Personal summary\/Comments<\/p>\n
Chapter 1 – Introducing GIS analysis\u00a0<\/strong><\/p>\n Chapter one explains what GIS analysis is and helps us understand what geographic features\/attributes are.\u00a0 For example, the chapter starts by stating that “GIS analysis is a process for looking at geographic patterns in your data and at relationships between features”.\u00a0 Which is basically saying that, from the layered maps or the collection of maps used to actually do GIS, it’s just an analysis of that data that helps find some sort of correlation to make the data make sense.\u00a0 That’s what I got, at least; it then goes into talking about what I assume are the steps for GIS analysis.<\/p>\n Step one<\/strong> – Framing your question: this step covers the fundamentals of what you’re actually asking or what you’re trying to prove\/show; in the reading, they used “Where were most of the burglaries last month”?\u00a0 It also states that you should try to be as specific as possible and approach the question with different methodologies depending on what you’re actually asking and how you think it can be resolved.<\/p>\n Step two<\/strong> – Understand your data: this step tells you that, to understand your data, you need to know what’s missing and how to acquire it; the chapter mentions that sometimes one method of looking at data will only get you so far. Which means sometimes you’ll need to either approach it with a different method or gather new layers to help map out the issue.<\/p>\n Step three<\/strong> – Choose a method: the chapter states that there are almost always 2 -3 methods to obtain information. (However, it doesn’t really give you any methods to help you get an actual idea of said methods. Which is a little disappointing)\u00a0 It then tells you that the same method won’t always be useful; it’s up to the person whether or not they believe said method is viable.<\/p>\n Step four<\/strong> – Look at results: basically states that you interpret the data to help it make sense<\/p>\n Step five<\/strong> – Look at the results: This step states that the results can come in all sorts of ways. Such as maps, charts, or tables. The reason for this is that some questions are just better explained in different expressions than others.<\/p>\n Chapter 2 – Why Map Where Things Are<\/strong><\/p>\n Based on the title of this chapter, you can assume it was primarily about mapping and why things are mapped. As for the overall objective of this chapter, it was to explain the importance of mapping things, what exactly your mapping is, and preparing\/analyzing your patterns\/data. The chapter starts by explaining the importance. “Mapping where things are can show you where you need to take action.” In this instance, they go back to their original question of burglary locations or just overall crimes. They then explain that by mapping out said crimes, they are able to create police routes to monitor the areas with higher crime rates. This tied into “what to map” because in this example they wanted to lower crime rates, so they mapped out all the areas with crime, not just some but all crime. They then created a patrol route.<\/p>\n I assumed this is kinda how cops created their routes (not sure if this is even an actual real-life thing or just an example), but it makes sense that this is how they would do it. (Once again, if this is actually how they make their patrols). I also had no clue that GIS could be used for things like this, well not until last week when I officially found out what GIS is.<\/p>\n In the reading, it also talks about categorizing, such as color-coding specified areas so you know what’s where. However, in the reading, they specifically mentioned 3 options.<\/p>\n Option one<\/strong> – Assign a general code to each record in the database, like RUR (Rural) and RES (Residential)<\/p>\n Option two<\/strong> – Create a linked table to match detailed codes with general codes. This one kinda confused me; it showed a picture with RUR (Rural) and RES (Residential) as general codes and some other letters\/ numbers as general codes<\/p>\n Option three<\/strong> – Assign categories on the fly by specific symbols (this is the one where everything is color-coded)<\/p>\n Chapter 3 – Mapping the Most and Least<\/strong><\/p>\n As the title states, this chapter primarily talks about mapping both the most and the least of your specified target. The reason for this is that it allows you to gauge the relationships between them. If you were to only map the most or high end, everything would look relatively bad or good, depending on the topic. (The same effect on the inverse)<\/p>\n In the reading, it uses mapping both the most and least to effectively track past and ongoing events. One example of this in the chapter they talk about is average annual precipitation. They track both the most and least to help make a gradient of color (dark blue = more rain while light blue = less rain). Now, the reason I chose this one specifically is that this is exactly what you see every day on the news; if you watch a weather channel, they’re going to show the amounts of rainfall, both the most and the least. This helps prove that it’s an effective measure.<\/p>\n Let’s say they focused on the most, and you got rained on because it didn’t make the cut; I know\u00a0 I’d be annoyed.\u00a0 So it makes sense that you should include both the most and the least.<\/p>\n <\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" Personal summary\/Comments Chapter 1 – Introducing GIS analysis\u00a0 Chapter one explains what GIS analysis is and helps us understand what geographic features\/attributes are.