{"id":1836,"date":"2024-01-26T12:59:36","date_gmt":"2024-01-26T17:59:36","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=1836"},"modified":"2024-01-26T12:59:36","modified_gmt":"2024-01-26T17:59:36","slug":"rose-week-2","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2024\/01\/26\/rose-week-2\/","title":{"rendered":"Rose Week 2"},"content":{"rendered":"<p><span style=\"font-weight: 400\">Chapter 1<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A bit of review because I took GEOG 292<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS has evolved from simply making maps to analyzing some of the world&#8217;s most pressing issues<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Beginning of chapter focuses some of the creation of GIS maps\u00a0<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Framing a question and why we would even create the map in the first place<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Understanding the data that has been collected for the map. Allows you to think and produce a map in a way that the viewer can absorb the information well and possibly think critically about the information.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This is a part of the \u201cchoose a method\u201d phase it talks about in order to adequately show the data.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Also talks about processing the data and looking at the results. All apart forming the basis of a map.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Understanding geographic features in a map and how the data plays into that.\u00a0<\/span><\/li>\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\">Discrete features<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Location, lines, and actual location pinpointed<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Continuous phenomena<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Blanket entire area of mapping-no gaps<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features summarized by area<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Represents the counts or density of individual features within area boundaries<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Two ways of representing geographic features<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Vector Model: each feature is a row in a table and feature shapes are defined by x,y locations in space<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Raster model: features represented as a matrix of cells in continuous space<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Map projections and coordinate systems<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">All data layers being used should be in the same map projection and coordinate system.<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Ensure accurate results when layers are combined to see relationships<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Types of 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, helps organize and make sense of 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\">Puts features in order from high to low. Used when direct measures are difficult or if the quantity represents a combination of 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\">Show total numbers<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Counts is the actual number of features on a map and an amount can be a measurable quantity associated with a feature<\/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 a relationship between two quantities and are created by dividing one quantity by another for each feature<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Chapter 2<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Better to look at distribution of features rather than individual to gain better understanding<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Different features for different layers<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Cater map towards audience<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Each layer needs geographic coordinates and map features must have a type of category value to identify each easily<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Map features of as a single type must all be using the same symbol<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Easily shows patterns even within the simplest of maps<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">GIS is able to put the data, location, and feature types all together in order to make a cohesive map\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Using a subset of features allows you or the user to narrow down the the category value to something more specific or even make the range more broad<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping features by category can provide understanding on how a place functions<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Features may belong to more than one category, using different categories within the map can reveal different and addition patterns on the data<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Too many categories within the same map is detrimental.\u00a0<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Display no more than seven different categories<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">When mapping an area that is large relative to the size of the features, using more than seven categories can make the patterns to hard to determine(map scaling)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">In smaller areas that are being mapped, individual features are easier to distinguish, so more categories will also be easier to distinguish<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Using too few categories can cause important info to be left out<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><span style=\"font-weight: 400\">Chapter 3<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">People map where the most and least are to find places that meet their criteria and take action or in order to observe relationship between places and data<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To map the most and least you map features based on a quantity associated with each<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Adds an additional level of info beyond mapping the locations of features<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">By mapping the patterns of features with similar values you\u2019ll see where the most and least are<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">You can map quantities associated with discrete features, continuous phenomena, or data summarized by area<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Must keep the purpose of the map and the intended audience in mind in order to help decide how to present the info on your map<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Once you determined what type of quantities you have, need to decide how to represent them on the map<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Either assigning each individual value its own symbol or by grouping the value into classes<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Mapping individual values you present an accurate picture of the data since you don&#8217;t group features together<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">May require more effort on the part of map reader to understand the info<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">To decide which scheme to use, need to know how the data values are distributed across their range<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Create bar chart and set horizontal axis to be attributed values and vertical axis the number of features having a particular value<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Look at outliers closely as they may be result of an error in the database or anomalies based on small data samples or may be completely valid<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Once decided how to classify data values, you\u2019ll want to create a map that presents the info to map readers as clearly as possible<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Keep map simple and present only the info necessary to show patterns in data<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Chapter 1 A bit of review because I took GEOG 292 GIS has evolved from simply making maps to analyzing some of the world&#8217;s most pressing issues Beginning of chapter focuses some of the creation of GIS maps\u00a0 Framing a question and why we would even create the map in the first place Understanding the data that has been collected for the map. Allows you to think and produce a map in a way that the viewer can absorb the information well and possibly think critically about the information. This is a part of the \u201cchoose a method\u201d phase it talks about in order to adequately show the data. Also talks about processing the data and looking at the results. All apart forming the basis of a map. Understanding geographic features in a map and how the data plays into that.\u00a0 Types of features Discrete features Location, lines, and actual location pinpointed Continuous phenomena Blanket entire area of mapping-no gaps Features summarized by area Represents the counts or density of individual features within area boundaries Two ways of representing geographic features Vector Model: each feature is a row in a table and feature shapes are defined by x,y locations in space Raster model: features represented as a matrix of cells in continuous space Map projections and coordinate systems All data layers being used should be in the same map projection and coordinate system. Ensure accurate results when layers are combined to see relationships Types of attribute values Categories Groups of similar things, helps organize and make sense of data Ranks Puts features in order from high to low. Used when direct measures are difficult or if the quantity represents a combination of factors Counts and Amounts Show total numbers Counts is the actual number of features on a map and an amount can be a measurable quantity associated with a feature Ratios Show a relationship between two quantities and are created by dividing one quantity by another for each feature Chapter 2 Better to look at distribution of features rather than individual to gain better understanding Different features for different layers Cater map towards audience Each layer needs geographic coordinates and map features must have a type of category value to identify each easily Map features of as a single type must all be using the same symbol Easily shows patterns even within the simplest of maps GIS is able to put the data, location, and feature types all together in order to make a cohesive map\u00a0 Using a subset of features allows you or the user to narrow down the the category value to something more specific or even make the range more broad Mapping features by category can provide understanding on how a place functions Features may belong to more than one category, using different categories within the map can reveal different and addition patterns on the data Too many categories within the same map is detrimental.\u00a0 Display no more than seven different categories When mapping an area that is large relative to the size of the features, using more than seven categories can make the patterns to hard to determine(map scaling) In smaller areas that are being mapped, individual features are easier to distinguish, so more categories will also be easier to distinguish Using too few categories can cause important info to be left out Chapter 3 People map where the most and least are to find places that meet their criteria and take action or in order to observe relationship between places and data To map the most and least you map features based on a quantity associated with each Adds an additional level of info beyond mapping the locations of features By mapping the patterns of features with similar values you\u2019ll see where the most and least are You can map quantities associated with discrete features, continuous phenomena, or data summarized by area Must keep the purpose of the map and the intended audience in mind in order to help decide how to present the info on your map Once you determined what type of quantities you have, need to decide how to represent them on the map Either assigning each individual value its own symbol or by grouping the value into classes Mapping individual values you present an accurate picture of the data since you don&#8217;t group features together May require more effort on the part of map reader to understand the info To decide which scheme to use, need to know how the data values are distributed across their range Create bar chart and set horizontal axis to be attributed values and vertical axis the number of features having a particular value Look at outliers closely as they may be result of an error in the database or anomalies based on small data samples or may be completely valid Once decided how to classify data values, you\u2019ll want to create a map that presents the info to map readers as clearly as possible Keep map simple and present only the info necessary to show patterns in data<\/p>\n","protected":false},"author":2094,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-1836","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\/1836","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\/2094"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=1836"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1836\/revisions"}],"predecessor-version":[{"id":1837,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1836\/revisions\/1837"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=1836"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=1836"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=1836"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}