<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Discrete features<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Locations, linear features usually represented by graduated symbols; area by shading<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous phenomena can be defined areas or surface of continuous values<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Defined areas: graduated colors<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Surfaces: graduated colors, contours, 3D perspective view<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Data summarized by area displayed by shading each area<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Keep in mind whether or not you are exploring data or presenting your map<\/span><\/li>\n<\/ul>\n<p><b>Understanding Quantities<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Quantities: counts or amounts, ratios, ranks<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Counts and Amounts<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Count- <\/b><span style=\"font-weight: 400\">actual number of features on map<\/span><\/li>\n<\/ul>\n<ul>\n<li><b>Amount- <\/b><span style=\"font-weight: 400\">total of value associated with each feature<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can be mapped for discrete features or continuous phenomena<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">counts\/amounts can skew data for areas with size variability<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ratios<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Evens out differences for large\/small areas (shows distribution of features)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Proportions often represented as percentages<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Density good for showing distribution when large area size variability<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Create ratios by adding new field to layer\u2019s data<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ranks<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Useful when direct measures are difficult<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Assign ranks based on another feature attribute<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Creating Classes<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Counts, amounts, and ratios grouped into classes because each feature has a potentially different value<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Valuable for maps used for public discussion<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping individual values = more accurate picture<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">If mapping ranks, assign one symbol to each rank<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can map ratios, counts, or amounts using individual values if:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">No more than 11-12 unique values<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">&lt;20 features<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Classes- <\/b><span style=\"font-weight: 400\">group features with similar values by assigning same symbol<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Important to consciously define class ranges<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Create classes manually if looking for features that fit specific criteria or comparing features to meaningful value<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Use standard classification scheme if wanting to group similar values to find patterns<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Four most common schemes<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Natural breaks- <\/b><span style=\"font-weight: 400\">classes based on natural groupings of data values<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS automatically determines high and low value for each class using math to test class breaks, maximizes difference between classes<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Good for mapping not evenly distributed data values<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Quantile- <\/b><span style=\"font-weight: 400\">each class contains equal number of features<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS adds up number of features (plus puts them in order) then equally separates them into number of classes specified<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Good for comparing areas of similar size, mapping evenly distributed data, emphasizing relative position of feature<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Equal interval-<\/b><span style=\"font-weight: 400\"> difference between high and low values is the same for every group<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS subtracts lowest dataset from highest then divides that number by number of classes specified<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Good for presenting info to nontechnical audience and mapping continuous data<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Standard deviation-<\/b><span style=\"font-weight: 400\"> placed in classes based on how they deviate from the mean<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS finds mean, then calculates standard deviation and separates classes<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Seeing what features are above\/below mean value<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Displaying data with lots of values around mean<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Plot data values in chart to see their distribution<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Easy to change class ranges in GIS so try different ones<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Outliers- <\/b><span style=\"font-weight: 400\">few extremely high or low values<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To deal with them:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Put each in its own class<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Group them together in a class<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Group them with next closest class<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Draw them using special symbol<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">While exploring number of classes, start with more and work way down until desired clarity<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Rounding data when reasonable to make it palatable<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Give classes meaningful names<\/span><\/li>\n<\/ul>\n<p><b>Making a Map<\/b><\/p>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS options to show quantities<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Graduated symbols<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which features: locations, lines, areas<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which values: counts\/amounts, ratios, ranks<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Graduated colors<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which features: areas, continuous phenomena<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which values: ratios, ranks<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Charts<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which features: locations, areas<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which values: