Month: January 2026

I’m Trinity Fry, a second-year student majoring in Environmental Science and Zoology (most likely majoring in Philosophy and minoring in Neuroscience soon as well). I am recently back from a wildlife rehabilitation program in Guatemala, hence the delayed post.

Reading:

I found the reading quite interesting, informative, and relatable. As an Environmental Science and Zoology student, I did not think the use of computers and codes was something I would have to familiarize myself with. However, I am quickly seeing that change as the uses of GIS and computer programming are broadening every day. As the text states, GIS is a monumental tool for all kinds of fields. From tracking the natural world to mapping human populations to company advertising, GIS is an extremely useful tool. “Students flock to GIS classes in colleges and universities; on-board navigation systems are the mark of a luxury car; police officers are routinely trained in GIS; organ donation has been rationalized using GIS; epidemiologists use GIS to
identify clusters of infectious disease; archaeologists use it to map sites; and Starbucks is reputed to use GIS to site its very successful coffee shops. Indeed, the list of GJS uses is extraordinarily comprehensive; the technology pervades many aspects of modem life.” (Schuurman, 2004, pg. 1). While this tool may seem straight forward, Schuurman does emphasize that simply having the programing is not sufficient, and like any other application, you must know how to implement its uses to understand and use it to its full potential. This text made me more exited to learn about GIS and its applications in my field of interest. This will be a very helpful tool to me in my future career, and I can’t wait to apply it to real-world case scenarios.

Schuurman, Nadine, “GIS: A Short Introduction” Ch 1, pg. 1-20, (2004) schuurman_gis_a_short_intro_ch_1.pdf

GIS Case Study:

1)

 

In this case study, GIS was used to map out the landscapes and forest changes in Ohio. This research was done to track the widespread disturbances and land changes due to the urbanization of highly populated areas, especially those initially settled in the 17th-18th century.  GIS and historical records were used to map out landscapes prior to colonization urbanization and track the changes over time up to modern day. The changes Deines saw included the switch and change of dominant species of areas along with the migration of species to new areas. The mix of urbanization, modern agriculture of Ohio, and introduction of invasive species has drastically changed the land the last few centuries.

Jillian M. Deines “Changes in Forest Composition in Ohio Between Euro-American Settlement and the Present,” The American Midland Naturalist 176(2), 247-271, (1 October 2016). https://doi.org/10.1674/0003-0031-176.2.247

2)

GIS can also be used to track the biodiversity and overlap of species populations. This would be important as urbanization drives populations to overlap and compete, or copulate, in more condensed areas. For example, mallard ducks and black ducks now overlap territories, although these species are behaviorally and genetically differing, they are close enough in relatedness to produce crossbred offspring called the mule duck. GIS can be used to track where these populations overlap and where these hybrid individuals are showing up to see if forced close quarters are causing this interbreeding.

Atlas, “GIS Use Cases- Biodiversity”, n.d. Biodiversity – GIS Use Cases | Atlas

Lavretsky P, Janzen T, McCracken KG. Identifying hybrids & the genomics of hybridization: Mallards & American black ducks of Eastern North America. Ecol Evol. 2019 Feb 27;9(6):3470-3490. doi: 10.1002/ece3.4981. PMID: 30962906; PMCID: PMC6434578. Identifying hybrids & the genomics of hybridization: Mallards & American black ducks of Eastern North America – PMC

Blog Week 2 

 

Chapter 1 

It was interesting learning about the different attributes that are all included in GIS, for example, components such as vectors and rasters. Previously, before this from math class, I had already had an understanding of what a vector is, the actual separation within the map being/had been made. Although I hadn’t heard of what a raster was before this reading, from what I understood from the description, a raster is the geographic area that you are separating from others. Essentially, rosters and vectors form the basis of what GIS operates on, while creating several other methods of organization and overlay. Examples of this are your categories that separate your types of data, or ranks that allow you to have an understanding of the value of things within a certain data set. While counts, amounts, and ratios are a little bit different, considering they’re not a continuous set of data, while categories and ranks are. 

