Geography 291: Geospatial Analysis with Desktop GIS

Chapter 1: Chapter one is a basic overview of the various ways to sort, analyze, and display information in GIS software. It covered the process of selecting and understanding your data, as well as all the ways to manipulate and display said data. I found the different “types of features” particularly interesting because they made intuitive sense to me and it was cool to see the different ways various types of data can be displayed. I was already vaguely familiar with the concept of vector and raster images, having used a number of different digital art programs, but it was interesting to see how that difference was represented in the much more analytical GIS software. I understand the concepts behind the various types of Geographic attributes, but I don’t fully comprehend all the ways in which these can be combined to produce different results. Presumably understanding will come with practice and experience, and I look forward to that. I worry that I will not remember all the different ways data tables can be used, as there are quite a few specific functions listed in the chapter. I understand the theory behind each of the various operations but I am sure that I will not remember them well enough to apply them to GIS without further study.

Chapter 2: Chapter two is about the process of mapping itself. It covers the basics of how to prepare the data and create the map, as well as various tips and strategies you can use to make your maps easier to understand. The chapter discussed the various uses of highly detailed maps vs more general ones. The chapter explained how unnecessarily over-detailed maps can in fact reduce clarity and make the map harder to understand, so in situations where granularity is not needed, it is best avoided. The explanation Geographic coordinates and how GIS uses them was clear and understandable, as well as the demonstration of using various types and categories to display different related types of information. What I most appreciated about this chapter was the advice it gave on how to create good maps. Advice about how detailed and granular to make the map, how many categories to include, how large of an area to cover etc. was all very helpful and interesting to learn about.

Chapter 3: I was initially confused about the concept of “the most and least” but the book did an excellent job of explaining it. The term itself was kind of confusing but I understand it now as simply including quantity in the analysis process, which makes a lot of sense and I can think of many ways that might be helpful. Additionally its use in summarizing data to be more easily understandable at a glance is also very helpful in the creation of usable maps. The various uses for counts, amounts, and ratios are now also clearer to me, as is the use of classes to simplify maps into more easily understandable divisions. Yet again it comes down to a question of granularity. In some cases, individual values may be necessary to provide detailed information for precise areas, but for other situations like public discussion or presentation, that kind of granularity is unhelpful and confusing. The standard classification schemes and their various uses are also a very helpful tool to know about. The section about choosing a classification scheme is particularly helpful in this regard and likely something I will refer back to many times during the course.

Going into the first chapter of Mitchell, I knew very little about GIS. However, by reading this chapter of the book, I became a lot more familiar with the concept. Chapter 1 was able to help me get a better understanding of what GIS is as a whole and also the breakdown of the software. One thing that I learned is that GIS has many different tasks and things that you are able to use it for. Before reading, I knew that there was a wide use of GIS. However, on page 13 of Mitchell, the book states a list of what GIS is most commonly used for. The list goes, in no particular order, “mapping where things are, mapping the most and least, mapping density, finding what’s inside, finding what’s nearby, mapping change.” This list is helpful to me because it gives me a more narrow idea of what GIS is used for instead of the “wide use” mindset that I previously had. Furthermore, the most interesting thing I learned is that in GIS there are different operations that you are able to perform on data tables. These caught my attention because they are different, useful tools that I did not know that GIS was able to do. The first operation is selecting; you are able to assign a value to a feature. The second operation is calculation; you can calculate attributes’ values in order to give new values to the features. The third operation is summarizing; you are able to get different statistics for specific attributes. I think that it is really interesting when you are able to find shortcuts or codes in different software in order to use it more efficiently. I believe that later on in my GIS learning and use, these operations will become very useful. 