counts\/amounts, ratios<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Contours<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which features: continuous phenomena<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which values: amounts, ratios<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">3D perspective views<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which features: continuous phenomena, locations, areas<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Which values: counts\/amounts, ratios<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Legend- <\/b><span style=\"font-weight: 400\">displays subset of values and symbols to indicate relative value of individual features<\/span><\/li>\n<\/ul>\n<ul>\n<li style=\"list-style-type: none\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Consciously choose colors to attract attention to what you want to<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Charts on maps useful for quick study of patterns<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Pie charts: show how much of total amount each category takes up<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Bar charts: show relative amounts<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Use contour lines to show rate of change in values across an area<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Choose interval small enough to give surface definition but not too small that the lines are too close together<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Label with value<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Use bold line for every fifth interval<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">When using 3D perspective have viewer in proper spot so tall parts don\u2019t block shorter ones<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<ul>\n<li><b>Z-factor- <\/b><span style=\"font-weight: 400\">value specified to increase the variation in the surface so differences are easier to see<\/span><\/li>\n<\/ul>\n<p><b>Looking For Patterns<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Look at transition from highest to lowest values<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">See distribution of values (clustered or spread out)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Can summarize up but not down<\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Chapter 1- Mitchell GIS grown enormously since 1999 New sources- lidar and drones Shared more openly and widely More people ArcGIS Living Atlas of the World GIS uses: Mapping where things are Mapping the most and least Mapping density Finding what\u2019s inside Finding what\u2019s nearby Mapping change GIS Analysis&#8211; process for looking at geographic patterns in your data and relationships between features Process For Analysis Steps: Frame the Question What info do you need Question form- be specific How will analysis be used, and by who? Understand Your Data Type of data and its features Method you use could require you to obtain additional data (or change its format) Choose a Method Almost always multiple methods for obtaining needed information Decide which method fits your question and research best Process the Data Once method is selected, use GIS to perform it Look at the Results Multiple ways of displaying results: maps, tables, charts Decide what is new\/valuable to add to your display Decide whether your information is valid or useful; then adjust accordingly Understanding Geographic Features Types of Features: Geographic features are discrete, continuous phenomena, or summarized by area Discrete: location can be pinpointed Continuous Phenomena: can be found or measured anywhere, blanket entire area being mapped Interpolation- GIS using sample points to assign values to the areas in between them Continuous data can also be areas enclosed by boundaries (everything within boundary must be same type) Features Summarized by Area: counts or density of individual features within an area (ex: number of businesses in each zip code) Data value applies to the whole area and not a specific place within it Lots of data (especially demographic data) is sorted by area GIS can be used to aggregate data that lies within similar areas Ways of Representing Geographic Features Vector Each feature is a row in a table Shapes defined by x,y locations Features can be discrete locations or events, lines, or areas Lines represented as series of coordinate pairs Areas defined by borders and represented as polygons Vector data analysis often times involves summarizing attributes in layer\u2019s data table Raster Features represented as matrix of cells in continuous space Each layer represents one attribute Analysis is combining layers to create new layers Cell size affects results of analysis\/map quality Cell size should be based on original map scale and minimum mapping unit Discrete features and data summarized by area usually use vector model Continuous categories either vector or raster Continuous numeric values are raster Map projection&#8211; translate locations on the globe onto flat surface Distort shape of features being displayed GIS systems usually already have their databases in the same coordinate system and projection Understanding Geographic Attributes Attribute Values Categories Groups of similar things that help you organize your data Category values can be represented as numeric codes or as text (abbreviated) Ranks Put features in order from high to low Used when direct measures are difficult or quantity represents multiple factors Counts and Amounts Total numbers Ratios Show relationship between two quantities Created by dividing one quantity with another for each feature Evens out differences between large and small areas Proportions- what part of a total each value is Density- distribution of features or values per unit area Working With Data Tables Three common operations: selecting, calculating, summarizing Selecting Select features to work with subset or assign new attribute In form of logical expression (code) Calculating Calculate attribute values to assign new values to features in the table Summarizing Could be mean, frequency, total, etc. &nbsp; Chapter 2- Mitchell Why Map Where Things Are? To see where\/what an individual feature is However looking at distribution of features allows patterns to form Can show you where to take action, or what areas meet your criteria Deciding What To Map To look for geographic patterns, map features in a layer using different symbols Information Gained From Mapping Where features are\/aren\u2019t Locations of different features to look for patterns Make sure map is appropriate for audience Preparing Your Data Make sure features being mapped have geographic coordinates GIS databases have coordinates assigned, incoming info must have coordinates (street address or latitude-longitude) When mapping by type, each feature must have an identifier for its type Many categories are hierarchical Sometimes a single code can indicate multiple types (major type and subtype) Making Your Map To create, tell GIS your features and their symbols Mapping a Single Type Draw all features using same symbol Can use this to find differences in the feature to explore further What The GIS Does Stores location as pair of coordinates or set of coordinate pairs Individual locations: GIS draws symbol for that specific point GIS can also draw lines for line features, also draws area outlines Using a Subset Can map features in subset based on specific category