\u00a0 For example, the chapter starts by stating that “GIS analysis is a process for looking at geographic patterns in your data and at relationships between features”.\u00a0 Which is basically saying that, from the layered maps or the collection of maps used to actually do GIS, it’s just an analysis of that data that helps find some sort of correlation to make the data make sense.\u00a0 That’s what I got, at least; it then goes into talking about what I assume are the steps for GIS analysis. Step one – Framing your question: this step covers the fundamentals of what you’re actually asking or what you’re trying to prove\/show; in the reading, they used “Where were most of the burglaries last month”?\u00a0 It also states that you should try to be as specific as possible and approach the question with different methodologies depending on what you’re actually asking and how you think it can be resolved. Step two – Understand your data: this step tells you that, to understand your data, you need to know what’s missing and how to acquire it; the chapter mentions that sometimes one method of looking at data will only get you so far. Which means sometimes you’ll need to either approach it with a different method or gather new layers to help map out the issue. Step three – Choose a method: the chapter states that there are almost always 2 -3 methods to obtain information. (However, it doesn’t really give you any methods to help you get an actual idea of said methods. Which is a little disappointing)\u00a0 It then tells you that the same method won’t always be useful; it’s up to the person whether or not they believe said method is viable. Step four – Look at results: basically states that you interpret the data to help it make sense Step five – Look at the results: This step states that the results can come in all sorts of ways. Such as maps, charts, or tables. The reason for this is that some questions are just better explained in different expressions than others. Chapter 2 – Why Map Where Things Are Based on the title of this chapter, you can assume it was primarily about mapping and why things are mapped. As for the overall objective of this chapter, it was to explain the importance of mapping things, what exactly your mapping is, and preparing\/analyzing your patterns\/data. The chapter starts by explaining the importance. “Mapping where things are can show you where you need to take action.” In this instance, they go back to their original question of burglary locations or just overall crimes. They then explain that by mapping out said crimes, they are able to create police routes to monitor the areas with higher crime rates. This tied into “what to map” because in this example they wanted to lower crime rates, so they mapped out all the areas with crime, not just some but all crime. They then created a patrol route. I assumed this is kinda how cops created their routes (not sure if this is even an actual real-life thing or just an example), but it makes sense that this is how they would do it. (Once again, if this is actually how they make their patrols). I also had no clue that GIS could be used for things like this, well not until last week when I officially found out what GIS is. In the reading, it also talks about categorizing, such as color-coding specified areas so you know what’s where. However, in the reading, they specifically mentioned 3 options. Option one – Assign a general code to each record in the database, like RUR (Rural) and RES (Residential) Option two – Create a linked table to match detailed codes with general codes. This one kinda confused me; it showed a picture with RUR (Rural) and RES (Residential) as general codes and some other letters\/ numbers as general codes Option three – Assign categories on the fly by specific symbols (this is the one where everything is color-coded) Chapter 3 – Mapping the Most and Least As the title states, this chapter primarily talks about mapping both the most and the least of your specified target. The reason for this is that it allows you to gauge the relationships between them. If you were to only map the most or high end, everything would look relatively bad or good, depending on the topic. (The same effect on the inverse) In the reading, it uses mapping both the most and least to effectively track past and ongoing events. One example of this in the chapter they talk about is average annual precipitation. They track both the most and least to help make a gradient of color (dark blue = more rain while light blue = less rain). Now, the reason I chose this one specifically is that this is exactly what you see every day on the news; if you watch a weather channel, they’re going to show the amounts of rainfall, both the most and the least. This helps prove that it’s an effective measure. Let’s say they focused on the most, and you got rained on because it didn’t make the cut; I know\u00a0 I’d be annoyed.\u00a0 So it makes sense that you should include both the most and the least. <\/p>\n","protected":false},"author":2382,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-7307","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\/7307","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\/2382"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=7307"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7307\/revisions"}],"predecessor-version":[{"id":7308,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/7307\/revisions\/7308"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=7307"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=7307"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=7307"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}