 

GIS as a program seems to me to be a process of sectioning out and boarding things. It’s interesting to see the examples in the text have such a wide variety; it makes me wonder how many different fields of work/career fields this system has made a bit easier. With the examples used, it ranged anywhere from the borders of land ownership, crime, or even the literal borders of different vegetation. 

 

With the use of categories that seem to allow GIS to be an extremely organized system. All while allowing you to overlay different data on top of one another, whether that be looking at the businesses and crime rates together or any other kind of variant. The process of finding specific information that was explained later in the chapter was interesting in how it essentially involves putting in a variety of necessary terms to find the exact information that you need. 

 

Chapter 2 

 

Throughout chapter two for the mapping process in GIS, there is a heavy focus on how to categorize the information within your maps. Quite a large portion of the information describes how to build a map of the necessary features/information that you are attempting to depict. Some of the things I understood were in relation to what content you want to be the focus of the map, like highlighting features in darker colors to bring more attention to those areas. It is very easy to build an overwhelming map, so an important thing to remember is not add more than 7 categories, as mentioned in the chapter. Another way was to combine categories to make them easier to view and understand. With this being said, from what I understand, it seemed like a give-and-take process because it’s easy to lose information while combining categories. 

 

There is also a big emphasis on the symbols you use within your maps, based on the visibility of the symbols and being able to tell the difference between them. Essentially, a majority of the reading is based on the visibility of the maps to the viewer. There was a huge emphasis on the colors used for categories, like using different color schemes can allow for more emphasis on different parts of the map and allow for focus among those categories, while other color schemes can make a map overwhelming to look at for the viewer and become more confusing. Also it seems important to emphasize correlating categories with similar colors as well. The dot data was also interesting to me because it reminded me a lot of when you look at germs or organisms under a microscope, which is a fun comparison since were looking at math data essentially. 

 

Although I struggled quite a bit trying to understand the record and database information. 

 

Chapter 3

For this chapter, as well theres so much information that emphasizes the details of mapping. Which sounds a bit redundant, but it is essentially focusing on the details of spreading out information that explicitly shows the information you want in a way the viewer can best understand. The process of most and least mapping is kind of confusing to me, but from what I could understand about the concept, is allowing the reader or viewer to see the value of the categories through what the chapter was explaining about ranks. This is at least one of the reasons why we should be mapping most and least values. One of the examples used in the chapter was about the temperature of different areas. 

Chapter 3 also felt very repetitive in many of the explanations, for part of it I seemed like it was repeating word for word what had been said in the previous chapter. 

It’s also really interesting how much GIS ( at least many of the examples within the chapters) is predominantly focused on urban planning. 

The classification scheme was really confusing to me. I think the overall idea is that different schemes have different ways of classifying information, and there are ways to tweak it to support your data most accurately. While reading the chapter, I was having a really hard time understanding the concept. Also, defining classes seemed kind of complicated because they essentially have to shift the numbers around to define the classes so that the data stays within the appropriate group instead of getting mixed up. It also seems really easy to misinterpret this data because of how complex this issue seems to me, at least. Overall, mapping seems to have a main prerogative around mapping data in a way that is easy for the viewer to understand.

Mitchell Chapter 1:

Chapter 1 starts out by discussing that GIS analysis is a process for looking at geographic patterns in your data and at relationships between features. I do have experience with GIS analysis during my internship last summer at the Delaware Public Health District. During my internship, I was able to gather surveys- and upon completion, participants dropped a pin (via ArcGIS) indicating which part of Delaware County they resided in. Afterwards, participants indicated their experience with food accessibility and security based on their surrounding geographic area. Based on this GIS analysis, we were able to see which areas of Delaware County were lacking in accessibility and security, and therefore place proper interventions to help those select communities in need.

