Geography 291: Geospatial Analysis with Desktop GIS

Mitchell Chapter 4

Chapter 4  is focused on what density is, and how to map density via GIS. Mapping density is important as allows you to see patterns of where features are concentrated. This is relatively important as this helps you find areas that require action or or monitor changing conditions. In my opinion, Mitchell’s example of a crime analyst helped me understand why density maps are important. A crime analyst may map the density of burglaries occurring over a year, per square mile, to compare different parts of the city. This aligns with the goals of mapping density, as a crime analyst may then take this data to let policymakers know where intervention is necessary.

The author discusses two ways of mapping density, which is by defined area and by density surface. Mapping density by defined area involves mapping density geographically using a dot map, or calculating the density value for each area. The closer together the dots are, this means that the higher the density of features are within that specified area. Mapping density by density surface involves the creation of a density surface in GIS as a raster layer. Each cell in the layer gets a density value, such as a number of businesses per square mile, based on the number of features within the radius of the cell. Creating a density surface seems like the easiest possibility to me as this technique is used if you have individual locations, sample points, or lines– which is great for raw data that has yet to be analyzed or summarized by another analyst/researcher. In order to map density for defined areas, you may calculate a density value for each defined area or create a dot density map. A density value requires the user to calculate density based on the areal extent of each polygon, while the creation of a dot density map allows for the user to map each area based on a total count or amount and specify how much each dot represents. I find this chapter very useful to understand how to plot features on a map that reflect density, and I see this how this may be applied to the field of public health or epidemiology in the form of disease clusters.

Mitchell Chapter 5

Chapter 5 discusses why it is important to find what is inside a location– which lets you see whether an activity occurs inside an area or summarize information for each of several areas so you can compare them. In order to find what’s inside, you can draw an area boundary on top of the features, use an area or boundary to select the inside and list or summarize them, or combine the area boundary and features to create summary data. It is important to find what is inside a single area, as this allows for intervention. Single areas include: a buffer that defines a distance around some features,  an administrative or natural boundary, an area that you draw manually, or a service area around a central facility. Furthermore, finding how much of something is inside each of several areas lets you compare the areas, which can include state parks, zip codes, watersheds, stores, or floodplains.

Mitchell discusses three ways of finding what’s inside: drawing areas and features, selecting the features inside the area, and overlaying the areas and features. Drawing areas and features are good for seeing whether one or a few features are inside or outside a single area, and all you need is a dataset containing the boundary of the area or areas and a dataset containing the features. Selecting the features inside the area is a good approach for getting a list or summary of features inside a single area, or a group of areas you’re treating as one. For this, you need the dataset containing the areas and a dataset with the features, including any attributes you want to summarize. Finally, overlapping the areas and features is good for finding which features are in each of several areas or finding out how much of something is in one or more areas. For this approach you need the data containing the areas and a dataset with the features, including any attributes you want to summarize.

Mitchell Chapter 6

Chapter 6 discusses how to find what is nearby, which lets you see what’s within a set distance or travel range of a feature. This lets you monitor events in an area, or find the area served by a facility or the features affected by an activity. It is important to map what’s nearby, as you can find out what’s occurring within a set distance of a feature, and find features inside an area that is affected by an event or activity. I personally see this being applied for natural disasters, as you may be able to see areas that have been affected or areas that are in more of a need.

The author then discusses three ways of finding what’s nearby, which includes straight-line distance, distance or cost over a network, and cost over a surface. Straight-line distance can specify the source feature and the distance, and the GIS finds the area or the surrounding features within the distance. Straight-line distance is good for creating a boundary or selecting features at a set distance around the source. For this, you need a layer containing the source feature and a layer containing the surrounding features. The second way of finding what’s nearby is distance or cost over a network, in which the user specifies the source locations or travel cost along each linear feature, then the GIS finds which segments of the network are within the distance or cost. This technique is useful for finding what’s within a travel distance or cost of a location, over a fixed network. In order to use distance or cost over a network, locations of the source features, a network layer, and in most cases, a layer containing the surrounding features are required. The last technique is cost over a surface, in which the user specifies the location of the source features and a travel cost, then the GIS creates a new layer showing the travel cost from each source feature. This is good for calculating overland travel cost, and you need a layer containing the source features and a raster layer.