 

The second chapter of Mitchell is all about mapping. Mapping is important because when you map things, you are able to look and see where you could potentially need to take action or what areas are able to meet your criteria. One fun thing I learned about mapping from Chapter 2 is that it is typically helpful to add different categories to your map. Categories split up features into different subtypes and aid the readability and fluidity of a map. Without categories, it might be hard to determine certain uses for your map and it may be difficult to read under certain contexts. Mitchell states that “mapping features by category can provide an understanding of how a place functions.” Mitchell then gives the example of how using a black line for road types only shows where the roads are, but if you categorize them into types of roads, the hierarchy of the roads would be visible along with regional traffic patterns. This shows that categories are extremely helpful when creating a map. In this example, adding categories gave the map a new function and made it easier to read. However, adding categories can be tricky to do properly. Mitchell says that there should never be more than 7 categories because the more categories you use, the more difficult reading your map will be. A few factors play into the 7 category rule: scale of features and map scale relative to features. One thing to keep in mind is that the scale of the features on a map can greatly influence the number of categories used. If the features on a map are small, it will be difficult to distinguish which categories are which if there are too many used. Also, if the map scale is large in scale to the features, the more categories used, the more difficult the categories are to see.

 

I found the third chapter of Mitchell particularly interesting because it was all about creating a map. I liked how this chapter was set up compared to the other chapters. This chapter was formatted by walking the reader through creating a map by telling them what questions to ask themselves in the process. These questions were the headings for each section, and the section would walk the reader through what to consider in order to answer the questions properly. My favorite section of this question system was about classes. Classes allow the person mapping to group together different values into classes, and they are typically utilized when the map will be presented for discussion instead of for individual analysis. I think the concept of classes is cool because they let the mapper create groups of data and then assign the different groups a symbol. Another thing I thought was interesting about classes is that they can be made manually or by the GIS program. Mitchell states that creating classes manually is usually used when the person creating the map is looking “for features that meet specific criteria or comparing features to a specific, meaningful value.” When creating classes using GIS software, the person mapping will use a standard classification scheme. Mitchell states that the person mapping will want to use a standard classification scheme when they “want to group similar values to look for patterns in the data. You can choose from several schemes.” I found standard classification schemes particularly interesting because there are multiple different ones that are available. There are natural breaks, quantile, equal interval, and standard deviation. In my opinion, Mitchell did a really good job breaking down the different types of classification schemes by stating how each one works, what it is good to use it for, and the disadvantages of using it. 

Mitchell Chapter 1-

I found this reading much easier to understand than the previous week’s reading. Its format, how it breaks down the information, makes me feel more confident about the information presented. I especially appreciated the step by step guide on the process of GIS analysis- frame the question, understand your data, choose a method, process the data, and look at the results. I learn best when steps are clearly laid out for me to re-write to help memorize them. Also, geographic features are broken down into discrete- pinpointed locations, continuous phenomena- values assigned between points or enclosed boundaries, and summarized by area- a data value applied to an entire area instead of any specific location within it (ex. demographics). You also represent geographic features in GIS through either a vector- features are rows on a data table, or raster model- features are a matrix of cells in continuous space. There are subsections of the geographic features I previously mentioned, which are called geographic attribute values. The types of attributes are categories- groups of similar things represented using numeric codes or text, ranks-which put features in order from high to low based on feature attributes, counts and amounts- which shows the actual number of features on a map or any measurable quantity associated with some feature, ratios- show the relationship between two quantities, created by dividing one quantity by another for each feature, and common ratios are proportions and densities, continuous (not including categories and rank attributes) and noncontinuous values- which is a way to know how the values are distributed to help group them. The last part of the chapter shows how to use the data tables in the GIS software with a step by step process. The common operations you use in data tables are selecting- choosing features to work with a subset of them or assign a new attributed value to those features, calculating- to assign new values to features in a data table, and summarizing- to summarize the values for specific attributes to produce statistics.

Chapter 2-

This chapter focuses on mapping where things are and beginning to understand why things are the way they are. The first subsection is “why map where things are” describes the benefits of looking at a distribution of features on a map, which help you more easily identify patterns, in comparison to looking at just individual features. Mapping where things are can show you where on a map you need to take action, or the specific areas that meet your criteria, and explore causes for the patterns you see. The next subsection, “deciding what to map” states that in order to look for patterns in your data you need to map the features in a layer using different types of symbols. What information you need from your analysis will help you display the features, like where they are and are not, map the location of different types of features and if certain types occur in the same place. You should use the map based on your intended audience for the issue you’re addressing. The next subsection is “preparing your data,” which is making sure your features have geographic coordinates assigned to them- either using the databases or mapping it by hand, and that your features have assigned category values- a code that identifies its type, and can be divided into subtypes as well. “Making your map” is the next subsection, which describes the features you tell the software that you want to display, the symbols to use to draw them, and that you can map all your features in a layer as one type or show them by their categorical values. It also describes what the GIS does for each way to map features. This subsection is very in depth and I will most likely refer to it fairly often. The last subsection is “analyzing geographic patterns,” and describes multiple ways features in a category can be presented as, such as a clustered, uniform, or random distribution, for example. Patterns can be the result of multiple factors, and any patterns that you can’t see just by looking usually need statistics to measure and quantify the relationship. 