The chapter goes-on to explain that geographic features are discrete, continuous phenomena, or summarized by area. Discrete includes locations and lines where the actual location can be pinpointed- and at any given spot, the feature is either present or not. Continuous phenomena includes precipitation or temperature- which can be mapped anywhere. Phenomena are data that “blanket the entire area you’re mapping- there are no gaps”. This expression that the author used to describe continuous phenomena made it very simple for me to understand, as the term was confusing to me at first. Summarized data represents the counts or density of individual features within area boundaries. Some examples of these types of features include, “the number of businesses in each zip code, the total length of streams in each watershed, or the number of households in each county”.

Overall Mitchell’s Chapter 1 allowed me to think more analytically regarding GIS. Prior to this chapter, I believed that GIS was a lot of plugging data into existing databases. However, this chapter challenged that idea and made me realize that one also must understand what type of data they are working with, and how to use that appropriate data to make sense of it during analysis.

Mitchell Chapter 2:

This chapter discusses the basis of how to map features and where features are located. The purpose of mapping features is to look at the distribution of features, rather than at individual features, so that you can see patterns that better help understand the area that you are mapping. I see this being able to be used in epidemiology, for example. If a citizen is concerned about cancer rates in a neighborhood, an epidemiologist is able to gather information, plot the data, and analyze frequencies in order to determine if cancer is prevalent in one neighborhood rather than another. Analyzing frequencies also allows for interventions to occur to help communities– and in this case, public health officials can analyze the neighborhood to determine the cause of the cancer rates.

I thought it was very interesting that when creating a map, you tell the GIS which features you would want to display and what symbols to use to draw them. I found this interesting because I thought that you had to create a map entirely from scratch, but it is very interesting to know that the platform provides displays and symbols to choose from. I also learned more about the function of GIS– and that it stores the location of each feature as a pair of geographic coordinates or as a set of coordinate pairs that define shape. Moreover, for individual locations, the GIS draws a symbol at the point defined by the coordinate for each address. For linear features, the GIS draws lines to connect the points that define the shape of streets.

Overall, I found this chapter interesting because I was able to learn more about how GIS functions, which seems to be primarily based on geographic coordinates. I am very excited to start working with the GIS software, and I feel as if this chapter lays a foundation for my understanding to create maps, understand how GIS works, and how to apply features.

Mitchell Chapter 3:

The chapter discusses how to map the least and the most, which allows you to compare places based on quantities, so that you can see which places meet your criteria, or understand the relationship between places. The chapter discusses that public health officials may map the number of physicians per 1,000 people in each census tract to see which areas are adequately served and which are not. It also discusses the type of features you are mapping, which are discrete features and continuous features. Discrete features are individual locations, linear features, or areas. On the other hand, continuous phenomena can be defined areas or a surface of continuous values.

A large portion of the chapter included counts, amounts, ratios, and classes. A count is the actual number of features on a map, while an amount is the total value associated with each feature. However, it may not be the best to use counts and amounts if you’re summarizing by area, as using them can skew the patterns if the areas vary in size. Instead, ratios should be used to accurately represent the distribution of features. Classes were a new concept to me, and group features together with similar values by assigning the same symbol, and specify upper and lower limits. You can specify the classification scheme and number of classes, and the GIS will calculate the upper and lower limit for each class. The four most common schemes are natural breaks, quantile, equal interval, and standard deviation. Natural breaks are good for mapping data visuals that are not evenly distributed. Quantiles are good for comparing areas that are roughly the same size and mapping the data in which values are evenly distributed. Equal interval is useful for presenting information to a nontechnical audience. Equal intervals are easier to interpret since the range for each class is equal, and this is especially true if the data values are in percentages. Lastly, standard deviation is good for seeing which features are above or below an average value.

