{"id":7291,"date":"2026-09-03T10:43:10","date_gmt":"2026-09-03T15:43:10","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=7291"},"modified":"2026-09-03T10:43:10","modified_gmt":"2026-09-03T15:43:10","slug":"bailey-week-2","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2026\/09\/03\/bailey-week-2\/","title":{"rendered":"Bailey Week 2"},"content":{"rendered":"

Chapter 1<\/span><\/p>\n

\u00a0<\/span><\/p>\n

Maps come in many forms, think of paper maps that show minimal information such as roads and towns.\u00a0 GIS maps have spatial pictures and can be created to show in depth information.\u00a0 Chapter 1 is about advance mapping where you can find patterns, trends and work towards solving problems.\u00a0<\/span><\/p>\n

Some key terms I found interesting listed below.<\/span><\/p>\n

 <\/p>\n

Map Features:<\/b> GIS uses three main shapes to draw everything.\u00a0 <\/span>Points,<\/b> which are tiny dots for certain locations. <\/span>\u00a0Lines<\/b>, connected paths such as pathways and roads.\u00a0 <\/span>Polygons<\/b>, shapes with boundaries that outline an area such as a county.<\/span><\/p>\n

 <\/p>\n

Discrete Data<\/b>, has clear edges like property lines.<\/span><\/p>\n

 <\/p>\n

Continuous Data,<\/b> flows across space with out hard borders such as temperature<\/span><\/p>\n

 <\/p>\n

It is amazing that almost everything can be mapped.\u00a0 How can you protect private information from becoming part of this system?\u00a0 I wonder if people can use this tool to commit crimes?<\/span><\/p>\n

 <\/p>\n

Chapter 2<\/span><\/p>\n

 <\/p>\n

This chapter involves plotting locations\u00a0 and spotting groups clustered together.<\/span><\/p>\n

Mapping where things are located.<\/span><\/p>\n

 <\/p>\n

Single Symbol Mapping, <\/b>giving every single item the same icon and color<\/span><\/p>\n

 <\/p>\n

Clusters<\/b>, tight bunches of dots<\/span><\/p>\n

 <\/p>\n

Outliers<\/b>, lone dots far away from everything else<\/span><\/p>\n

 <\/p>\n

If you are going to map everything your map could look messy. Map scale has to be right so that your information can be interpreted.\u00a0 Are there sources to help pick the best map scale?<\/span><\/p>\n

 <\/p>\n

Chapter 3<\/span><\/p>\n

 <\/p>\n

Talks about mapping numbers and the importance of calculating them correctly before putting them on your map.\u00a0 You do not want incorrect information available to interested parties.<\/span><\/p>\n

 <\/p>\n

Data grouping, <\/b>\u00a0how you split up numbers into groups before picking colors<\/span><\/p>\n

 <\/p>\n

Normalization<\/b>, fixing raw counts so a fair comparison can be made.<\/span><\/p>\n

 <\/p>\n

Choropleth Map<\/b>, classic shaded map where areas are colored lighter or darker based on their numbers<\/span><\/p>\n

 <\/p>\n

So you should never map raw totals for large regions. You need to make sure detail is incorporated or your map will just show basic information.<\/span><\/p>\n

 <\/p>\n

How do you choose color shades?<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Chapter 1 \u00a0 Maps come in many forms, think of paper maps that show minimal information such as roads and towns.\u00a0 GIS maps have spatial pictures and can be created to show in depth information.\u00a0 Chapter 1 is about advance mapping where you can find patterns, trends and work towards solving problems.\u00a0 Some key terms I found interesting listed below.   Map Features: GIS uses three main shapes to draw everything.\u00a0 Points, which are tiny dots for certain locations. \u00a0Lines, connected paths such as pathways and roads.\u00a0 Polygons, shapes with boundaries that outline an area such as a county.   Discrete Data, has clear edges like property lines.   Continuous Data, flows across space with out hard borders such as temperature   It is amazing that almost everything can be mapped.\u00a0 How can you protect private information from becoming part of this system?\u00a0 I wonder if people can use this tool to commit crimes?   Chapter 2   This chapter involves plotting locations\u00a0 and spotting groups clustered together. Mapping where things are located.   Single Symbol Mapping, giving every single item the same icon and color   Clusters, tight bunches of dots   Outliers, lone dots far away from everything else   If you are going to map everything your map could look messy. Map scale has to be right so that your information can be interpreted.\u00a0 Are there sources to help pick the best map scale?   Chapter 3   Talks about mapping numbers and the importance of calculating them correctly before putting them on your map.\u00a0 You do not want incorrect information available to interested parties.   Data grouping, \u00a0how you split up numbers into groups before picking colors   Normalization, fixing raw counts so a fair comparison can be made.   Choropleth Map, classic shaded map where areas are colored lighter or darker based on their numbers   So you should never map raw totals for large regions. You need to make sure detail is incorporated or your map will just show basic information.   How do you choose color shades?<\/p>\n","protected":false},"author":2414,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-7291","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\/7291","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\/2414"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=7291"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7291\/revisions"}],"predecessor-version":[{"id":7292,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7291\/revisions\/7292"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=7291"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=7291"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=7291"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}