{"id":7611,"date":"2026-09-25T19:51:52","date_gmt":"2026-09-26T00:51:52","guid":{"rendered":"https:\/\/sites.owu.edu\/geog-291\/?p=7611"},"modified":"2026-09-25T19:51:52","modified_gmt":"2026-09-26T00:51:52","slug":"montana-week-5","status":"publish","type":"post","link":"https:\/\/sites.owu.edu\/geog-291\/2026\/09\/25\/montana-week-5\/","title":{"rendered":"Montana week 5"},"content":{"rendered":"

Tutorial<\/b><\/p>\n

Chapter 4<\/b><\/p>\n

 <\/p>\n

This chapter was all about working with datasets. The first 2 subchapter modules had you implement data sets into the tutorial and started with some dataset management. Later chapters focused on summing data, selecting by certain data fields, and joining data types to find the answers you desire. There was also the introduction of SQL queries which gave some baseline knowledge on how one might code within the SQL language to get the desired data.<\/span><\/p>\n

\"\"<\/p>\n

\u00a0Above is a Maricopa County figure separated by municipalities that was implemented in the first sub module.<\/span><\/p>\n

\"\"<\/p>\n

You could switch between the normal easy to read GIS interface and the SQL coding tab to see how the identifiers would be used and written in a SQL query.<\/span><\/p>\n

 <\/p>\n

Chapter 5<\/b><\/p>\n

First modules focused on teaching about distortion in a chunk of the world displayed. It illustrates how world maps are less accurate than smaller maps where all features are on a similar geographic plane. Ex: maps of the US are more accurate than maps of the world that have inaccurate representations of Greenland, Antarctica, etc. Many of the modules in this chapter also introduced various coordinate systems to label distinct features at exact locations. There was a lot of work that focused on finding the correct downloaded data in file explorer and implementing it into the GIS. I probably struggled with this chapter the most but I thought the last module was pretty cool and I can see the real world applications for these processes.<\/span><\/p>\n

This first map displays libraries spread across New York City.<\/span><\/p>\n

\"\"<\/p>\n

This second one is a map of Hennepin County, Minnesota with elevation contours and bike routes downloaded from the USGS website.<\/span><\/p>\n

\"\"<\/p>\n

Chapter 6<\/b><\/p>\n

This chapter had us focus on merging and breaking up spatial entities using both the merge tool and dissolving polygons to generalize distinct areas into more regular polygons. It had us use selection tools to find all streets within an area and used the pairwise clip tool to cut off unnecessary street data(pictured below).<\/span><\/p>\n

\"\"<\/p>\n

There was a large focus on using geoprocessing tools in this chapter as we did various processes. The image below is a shot of New York fire streets. We can manipulate the data in a way that would be useful to firemen in the city.\u00a0<\/span><\/p>\n

\"\"<\/p>\n

The last module showed similar use by showing the total number of people with disabilities in certain tracts and providing the information of where these tracts fall within fire station territories. I assume that this is useful because firemen have to assume that some people who are disabled(ex: in a wheelchair, can\u2019t get out of bed) may be harder to account for at the scene of a fire or they may need medical assistance themselves.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Tutorial Chapter 4   This chapter was all about working with datasets. The first 2 subchapter modules had you implement data sets into the tutorial and started with some dataset management. Later chapters focused on summing data, selecting by certain data fields, and joining data types to find the answers you desire. There was also the introduction of SQL queries which gave some baseline knowledge on how one might code within the SQL language to get the desired data. \u00a0Above is a Maricopa County figure separated by municipalities that was implemented in the first sub module. You could switch between the normal easy to read GIS interface and the SQL coding tab to see how the identifiers would be used and written in a SQL query.   Chapter 5 First modules focused on teaching about distortion in a chunk of the world displayed. It illustrates how world maps are less accurate than smaller maps where all features are on a similar geographic plane. Ex: maps of the US are more accurate than maps of the world that have inaccurate representations of Greenland, Antarctica, etc. Many of the modules in this chapter also introduced various coordinate systems to label distinct features at exact locations. There was a lot of work that focused on finding the correct downloaded data in file explorer and implementing it into the GIS. I probably struggled with this chapter the most but I thought the last module was pretty cool and I can see the real world applications for these processes. This first map displays libraries spread across New York City. This second one is a map of Hennepin County, Minnesota with elevation contours and bike routes downloaded from the USGS website. Chapter 6 This chapter had us focus on merging and breaking up spatial entities using both the merge tool and dissolving polygons to generalize distinct areas into more regular polygons. It had us use selection tools to find all streets within an area and used the pairwise clip tool to cut off unnecessary street data(pictured below). There was a large focus on using geoprocessing tools in this chapter as we did various processes. The image below is a shot of New York fire streets. We can manipulate the data in a way that would be useful to firemen in the city.\u00a0 The last module showed similar use by showing the total number of people with disabilities in certain tracts and providing the information of where these tracts fall within fire station territories. I assume that this is useful because firemen have to assume that some people who are disabled(ex: in a wheelchair, can\u2019t get out of bed) may be harder to account for at the scene of a fire or they may need medical assistance themselves.<\/p>\n","protected":false},"author":2420,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-7611","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\/7611","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\/2420"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=7611"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7611\/revisions"}],"predecessor-version":[{"id":7619,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7611\/revisions\/7619"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=7611"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=7611"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=7611"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}