 

1. Good evening, my name is Nicole Cherry, I’m from Columbus, Ohio, and I am a first-year student studying Environmental Science. Possibly a double major including Geography and a minor in Women and gender studies, but I haven’t fully made any decisions past ENVS as my major. I’mexcited to take GIS since I know it will contribute to my major, but further than that, I don’t know much about it.   
2. Something I found really interesting and helpful to get a better understanding of what GIS is was the comparison between the relationship of GIS and the quantitative revolution, and the relationship between mathematics and calculators. This comparison helped me to understand how GIS is essentially a tool used for spatial analysis to make the process much easier and make advances within the field easier to understand and obtain. GIS takes graphing and geographic information from a solely analytical approach to add a visual approach, which causes people to process said information differently. The legitimacy of GIS decisions and results is frequently not disputed, which was really interesting to me because it also mentions how this can essentially frame someone’s perception of different income communities. With this information, Goodchild argued that in GIScience, it is imperative to still dissect the inherent bias that comes with human production in science. This to me really analyzes how even though Fields of science still contain human biases and need to be evaluated and questioned. I also thought it was interesting that it was noted repeatedly that GIS is incredibly important in many spaces in our lives, and having never heard of GIS before coming to OWU, the knowledge of this program seems so necessary to everyone, yet not as widespread as I would anticipate. Even things that seem basic to me on a surface level, such as farming, are incredibly reliant on GIS. Finally, a part that I thought was really interesting throughout the entire reading is that the relationships between groups, even human geographers and GIS scholars, are explored so intently. I guess finishing the reading this does make a lot of sense since, from what I understand, it is the main basis of GIS in exploring relationships between groups of any kind, from humans to relationships and boundaries between plants. GIS seems to be heavily focused on deciding what those boundaries are and where to put them.

1. (A) Political issues are just an interest of mine, so I thought looking up prominent hate groups would be interesting. This source states how the media has brought attention to hate groups, and GIS is used in areas with high rates of hate crimes of different groups, to have a better understanding of where these hate groups are predominantly located. 

Mapping crime – Hate crimes and hate groups in the USA: A spatial analysis with gridded data – ScienceDirect

3. (B) As a member of the LGBTQIA+ community Political issues surrounding this are very important and impact me, so I just thought it would be interesting to see how GIS is involved in research surrounding these issues. This source used GIS to map LGBTQIA+ uncertainty within this political climate. 

Coloring Outside of the Lines: Sketch Mapping Fear, Safety, and Community for LGBTQ+ Students Amidst Anti-LGBTQ+ Legislation

Chapter 1

GIS, or Geographic Information System, is a process for looking at geographic patterns and features. This works by creating softwares and models to view data in a complex or simple way. To start, you have to decide the question you want to answer which will help in the next steps of determining the approach. Depending on the reasoning behind the question and the purpose of observing the data in this way will determine how complex or simple the visualizations need to be. After reading the first part of this chapter, it has helped me gain a better understanding of why someone needs to use GIS for their jobs. It also helped describe why more data would be needed and that getting more information can be as simple as adding new calculations into the software. Also, I appreciated how it explained the difference between using GIS for a quick study compared to a long, time-consuming one that could be used for a more official purpose. I found it interesting how the chapter mentioned that you want to find a way to represent your data clearly so that the intended viewers would be able to understand the information. I think it was also good to note that this can take many attempts to get to the final product and it is not a simple process. The features you include can be discrete, where the location gets pinpointed; continuous phenomena, where the data blankets the entire area being mapped; or summarized by area, representing data within area boundaries. Geographic features are additionally represented by either vector or raster. With vectors, each feature shape is defined by an x,y location. With raster, features are represented by a matrix of cells in a continuous shape. The representation used depends on what specifically needs to be shown with the data. When combining layers, the same map projection and coordination should be used to show accurate results when comparing relationships between information. This chapter did a great job explaining while also utilizing examples and pictures making it easy to understand. Finally, through using attribute values (categories, ranks, counts, amounts, and ratios) you can combine the numbers into a data set to then be able to use calculations. 