values Usually done for individual locations (linear features would often be incomplete) For continuous data, you would be leaving out context of surrounding areas Mapping By Category Draw features by using different symbol for each category value What the GIS does Stores category value for each feature in table Separately stores specified symbols Features might belong to multiple categories Sometimes useful to make multiple maps with different categories to compare Display no more than seven categories on one map (also affected by distribution of features and map scale) Hard to distinguish categories on maps with small features For large maps, multiple categories can distort trends and make it harder to find differences between categories Conversely, important not to have too few categories on smaller maps (don\u2019t leave out info) If more than 7 categories, group the categories The way categories are grouped can influence readers\u2019 perception (categorize carefully!) Ways to group categories:\u00a0 Assign each record two codes\u00a0 create table containing one record for each detailed code with its corresponding general code Assign same symbol to various detailed categories that are apart of a general category Symbols used to display data are important to display it properly For areas\/raster layers: display similar categories in different shades of same color For linear features: use different widths\/patterns (text labels could also be useful) Maps more meaningful when they contain recognizable features, put reference features in light colors Reference feature&#8211; feature on map that makes the area identifiable Some GIS software provides base maps with reference features Analyzing Geographic Patterns Play with map scale to try and find identifiable patterns in features Exceptions can reveal further causes\/areas of further interest Use statistics to more scientifically find relationships between different features &nbsp; Mitchell- Chapter 3 Why Map The Most And The Least Find places that meet criteria to take action or see relationships between places Mapping based on quantities adds additional info What Do You Need To Map Discrete features Locations, linear features usually represented by graduated symbols; area by shading Continuous phenomena can be defined areas or surface of continuous values Defined areas: graduated colors Surfaces: graduated colors, contours, 3D perspective view Data summarized by area displayed by shading each area Keep in mind whether or not you are exploring data or presenting your map Understanding Quantities Quantities: counts or amounts, ratios, ranks Counts and Amounts Count- actual number of features on map Amount- total of value associated with each feature Can be mapped for discrete features or continuous phenomena counts\/amounts can skew data for areas with size variability Ratios Evens out differences for large\/small areas (shows distribution of features) Proportions often represented as percentages Density good for showing distribution when large area size variability Create ratios by adding new field to layer\u2019s data Ranks Useful when direct measures are difficult Assign ranks based on another feature attribute Creating Classes Counts, amounts, and ratios grouped into classes because each feature has a potentially different value Valuable for maps used for public discussion Mapping individual values = more accurate picture If mapping ranks, assign one symbol to each rank Can map ratios, counts, or amounts using individual values if: No more than 11-12 unique values &lt;20 features Classes- group features with similar values by assigning same symbol Important to consciously define class ranges Create classes manually if looking for features that fit specific criteria or comparing features to meaningful value Use standard classification scheme if wanting to group similar values to find patterns Four most common schemes Natural breaks- classes based on natural groupings of data values GIS automatically determines high and low value for each class using math to test class breaks, maximizes difference between classes Good for mapping not evenly distributed data values Quantile- each class contains equal number of features GIS adds up number of features (plus puts them in order) then equally separates them into number of classes specified Good for comparing areas of similar size, mapping evenly distributed data, emphasizing relative position of feature Equal interval- difference between high and low values is the same for every group GIS subtracts lowest dataset from highest then divides that number by number of classes specified Good for presenting info to nontechnical audience and mapping continuous data Standard deviation- placed in classes based on how they deviate from the mean GIS finds mean, then calculates standard deviation and separates classes Seeing what features are above\/below mean value Displaying data with lots of values around mean Plot data values in chart to see their distribution Easy to change class ranges in GIS so try different ones Outliers- few extremely high or low values To deal with them: Put each in its own class Group them together in a class Group them with next closest class Draw them using special symbol While exploring number of classes, start with more and work way down until desired clarity Rounding data when reasonable to make it palatable Give classes meaningful names Making a Map GIS options to show quantities Graduated symbols Which features: locations, lines, areas Which values: counts\/amounts, ratios, ranks Graduated colors Which features: areas, continuous phenomena Which values: ratios, ranks Charts Which features: locations, areas Which values: counts\/amounts, ratios Contours Which features: continuous phenomena Which values: amounts, ratios 3D perspective views Which features: continuous phenomena, locations, areas Which values: counts\/amounts, ratios Legend- displays subset of values and symbols to indicate relative value of individual features Consciously choose colors to attract attention to what you want to Charts on maps useful for quick study of patterns Pie charts: show how much of total amount each category takes up Bar charts: show relative amounts Use contour lines to show rate of change in values across an area Choose interval small enough to give surface definition but not too small that the lines are too close together Label with value Use bold line for every fifth interval When using 3D perspective have viewer in proper spot so tall parts don\u2019t block shorter ones Z-factor- value specified to increase the variation in the surface so differences are easier to see Looking For Patterns Look at transition from highest to lowest values See distribution of values (clustered or spread out) Can summarize up but not down<\/p>\n","protected":false},"author":2331,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-5043","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\/5043","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\/2331"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=5043"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5043\/revisions"}],"predecessor-version":[{"id":5044,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/5043\/revisions\/5044"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=5043"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=5043"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=5043"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}