Chapter 1 

Chapter 1 helped me to better understand what GIS really is and what it’s supposed to do. I thought that GIS was pretty technical and computer-based, but I realized through reading Chapter 1 that GIS analysis really begins with thinking through a question. GIS is a system to store, manage, analyze, and display spatial data, but the value of GIS depends on how well the analyst frames the problem. The author, Mitchell, points to important concepts that include geographic features, attributes, and layers, and shows how they all contribute to answering a question. What I found interesting was that it’s not accidental or arbitrary to do a GIS analysis; you make a decision about what you want to find out and then use appropriate data to do it. I think I now see it as a process of reasoning rather than a technical process. I also appreciated that I could see how maps were used to make important decisions, including public policy, and that it really makes you think about your decisions, even small ones, that you make while working with your data. Reading this chapter really made me think about how important it is to be clear about what you want to do before you start to do it. It also made me realize the level of responsibility that comes with conducting GIS analysis, as the choices you make at the beginning can affect how other people will interpret a place or a pattern. It also made me ask questions such as: How do analysts ensure that they frame their questions correctly? How do they deal with incomplete data? How does uncertainty play a role when maps are being used to make decisions?

Chapter 2 

In Chapter 2, Mitchell discusses how before analyzing why something is happening, one should first understand where it is happening. He goes on to say that mapping locations is the first step in GIS analysis and helps one understand basic spatial patterns such as clustering, dispersion, and gaps. This may sound like a very basic concept, but as I read through this chapter and the rest of the book, I understand why this concept is important. Sometimes it can be difficult to understand patterns when using a table or list, but with a map, it can instantly become clear. Another important point that Mitchell makes is how scale affects a map. What may look significant at one scale may not look significant at another scale, and this shows how easy it is to come to a false conclusion when one does not think about scale. Another important point that was discussed in this chapter was how mapping involves making decisions about what to map and how to map it. This shows how mapping can sometimes be more interpretive than I initially thought. I found this to be interesting because sometimes when one looks at a map, it seems to be a very factual piece of work, but with this reading, I can see how it involves interpretation just as any other type of analysis does. This chapter has made me think about how mapping can sometimes mislead people unintentionally if one does not make these decisions carefully enough. Some questions that I had while reading this chapter were: What is the right way to go about choosing a scale when mapping? What is the right way to go about choosing a classification method to avoid misleading patterns? 

Chapter 3 

Chapter 3 introduces the reader to the importance of mapping quantities in providing more depth in the analysis, rather than just the location of the data. Mitchell introduces the reader to the difference between mapping totals and mapping ratios or density. It was clear that the importance of normalization cannot be overstated, especially when dealing with data that is not normalized. A larger area is likely to have higher totals despite the density being low. Another important aspect of mapping quantities that the author introduces is the different ways in which data is classified. I found the chapter interesting in that the author shows the reader that the choice of classification is likely to affect the general look of the map. Another important aspect that the author introduces is the issue of dealing with outliers. In some cases, the outlier is likely to distort the map if not handled with care. This reminded me that the importance of understanding the data cannot be overstated before mapping the data. The author also introduces the reader to the importance of density mapping in highlighting the data. In my view, this chapter reminded me that mapping quantities is a powerful tool that requires careful consideration in order to avoid misinterpretation. After going through this chapter, I had some questions in my mind. When is the use of totals more important compared to the use of ratios? How does one deal with the issue of outliers in classification? How does density mapping affect the interpretation of the data?

My name is Kainaat Aslam, and I am a senior at Ohio Wesleyan University. I decided to take GEOG 291 to make myself more comfortable working with spatial data and to gain knowledge of how GIS is actually used in life. I have not really worked much with GIS before, and I am excited to see how mapping and visualization all come together. I like to travel, go out with my friends and explore different places of interest so learning more about geography tools actually feels pretty connected to my interests. I am working and going to school at the moment; hence, I like that this class is flexible and allows me to stay on top of my work with weekly due dates. I have also completed the GEOG 291 Quiz.

Schuurman Chapter 1 Response

In Chapter 1, I learned about the importance and widespread usage of GIS. I have come to realize that GIS is everywhere and that it influences almost every field of study. Schuurman starts off by demonstrating that GIS is involved in numerous fields that people would not associate with GIS. She presents examples such as navigation systems, policing, organ donations, detecting clusters of diseases, agriculture, archaeology, and even the placement of businesses. I was struck by the rapid development of the technology to the point that many people now rely on it on a daily basis without being aware of the degree to which it influences their decisions in life. Schuurman observes that many geographers have a kind of ‘love-hate’ relationship with GIS technology because of its strengths and weaknesses.

Another important concept that stood out in my mind during the reading was the “identity problem” of GIS. What I mean by that is that GIS does not mean one single thing; its definition varies depending on the user’s perspective. A city planner might think of a GIS as a computer program that finds boundaries or locates a property, while a researcher might think of a GIS as a science that concerns itself with the way spatial phenomena are represented in computers.