Chapter 2

Deciding what to map with GIS is dependent on the question you are asking. By looking at the location of these features, we can then explore the patterns being shown. To find these patterns, the data should be layered within the map with different symbols. This connects back to the first chapter where it must have the same coordination so the relationship can be easily visualized. The use of the map created also is dependent on the audience. Extra information should be included in the map when the intended audience does not clearly understand the data or location. The chapter explains that when you prepare your data to create the map you should assign geographic coordinates and category values. This step helps ensure that your map will clearly show what information you are trying to inform others on. What I found interesting about this chapter is how customizable the software is. GIS allows you to tell it what features to display and how to symbolize them as well as storing the specific coordinates of your data points. While this concept seems complex, the chapter included photographs to help visualize what it is trying to explain with each type of map. GIS can be mapped in multiple ways, including dots, lines, or others depending on what your data is. For example, the chapter included lines for mapping streets, and points for mapping location of crime. The color can additionally be changed to allow for the overlap described in chapter one that lets the viewers see the relationship between the data. It also included that a rule of thumb is to have no more than seven categories because most people can only distinguish up to seven colors on a map. This is especially an issue when data is displayed in small scattered features. The main example the chapter showed was zoning maps and how much clearer it is to read with less categories. It gave an example of grouping categories in order to create less color difference while also showing the same information. In the zoning map example, it combines heavy industrial, light industrial, and mixed used industrial into one industrial category. The chapter included multiple more examples on how to choose colors, symbols, and lines when creating GIS to help get the point across in an easy viewable way. The clearer that the information is presented, the easier it is to view the patterns. 

Chapter 3

When using GIS, another component to think about is to map both the most and the least. This allows for them to find the places that meet their criteria and see the relationship between locations. Mapping quantities allows for another layer of depth beyond mapping location. To begin this step, the chapter explains that you first must consider what features you are mapping. One part I found interesting was that it explains your map should be created with the purpose in mind. When presenting the map to an audience more components need to be considered compared to if you are looking at the data yourself. Quantities on a map can be counts, amounts, or ratios. Counts and amounts show you the total numbers while ratios show the relationship between two quantities. This chapter also introduces using ranks. Ranks show relative values and can be useful when direct measures are difficult. An example I liked in the chapter was stating what portions of the trail had an excellent or good view compared to portions with fair, poor, or no data. Once the quantities are determined, the next step is dividing them into classes or giving each value its own symbol. Mapping individual values requires a lot more precision, yet can allow you to spot relationships in the raw data. I found it extremely interesting how it explains GIS is able to calculate mean and standard deviation when creating the map. It also explains how deciding classes is not just a simple process and it must consider outliers in data and how you want it to be presented. Additionally, you want to make sure it stays easy to read. This chapter did a great job of explaining the process of creating a map and including options and steps and the advantages and disadvantages of each. It also provided many charts, graphs, and examples similarly to the last two chapters. Towards the end, what I found most interesting was the inclusion of the Z-factor. The Z-factor increases the variation in the surface making the differences much easier to see without exaggerating. You can also include a light source to determine how shadows appear within the surface. What I found most interesting about this was the effect it gave the map and how big of a difference it made in the examples to be easily understood.

Mitchell Chapter 1:

The most important thing I found from the beginning of this chapter was that GIS stands for Geographic Information System. It allows us to see patterns and relations in geographic data, and is used in many jobs. Using GIS is very helpful in understanding more about a specific place, however you still need the right tools and analysis to make that happen. The first step in GIS Analysis is asking a question. It can be any type of question, and then you simply have to understand your data. Then you choose a method, process the data, then examine the results. I found that it seems very similar to the scientific method. 

There are different types of geographic features, such as discrete features, continuous phenomena, and features summarized by area. In discrete features, the specific location can be pointed out and is there or not. Continuous phenomena can be found or measured anywhere, such as precipitation. Interpolation: the process of assigning values to the area in between points. Centroids: center points. Summarized data is the counts of individual features within area boundaries. Demographic data in particular tends to come as summarized data, but you can use GIS analysis in order to overlay the data in which you want. 