Another concept that came to mind while reading this chapter is that GIS has both technical and philosophical roots. She mentions some research done in the 1960s that would later influence computerized GIS systems such as the early Canada GIS. The chapter also makes the point that GIS isn’t neutral. The choices people make about things like boundaries, categories, scale, and how the map is displayed all shape the way the information ends up being interpreted. There is always some decision-making involved with GIS that will affect what people interpret from their use of the program. This chapter helped me understand that GIS is not just software but rather an approach to thinking about places and what they mean.

GIS Application 1: Public Health and Disease Mapping

GIS technology is commonly used in the field of public health. GIS can track disease outbreaks and the spread of disease. An outbreak can often be represented as clusters or groups. Using the technology, public health officials can easily pinpoint the areas that are most affected by a disease and plan the most appropriate course of action. Outbreaks tend to occur in clusters on a map, and GIS helps health departments visualize where these clusters are occurring and how they are changing over time. By adding environmental information, population density, or transportation routes on top of the case information, health officials can begin to identify what might be driving the spread of the disease. This makes GIS useful not only for identifying where the disease is occurring, but also for beginning to form hypotheses about why the disease is occurring in a particular place.

https://online.utpb.edu/about-us/articles/gis-geospatial/how-public-health-experts-use-gis-to-fight-disease-and-save-lives/

https://www.cdc.gov/field-epi-manual/php/chapters/gis-data.html

GIS Application 2: Crime hotspot Analysis

Another important application of GIS is the study of crime patterns. Police departments create maps to represent the areas in which various types of crime are occurring and use GIS to identify “hotspots,” or areas that experience repeated or high volumes of crime. This helps to identify the areas that need to be targeted by police patrols or crime prevention programs. Crime mapping also enables the study of the relationship of various environmental factors to crime patterns. Hotspot analysis aids in the identification of crime trends and the evaluation of the effectiveness of crime prevention strategies. 

https://www.esri.com/en-us/industries/blog/articles/crime-analysis-with-arcgis-pro-video-blog-series-part-3

https://www.esri.com/en-us/industries/law-enforcement/strategies/crime-analysis

Mitchell Chapter 4:

This chapter begins with talking about map density and why it is important. Using a density map will allow you to see different features and high/low concentrations of features. You can use the GIS map in order to graph different points of data. There are two different types of mapping: 1) the density of features (like the locations of businesses) and 2) feature values (like the number of employees at each business). There are also two ways to map density, the first one being by the defined area, and the second being by the density surface.

The next section of the chapter compares the two methods of mapping, and allows people to see which method would be better for their data. I found this comparison very useful and something I will come back to! The next step of the mapping process is to calculate the actual density of the area being mapped. A dot map in particular gives people a really quick glance at the density and is very visual. I liked how the graph was portrayed in this. Specifically for a dot density map, they made sure to tell us that we have dots based on smaller areas, but the bigger boundaries would have to be defined. 

I think it was interesting how they discussed calculating density values. It seems to me like they are just based on the cells and what values are in them. But I liked how they included the conversion and equations that would be helpful! The search radius allows for larger and more general patterns within the map. It lets you specifically put what data points you want to be calculated for density in there. Assigning the number of classes and using contours helps with creating the map, as discussed in Chapter 3. The chapter ends with learning about how to discuss your results!

Mitchell Chapter 5: 

As the chapters have discussed, everyone uses GIS differently depending on their job. For example, the authors provided an example of how many drug-related arrests take place within a certain distance of a school, because that will enforce a bigger penalty. There are different types of boundaries you can draw as well. They also discuss how features can be discrete: unique, identifiable features; or continuous: seamless geographic phenomena. You also need to discover if you need a list, count, or summary based on your data. I think it’s cool that you can only choose features that are inside or outside your boundaries and not both, it makes it easier to comprehend. 

However, Mitchell does go on to say that if you need information about what is beyond the area, then you can include that as well. There are three ways of finding out what is inside, and those three ways are: 1) drawing features and areas, 2) selecting the features inside the area, and 3) overlaying the areas and features. Similar to Chapter 4, I liked how they put in a little table of comparison on how to choose the different methods! This is very helpful to me. Making a map is the first step, and after that you have to follow the instructions based on what data you have. Discrete areas are important to note because the parcels inside can affect what is outside. 

You can also specify features using geographic selection, which is finding out what features are in a particular distance of another feature. You can summarize using categories or quantities. The GIS will then select what features are inside the area and then flag the ones that are inside to let us know that they are inside. To read the results you can use the sum, the average/mean, the median, or the standard deviation. The final step is overlaying areas and features, and that seems like the coolest way to me! It will read the boundaries and make a map for us to examine the continuous categories or classes. 

Mitchell Chapter 6:

While using GIS, you can find out what locations and features are nearby. Travelling ranges can include measuring distance, time, and cost, and that can be specific to a certain facility. However, to define a certain range, you can use one of three methods: 1) straight-line distance, 2) measure distance or cost over a network, or 3) the measure of cost over a surface. However, cost does not have to be an amount of money, it can also be measured in time. I thought that was interesting because I didn’t think about it that way! Like in Chapter 5, they talk about a list, count, and summary, and that is how it is defined. 

The authors discuss how the different methods work, and what each method is specific for. Again, they provide a table that allows people to compare the best ways to use each method. If you have features that are within a given distance of a source feature, you should use a straight-line distance method. If you have to create other features in which you have to specify the buffer and source feature, then you create a buffer. It tells you how you can select and tag different features within the map. They also make different diagrams based on the data and also create a distance surface. 

Summarizing discrete and continuous features depends on what data you have, and ArcGIS creates default displays that will do their own colors and features. I think it’s cool that you can specify the colors and boundaries that you want. The GIS will identify the lines in a network, and that will also help define the boundaries. Centers: “they usually represent centers that people, goods, or services travel to or from. You can then find the surrounding features along, or within, the area covered by those lines”. The map will start measuring at the center of your feature, then it will create the map around that and based on your boundaries. You can always make multiple centers too. The chapter ends with more ways to calculate data! It seems pretty easy as long as you’re thorough. 

Blog week 3 

Chapter 4 

This chapter of focused primarily on what density mapping is and the several ways to do this kind of mapping. In the beginning, it begins to explain that density mapping is necessary to show and view the highest concentration of a feature. This can include a wide range of data, such as the number of workers in a business district or the number of homes with children within a certain zipcode. After this, the chapter moves on to describe the different types of density mapping, the benefits and downsides of each, and later describes how to use them and which situations they would be more beneficial to use in. 

The two described versions of mapping density include defined areas and a density surface. A defined area is typically a dot map or essentially individual locations. Often, these kinds of maps are used when you’re already using data like a census, which makes it a lot easier to put in the information. The other kind of density mapping is a density surface, which is made through a GIS raster layer or a contour map. This version of a density map is much more detailed than a defined area, but it also takes quite a lot more work to build these maps, so they’re a little more time-consuming and confusing than a defined area. Although they’re definitely worth it to use in situations where more visibility of the details in your map is necessary. 

Later in the chapter, it then continues to describe how to map density through processes such as the cell size, search radius, and units. As mentioned in the last few chapters as well, it emphasizes the importance of color gradiance and how to situate it. And lastly, it explains how to view these maps and properly evaluate them. 

Chapter 5 

At the beginning of chapter 5, it begins to describe the importance of mapping what’s inside individual areas. One of the examples given was related to crime and being able to find hot spots. This seems to be derived from the density mapping described in the last chapter, but is more specifically related to individual regions to better/analyse things. I also liked the example that was used to explain the way in which areas are decided as more valuable than others for conservation purposes. They further explained how mapping these individual areas and features allows you to see what types of features are in which areas and create a better analysis. 

Then it later continues to talk about the different ways to find what features are within what areas, that being drawing areas and features, selecting inside areas, and overlapping areas. These are all used to find different information about an area or a collection of areas. They also continue to mention that building a map quite frequently, if done well enough, with me, all you need to do is an analysis of certain data and the correlation between features and areas. They also mention how the different ways of showing a defined area are important, depending on the goal in mind. For example, only adding the border of an area emphasizes the border itself, while shading it in or putting a screen over it emphasizes the area as a whole. 

Throughout much of the second half of the chapter, it is almost like a summary or repetition of previous chapters and information. For example, to explain again what vectors are and how rasters are used in GIS, along with what they’re needed for. 

Chapter 6 

For chapter 6, it explains the different ways of finding information in relation to things nearby to what you’re focused on. It begins by explaining the 3 different ways of finding this information. It begins with straight line distance, which is used to define an area of influence by using boundaries; this is used purely to measure distance. Then later explains distance or cost over a network, which measures travel, through cost and distance. Lastly was cost over surface, which is used to calculate areas and travel range. While measuring this through cost. Another thing that was kind of interesting to me was the distinct bands, which, I’m not sure if this was the intention, reminded me of the Chicago school model that explains the sectors of a city. It isn’t the most accurate example of cities, but it’s just what distinct bands remind me of. 