Geographic features are represented in two ways: vector and raster. In the vector model, each feature is represented by a row in a table and X,Y points on the map. Specific areas on the map are defined by borders. In the raster model, the features are represented by cells in a continuous space. The cell size does matter because information can be lost, which I think is interesting. Discrete features are often represented by the vector model. There are many types of attribute values, such as Categories, Ranks, Counts, Amounts, and Ratios. These values matter depending on the map type you’re making. The main tasks we will have to perform are Selecting, Calculating, and Summarizing. The equations are represented in Chapter 1. 

Mitchell Chapter 2: 

It is important that people understand that mapping is important, but understanding the patterns in certain types of geographical spaces can be helpful with GIS. It is used by police officers, wildlife biologists, and retail analysts. These jobs all have different uses for GIS, and it helps to have categories on the maps to describe the areas and features. You have to assign geographic coordinates and category values to each map, which I think sounds fun! To start your map, you simply have to tell GIS what you want and where you want things. Maps can be very simple, with features that represent simple patterns. 

One of the main functions that GIS does is it stores the locations of different features as a pair of geographic coordinates or as a set of coordinate pairs that define area. Using these specific coordinates, you can make symbols at each point and connect them (it reminded me of connect the dots)! Using the data layers and subsets, you can ask GIS analysis to specifically point out what kind of data you are looking for. For example, if you are tracking wildlife migration, you can tell it to focus on one particular animal or route. I also think it’s nice that the GIS will store a category value for each feature in the data’s table layer. 

I like how they mentioned that you can only use up to 7 colors, because humans can’t really process more than that, which is fair. It is definitely easier to understand an area with less colors and less features if possible. This can be helped with grouping categories, but we have to keep in mind that some important information can be lost if we combine too many things. The main thing being discussed is simply knowing your data and what categories would make sense together. Choosing symbols is also important! They state that you can use different colors, or shapes, but colors are preferred because they are easier to distinguish. Text labels are also necessary so the audience can see what you see. Overall, it seems pretty easy, but I understand how it could be very picky and difficult to analyze if done improperly. 

Mitchell Chapter 3: 

At first, I was a little confused at why it said to map the most and the least. But, upon reading more, it made sense because you have to associate the data with quantities of each feature. As discussed in Chapter 1, there are different patterns of features needed to map certain data. There can be dots, colors, shapes, and shading on different maps used for different purposes. Data summarized by area typically are displayed by shading charts. I liked how it also defined the differences between exploring the data and simply presenting a map. You have to understand your quantities, counts, ratios, ranks, and amounts. 

One of the next steps in using GIS analysis is to create classes. Counts, amounts, and ratios are typically the data that are grouped into classes. When you map individual values, you can search for patterns within the raw data and also present an accurate picture of the data you are exploring. I think it’s cool that you can group classes together by using the same symbol. The classes also require you to find the upper and lower level, so the class can be used in between those values. You can also use standard classification schemes, which let you look at different patterns in the data using similar values. Some of the subsets of standard classification schemes are natural breaks (jenks), quantiles, equal intervals, and standard deviation. 

Each classification scheme has a specific way of identifying the different patterns and groupings within the data. However, to choose one of these, you have to know how the data values will be distributed across the map or the graph. I found that it seems very similar to choosing the correct graph for your data sets in math classes. It appears that we also deal with outliers, and we put those into their own classes. Once you have all this information, you can make your map, yay! Of course, the map types are different as well, and also depend on what kind of data you have. The symbols, colors, shapes, and general charts will all be different for what you are trying to examine. One hint I found useful was using contour lines for continuous phenomena! In the map, you can also edit viewer location and that will make a difference, as well as the Z-factor and the light source.

Chapter 1:

What is GIS analysis? – Finding patterns in your data based on their geographical locations and finding relationships between features.

Understanding geographical features

Discrete: As any point, the feature is either present or not; an actual location can be pinpointed.

Continuous phenomena: Can be found and measured anywhere.

Summarized by area: Data that applies to a certain defined area, but not any specific point within it.