Later in the chapter, it continues to explain the details of the parameters and the necessary parts to finding what’s nearby and how to build maps that will support this goal. 

Something I thought that was kind of interesting was the spider diagram, it’s used to help show when a feature is within range/distance to two different/several locations, and mapping with GIS helps to draw lines between the feature and multiple locations,s so it is easier to visualize these attributes. 

Something else I thought was interesting was when, later on in the chapter, it begins to talk about mapping classes. There’s quite a bit of difference between how features and classes are mapped; the main thing being that it is advised not to map more than 7 features on a map, but if you map more than that, it just advises you to begin using different colors to depict it properly and without confusion.

My name is Muzhda Azizi. I am originally from Badakhshan, Afghanistan. I am currently a junior at Ohio Wesleyan University, majoring in Environmental Studies and minoring in Business. I enjoy being in nature, and I have a strong interest in art, poetry, and linguistics. I have completed the GEOG 291 Week 1 quiz as part of this assignment.

Reflection on Chapter 1:
Reading chapter 1 of GIS: A Short Introduction by Nadine Schuurman helped me understand that GIS is more than just making maps or using software. Before reading this chapter, I thought GIS was mainly about mapping locations and organizing spatial data. However, the chapter explains that GIS has a much deeper meaning and plays an important role in how information is analyzed, interpreted, and used in real-world decision-making.
        One thing that stood out to me was the idea that GIS does not have a single identity. The author explains that GIS can be seen both as a system and as a science. As a system, it includes the tools, software, and data used to create maps and analyze spatial information. As a science, it focuses more on understanding how spatial data is collected, classified, and interpreted. I found this interesting because it shows that GIS is not just technical, but also intellectual. The way data is categorized or displayed can affect how people understand an issue, which means GIS is not completely neutral.
        Another part that I found interesting was the discussion about visualization. The author of this chapter explains that people understand visual information better than numbers or tables. The example of John Snow’s cholera map shows how mapping helped identify the source of the disease by showing patterns that were not obvious before. This shows how powerful and useful GIS can be in areas like public health, environmental studies, and urban planning. At the same time, the chapter also makes it clear that maps can be misleading if the data is incomplete or poorly represented. Overall, this chapter helped me see GIS as more than just a technical skill. I also learned that GIS plays a role in many everyday systems rather than one specific area, even when we do not notice it.

GIS Application 1: Crime Mapping
One way GIS is used in society is crime mapping, where spatial analysis helps law enforcement visualize and understand patterns of criminal activity. According to the Office for Victims of Crime, GIS tools allow agencies to map crime locations and analyze trends, which supports better decision-making for public safety and resource allocation.

Figure 1. Example of GIS layers used in crime mapping.

GIS Application 2: Disaster Management
Another way GIS is used in society is in disaster management. GIS technology helps to identify and map areas that are at risk of natural disasters such as floods and other hazards. By combining different types of data, GIS can highlight vulnerable regions and support planners in making decisions about resource allocation and emergency preparedness. Tools like flood simulation and vulnerability mapping allow officials to see where risks are highest and plan ways to protect communities before disasters occur.

Figure 2. Example of flood risk modeling using GIS to show varying flood depths across an area.

Sources:
GIS Navigator. (n.d.). Disaster management. https://gisnavigator.co.uk/disaster-management/
Office for Victims of Crime. (2003). Crime Mapping. https://ovc.ojp.gov/sites/g/files/xyckuh226/files/pubs/OVC_Archives/reports/geoinfosys2003/cm3.html
Schuurman, N. (2004). GIS: A short introduction (Chapter 1). Blackwell Publishing. https://sites.owu.edu/geog-191/wp-content/uploads/sites/208/2022/10/schuurman_gis_a_short_intro_ch_1.pdf

 

 

Mitchell Notes 

 

Ch 1:

• GIS has become significantly more widespread and readily available since the book was first published in 1999.
• Although GIS has made such advancements so quickly, it is still fundamentally the same, as how it is used hasn’t changed significantly, which means the original basics of understanding are still necessary to implement GIS tools.
• GIS will continue to expand, and more books to assist in public understanding will be published.
• “GIS analysis is a process for looking at geographic patterns in your data and at relationships between features.”
  • GIS can be simple or more complex; maps can be considered analysis or graphing with overlapping data regions.
• First step to GIS is asking a specific spatial question. 
• How you explore the data depends on what your intention with the results is (more professional or casual). 
• It is important to take geographic features into account when analyzing data.
  • “Geographic features are discrete, continuous phenomena, or summarized by area.”
• Analysis should remain consistent, as in all data points and mapping techniques should be in the same format. 
• Attributes: identify, describe, or represent a feature. 
  • Categories = groups of similar things.
  • Ranks = order of features, high to low. Ranks are relative.
  • Counts/amounts = total numbers of observations.
  • Ratios = relationship between two observed quantities.

 

Ch 2:

• GIS takes information from a table and translates it into a mapping format.

• The style and amount of information put into a GIS graph are based on the amount of data collected and the question attempting to be answered.
• The intended audience should be considered when developing maps and figures.
• Each input needs a geographical place.
• Mapping symbols must be consistent and have a unique symbol designated to each category or feature type.
• With more categories, you may need to combine them to make the map easier to read and analyze.
  • The way categories are grouped could change the way the reader interprets the information.

 

Ch 3:

• Mapping features based on quantity adds more depth and information to the figure.
• Goes more into depth on each attribute and how to graph them properly. Also explains each more in depth with examples

Chapter 1 

This chapter introduced me to the simple breakdown of GIS. At first glance, the Geographic information system can seem quite puzzling and often can intimidate others because of the thought of it being solely high-tech. This is a common misconception when it comes to GIS analysis, it is actually less about the software and more about the way you think through a problem. Something that I related was the concept of framing a question and thinking through the process before touching any tools. I compared this to the common saying of “thinking before you speak”, something I try to do whenever I talk. I am someone who doesn’t talk unless needed to, which lets me choose my words carefully and observe the situation around me before I speak. There is also the other half of society who does not think before they speak. These people are similar to those who jump into GIS and map something that they aren’t entirely knowledgeable about, leading to results that mean little to nothing. As I previously mentioned before in my Week 1 post, GIS appears to have a lot of ‘invisible power’ because it is simply everywhere and is constantly influencing our decisions. Through this chapter, I noticed that this power is apparent in the users of GIS, especially when results are shared publicly. Geographic information system analysis can be used in courtrooms and even for policy decisions. This made me realize that the smallest of choices (data sources and parameters) can create serious consequences. With the mention of the realness of GIS analysis, it comes to show how much responsibility and leverage the users of it have. The excerpt not only introduced GIS analysis but also explained that good analysis is dependent on judgment and intentionality rather than technical skill alone. 

Chapter 2

This chapter focused on the importance of mapping where things are before attempting to analyze why they are there. When picking out a book, you look at the cover and almost create a story in your head as to what the story is about. You don’t actually know what the story is about until you read it. Similar to mapping, you can’t know why things are where they are until you put it on a map first and analyze the map. At first, this idea seemed almost too simple and was something I thought to be common sense. However, further into the reading I realized how often people overlook this step. Mapping locations alone can already reveal patterns such as clustering, spacing, or absence, which can raise questions that might not be obvious through data tables alone. This reminded me of how observing a situation quietly can sometimes tell you more than immediately asking questions. It is all in the name – GIS analysis: analyze the situation you are going to use GIS for! One idea that stood out to me was how scale can completely change what a map appears to show. Patterns that look significant when viewed from far away can disappear when zoomed in, and vice versa. This made me think about how easy it is to misinterpret information when only one perspective is shown. It also made me more aware of how maps can unintentionally mislead if the scale is not carefully considered or explained. The chapter also made it clear that mapping is not as objective as it may appear. Choices such as what data to include and how much detail to show influence how the map is understood and perceived. The idea that maps simply present facts is challenged in saying this because it simply isn’t just facts. Instead, they tell a story, and the mapper has control over how that story is told. Overall, this chapter reinforced the idea that even basic maps require thought and intention, and that understanding “where” something is located is often the first step toward understanding much larger patterns.

Chapter 3 

The last reading emphasized how mapping quantities adds another layer of meaning beyond simply showing locations. One of the most important key concepts this chapter made was discussing the difference between mapping raw totals in comparison to using ratios or densities. In the beginning, mapping totals may seem straightforward; though, the chapter explained how this can be misleading. This scenario is especially common when areas vary in size. Larger areas can appear more important simply because they contain more, not because they are more concentrated. Given this context, it made me realize just how easily patterns can be exaggerated or minimized depending on how data is presented. Moving along the reading, I found the discussion on classification particularly interesting. The fact that the same data can look completely different depending on how classes are created made me think about how much influence the mapper has over interpretation (once again). Choosing natural breaks, equal intervals, or quantiles is not just a technical decision. This decision is interpretive and made from that of a human individual. Once more, these decisions reinforce the idea that GIS analysis involves judgment, not just calculation. Another aspect that stood out to me was how outliers can distort a map if they are not handled carefully. One unusually high or low value can change how all other data appears, which again highlights the importance of understanding the data before mapping it. Reading through this chapter made me more aware that maps showing “the most and least” are powerful, yet also risky if created without careful thought. In other words, the users of GIS are responsible for creating maps with intention and meticulous work. It reinforced that GIS is not about producing visually appealing maps, but about presenting information in a way that is accurate and intentional.  