Representing geographical features

Vector: Each feature is a row on a table, and areas are defined by x, y locations.	Typically discrete and summarized by area are displayed this way. Vector can also be used for continuous.
Raster: Features are represented as a matrix of cells.	Continuous often displayed this way.

Understanding geographical attributes

Categories	Groups of similar things
Ranks	Put features in order, from high to low
Counts	Total number of features on a map
Amounts	Any measurable quantity associated with a feature
Ratios	Relationship between two quantities shown by division of on by another

Chapters 2 & 3:

Chapters 2 and 3 surprised me because they overlap heavily with statistics, expected, and art, unexpected. While I was aware that visual qualities would come into this because GIS can make maps, I didn’t expect so much, so early just about aesthetically and intuitively displaying data. The chapters explain how to make it most clear and obvious what your data means to your audience, even talking about how you might display differently for different groups depending on priority and familiarity, and these explanations make it clear how maps can be used to confuse viewers as well. During elections, I often see voter maps where most of the individual blocks are red but it is still a blue state; these maps are used by people wondering how that could be because the map doesn’t show the number of people in each block, leading to a perceived over-importance of large areas with small amounts of people.

Displaying too many categories at once can make a map difficult to use and understand because there is too much information being presented, but too few categories leads to an oversimplification of data that doesn’t give the full picture. The GIS user must decide on a case-by-case basis what on appropriate way to display the information is.

1. Introduction

Hello, my name is Kathleen, and I am from Dallas, Texas. I am a junior majoring in astrophysics with a minor in environmental science. I plan to work in meteorology or compact objects research. I am taking this course because GIS is one of the most important tools for tracking and predicting severe weather.

2. Reading

This reading surprised me but also taught me a lot about how GIS and how it is viewed and used by various groups of people. I don’t have any experience with GIS and I originally thought it was only used by environmental researchers, but this chapter taught me that it is used in so much more. On just page 1, I learned that even Starbucks uses GIS to find successful shop locations. GIS also has different “definitions” to different sections of the science community. In the chapter, Schuurman offers the examples of city planners who see GIS as a tool to see how residents are affected by possible infrastructure changes, while researchers see it as a way to define boundaries of changing phenomena. I found it very interesting that Canada, the US, and the UK all worked on computer cartography data together to shape what we know today. It is astounding that it would have been developed much later if Tomlinson and Pratt hadn’t sat next to each other on the airplane. The chapter states that GIS would have been inevitably created, if not by geographers, as its creation was supported by many other disciplines in the era of a world increasingly relying on digitalization of data. It is very cool that GIS has given researchers an accessible way to make conclusions through visual data. While Schuurman makes the point that some see it as “unscientific”, I believe that visuals are the best evidence to draw conclusions. This chapter also introduced the “behind-the-scenes” of GIS with GIScience and GISystems. GIScience looks at how the GISystems are used and GISystems looks at what data is needed and how it will be analyzed and coded. The end of the chapter provides us with a multitude of examples of how exactly GIS is woven into our lives. It is surprising how every little detail of our lives, down to what flyers we get in the mail, is influenced by GIS.

3A. GIS Application #1

I am an astrophysics major so I researched how GIS is used in astronomy. The most common use is selecting a site for radio astronomy. This source describes how GIS was used to determine the site for radio astronomy testing in Portugal. They determined that Herdade da Contenda was the location with the lowest risk factor of fire, flooding, impact on flora and fauna, and many other factors.

Source: https://www.mdpi.com/165092

3B. GIS Application #2

I travel to Colorado yearly to hike in the mountains, so the forest fires have had a high impact on our ability to go. This research used GIS to identify areas with a higher fire risk and to determine the factors that influence the intensity of wildfires.

Source: https://doi.org/10.1016/j.rsase.2022.100872

4. Quiz

I have completed the quiz.

 

My name is Claire Evans, and I am a second year Environmental Science and Art History student. 