Chapter 1:

 Rather than jumping straight into the intricacies of mapping and data analysis, Chapter 1 stresses the importance of understanding and clearly defining the topic at hand. I believe that this is an effective way to introduce new students to the basics of GIS, as it eases you into it. One major takeaway I noted is that Mitchell highlights how GIS analysis conducted with intent tends to begin with asking the right questions related to the information you need, with more specific questions helping guide your analysis. I had not realized this prior, as I just saw GIS as simply plotting data. I realized we can use GIS to address important problems by asking pressing questions that are specific to the area of interest. It’s also important to note that Mitchell presents GIS systems as accessible, inviting us to ask our own questions and come to our own conclusions and discoveries. This is an exciting revelation for me.

Chapter 1 also introduced me to the basics, like understanding and identifying geographic features as how they are presented within a GIS. My takeaway is that there are many different ways to visualize data as features, depending on what kind of data it is and the purpose of creating a visual for said data. For example, vector vs raster modeling. Vector modeling represents features as points and lines often using coordinate-based data, making it good for plotting things like roads, boundaries, and buildings. Raster modeling represents the features as a grid of cells using continuous data, which is good for plotting things like elevation, temperature, weather patterns, and land types. I found it interesting how these two forms of modeling could technically be used interchangeably for the same purpose, but they are used for whatever they are visually better suited for. 

I feel that explaining how we can all use GIS as an effective tool is the premise and the author’s main goal after reading chapter 1. It introduces GIS analysis as a system that is capable of examining and visualizing geographic data to understand specific spatial patterns, relationships, and trends in a way that I found understandable. It takes this information and directly ties it to visual features within a GIS mapping system. Question: Would reading printed park maps be considered a form of GIS analysis? Where is the line drawn for maps being purely for visualization or analysis?

Chapter 2:

Chapter 2 starts off by building on the foundation that Chapter 1 created by highlighting the importance of visualizing data using mapping. Honestly, I found this redundant. The benefits of mapping data already seemed clear to me. For example, Mitchell discusses how visualising data on maps can help us look for patterns in the distribution of the features, and make decisions based on these patterns. I thought that was obvious, but I appreciate that Mitchell is making things very understandable for new students like myself. Some things that I was unfamiliar with that chapter 2 discusses is deciding what to map, and preparing my data for said map. I learned that when deciding what to map, you need to consider the information you want to analyze and how the map containing this information will be used. This made me realize that it’s important to take into consideration the specific audience the map will be presented to. For example, a highly detailed and overly complicated map is ineffective if it was intended to be made for the purpose of sharing basic information with the general public. As for preparing data, I was highly unfamiliar with the topic. I learned that a crucial first step is to assign geographic coordinates to the feature you wish to plot. Another important thing I learnt is that you need to assign category values to features if there are differing features, or features sorted by type. The category value is a code/tag that identifies the feature type. I often see these categorizations of features when looking at maps, but I’m now realizing that this feature identification can be used for various applications, such as distinguishing areas for city planning. Chapter 2 does a good job at answering basic questions about mapping and how to create a map, as well as explaining how to proficiently analyze these maps.    Question: How can we effectively and critically evaluate data sources to identify biases/untrustworthy information before incorporating it into our GIS analysis?

Chapter 3:

When I first read the title of chapter 3, it being called “Mapping the Most and Least”, I was confused. Unlike the previous titles, what it was trying to convey wasn’t immediately clear to me. However, Mitchell explained it in an understandable fashion. Mapping the most and least means to identify where values relating to your data/criteria are highest or lowest to analyze certain aspects about the data, most often through patterns. If I were to think of an example, I would say that analyzing a low income area for care facilities scarcity is an example of analyzing where values are the least. This is something that I had not previously considered, as I was focused on the idea of mapping where things might be located, not where things might be missing or lacking. It showed me how presenting the quantities of data in different ways is an important thing to consider when deciding what I want the purpose of my map to be. This is just one method of GIS analysis that is presented in chapter 3. Other methods are given.