Something within the chapter that caught my eye is the idea of data within GIS being biased due to human biases and choices that must be made to convert data into something  usable within GIS. Uncertain data being difficult to represent and share is true regardless of what a person is using, visual or verbal, GIS or physical papers. The chapter mentioning that GIS can’t work well with uncertain data is then interesting in that it is not a fault only of GISystems. Because it doesn’t have a large impact on how the systems are used, the inclusion of the arguments pertaining to the origins of GIS in an introduction chapter to the systems surprised me. I’m currently taking Urban Geography, and the point made about how a neighborhood looks on a map and how a route may not actually be the most effective based on the data given being incomplete or in favor of a certain area reminded me of the idea that a city looks very different from a map view to a street level view. Dr. John Snow having both mapped out the cases of cholera, but also having to get extra information via speaking to people who lived in the area in order to figure out what wells were causing the cholera outbreaks reminds me of this as well. It’s also similar to looking at a piece of art in a setting other than where it was intended to be; you lose context and surrounding features, such as lighting and sound, when looking at a piece in a museum rather than where it is from, just as you lose some information when looking at a map of data rather than being in the area and community that you are examining.

MSF (Doctors Without Borders) uses MSF to create maps of common needs in communities they are stationed in, and they use a simple form of GIS through MissingMaps to make maps of constantly changing refugee camps that volunteers can help create. 

This study used GIS to examine the number, size, and make-up of Buddhist organizations in the 4 corner states. They examined factors such as race, age, and political leaning to see if there was a potential correlation between these things and the practice of Buddhism in the 4 corner states.

Introduction: My name is Ava Johnson and I am a senior! My major is East Asian studies and I have recently come back to the U.S. after being in Japan for the second time since I have been in college (once to study abroad, and the most recent time for a TPG). I actually took GIS 292 in the fall of 2024, but I truly do not remember most of the things that I learned since it’s been a year and a half. I am excited however to get back into the swing of things for my last semester here at OWU!

Chapter 1: As someone who has mistakenly already taken GIS 292, this chapter was a very nice refresher to be able to go over the ropes again as it has been nearly 2 years since I have done anything remotely related to GIS. Nadine Schuurman introduces Geographic Information Systems, or GIS, by showcasing the many ways that GIS has been used, and can be used in order to peak a person’s interests. In other words, explaining there is no singular way to utilize GIS, and uses examples of college students, epidemiologists, and even corporations like Starbucks utilizing it all in different ways. She argues that GIS can be understood simultaneously as a tool, a science, and a socially embedded practice, and that debates over its identity reveal deeper tensions about knowledge, power, and representation. I appreciated how Schuurman explained GIS first as a technical system designed to capture, store, analyze, and visualize spatial data to then lead to how it has transformed over time.  This instrumental view highlights GIS as software and hardware used for mapping and spatial analysis. However, she also makes note to mention that there are in fact many limitations of this definition, noting that it ignores the theoretical assumptions built into GIS models, such as the simplification of complex social realities into discrete data layers. I also really appreciated how Schuurman introduced critical perspectives that view GIS as socially constructed and politically charged, not solely biased towards positive outcomes of utilizing GIS. This section really takes a step back from the exciting possibilities that come with using GIS to showcase realistic concerns and how these thoughts can oftentimes challenge the assumption that GIS is neutral or objective. With that being said, Schuurman’s chapter encourages readers to see GIS as more than a technical tool. This chapter shows us as readers, and relatively new or unfamiliar with the tool, how GIS shapes knowledge, whose interests it can peak, and how it might be used depending on what a user needs it for.

 

Application 1:Since I studied abroad in Japan, I thought it would be cool to find something related, and I did! I found this application of the different borders of Japan, specifically different prefectures. Along with this, specific kinds of data such as area in square kilometers, as well as population rates were also on the map once a specific prefecture was selected.

Source: Michael Bauer Research GmbH   

 

Application 2: Similar to the first application, I searched up “recent earthquakes near Japan”, and an application came up with different hotspots, deaths, injuries, and overall popular locations.

Source: Maria da Conceição Neves