For example, there are different types of quantities that you can use. According to Mitchell, being aware of the quantity type your mapping can help with deciding how to present your data in the best way. Once the type is determined, a decision must be made about how to represent it on a map. This can be done either through grouping the values into classes or by assigning each value its own individual symbol. I learnt that each choice has its merits, and I now know how to apply them to my own maps. For example, grouping the values into classes is useful for maps with a large range of values to present the data in an easily readable manner. Showing overall patterns is favored over exact data using this type. This would be good for maps about concentration levels of rain or air pollution. On the other hand, assigning each value its own individual symbol is useful for maps where precision matters, and exact values are important due to the specificity of the data. This would be good for maps geared towards recording specific sampling sites, or showing how specific geographic locations may present differently from each other.     Question: What if the data is in a middle ground where it isn’t clear if I should present my data with simplicity or complexity? 

Chapter 1

Chapter one introduces GIS and how it is used to analyze geographic features. The most common analysis people do includes mapping the location, density, and change. GIS analysis is identifying and studying geographic relationships and patterns through maps and data layers. Analysis begins with a question. Your method of analysis depends on what question you have and how you are presenting the results. It is important to know what data you have and what data you need to calculate and create. Studies using approximate data are quicker, but those requiring accurate data take more time. I really like the example the chapter gives in describing the difference: if you are looking at assaults in a city, it will be a quick study, but if the information is used for evidence in a trial, you will need the precise measurements for the locations and numbers in a specific area over a period of time. The results of the GIS analysis can be displayed as a map, table, or chart. It is important to not only understand how GIS works but also what geographic data is being displayed. Discrete locations and lines do not have a distinct location, such as parcels of land value. Continuous phenomena can be measured at any location, so there is data everywhere you are mapping. If the data is not used in an area with boundaries, GIS uses interpolation on a series of points. Interpolation is assigning values to the area between the points. The third type of data is summarized data, which represents the density of certain features within a boundary, such as the number of households within each county. Geographic features can be represented by vectors and rasters. With vectors, features are defined with an x,y coordinate. With rasters, features are represented by multiple cells.

Chapter 2

Chapter two discusses how to prepare and map your data. Through observing a distribution of features, rather than individual ones, you can find patterns in the data. GIS mapping can be used to show where features are and aren’t, and the different types of features. The audience and issue determine how you present your mapped data. Every feature will need geographic coordinates and an identifying code. For individual locations, GIS will put a symbol at the given point. For linear features, GIS draws lines connecting each point. For features within an area, GIS draws an outline. Mapping subsets is common for individual locations rather than linear features because highlighting only linear features doesn’t provide any information about the surrounding areas. You can also map features by category, with each category having a specific symbol. GIS will store a value for each feature in the layer and an assigned symbol for each value. It may be helpful to have separate maps for each data set, otherwise it can get messy if there is too much data. You should keep the maximum number of categories to seven, as it can be difficult for most people to interpret if there are more. You can also group categories if you need to show a lot of data, but keep it to one map. There are three ways to group categories into detailed and general: assign each record two codes, create a table with a record for each detailed code and corresponding general code, or assign one symbol to each detailed category within the general category. It is important to include references such as major highways or rivers so the map can be more meaningfully interpreted. These references should use lighter colors so they don’t take away from the actual data.

Chapter 3

Chapter three explains the importance and process for mapping the most and least. Mapping the most and least can help people solve problems or see relationships. You can map discrete features, continuous phenomena, or data summarized by area. Discrete features are locations, linear, or areas. Continuous phenomena are defined as areas of continuous values. Data summarized by area uses shading based on its value. Maps can be used to find patterns or present patterns that have already been identified. If you want to find patterns, the data needs to be displayed in many different ways and with great detail. If you are presenting previously found patterns, you need only to create a map with generalized data. For mapping the most and least, you assign a symbol to each feature based on a quantity: counts or amounts, ratios, or ranks. A count is the number of features and the amount is the value associated with each feature. Ratios show the relationship between two quantities to even out the differences between large and small areas. Some examples are densities and averages. When summarizing by area, ratios should be used. Ranks show relative values in order from high to low. Ranks can be used, for example, when seeing which soil type in an area is best for growing crops. Classes are used when representing quantities on a map. The four ways to group data into classes are natural breaks, quantiles, equal intervals, and standard deviation. Natural breaks are set by natural groupings of data values. Quantiles have an equal number of features within each class. An equal interval has an equal difference between the high and low values. Standard deviation has features that are placed based on how much the value varies from the mean, which is calculated by the GIS.