Chapter 3-

This chapter describes what mapping the most and the least entails, how to do it, and its benefits. The first subsection, “why map the most and the least,” explains that people map where the most and the least are to see the relationships between places or to find places that meet their criteria, by mapping features based on a quantity associated with each. “What do you need to map” is the chapter’s next subsection, describing what you need to do to decide how to best present the quantities to see the map’s patterns. You can map quantities associated with the geographic features listed in chapter one, and make sure to remember the purpose of your map and its intended audience when deciding how to present your information. The next subsection, “understanding quantities,” describes how you need to assign symbols to features based on an attribute that contains a quantity- amount, ratio, or rank. Counts and amounts show total numbers and allow you to see the value of each feature and its magnitude compared with others, ratios show the relationship between 2 quantities and can even out differences between small and large areas, or areas with many or few features, so the map more accurately shows the features’ distribution, and ranks put features in order from high to low and care useful when direct measurements are difficult or if a listed quantity represents a combination of features. “Creating classes” helps you decide two to represent your quantities on a map, either by assigning each value its own symbol or grouping values into classes, typically based on which feature you choose to map your data. The 4 most common classification schemes, natural breaks, quantile, equal interval, and standard deviation are also explained and compared to each other in depth. “Making a map” is the next subsection, and describes the options GIS has for creating maps to show quantities- graduated symbols, graduated colors, charts, contours, and 3D perspective values, along with creating the view, z-factor, light source, and perspective view very in depth. “Looking for patterns” tells you to either look at the transition between the least and most are, whether values cluster or not, to see how the phenomena behaves.

Chapter 1: I think it’s interesting how GIS has become more accessible over time with an increase in social media and tech use. Before coming into college as an ENVS major, I had honestly never even heard of GIS as a field. I like how this book begins with the basics of GIS and explains what it is and how to use it before getting into more of the actual map-building concepts. I think building up a base level of knowledge on GIS will come in handy later when we are presented with more complex topics. I also think it’s interesting how the book explains there are various ways to display the same data. Some methods are just more in-depth and are useful for certain scenarios whereas other methods may be more useful for quick looks at patterns. The explanation of the difference between discrete and continuous data was helpful, and I had not realized there was a distinction between these two kinds of data, but when the book presents the pictures, it makes sense that they are two different things. It is also very helpful that the book includes pictures next to the concepts being introduced so that once we begin map building, we can visually recognize these terms. Interestingly, single-point locations like businesses look very similar as both a vector and raster, but lines on a map, like highways, look much different as a vector compared to a raster. Areas appear to have the most loss of detail when expressed as a raster compared to a vector. The portion of the book explaining the various attribute values was slightly confusing at first because each type seems like they have similar functions (or at least the words all seem similar to me). However, once I went back through and read it a couple more times and studied the maps closer, it began to make more sense. I also suspect that once we begin making our own maps this will be a little more intuitive in practice. 

Chapter 2: The first second chapter begins by explaining that you can either map things to identify individual features or to look for patterns in the distribution, though it’s interesting how when looking at the two different maps, they are actually the exact same. I also think it’s very cool that by identifying patterns on a map, a range of different professions from police officers to biologists can determine plans of action based on the data. It is slightly unfortunate that smaller maps cannot show as much information as large maps so they don’t become overcrowded, because sometimes maps may need to be in a small format. However, if there is too much information on the map to be able to read or identify anything, it would defeat the purpose of it entirely. I like how the book explains what the user does to input data for a map versus what GIS does when making the map. When I use R in my biology classes, we also use subsets a lot to uncover hidden patterns. Usually, we’re working with a very large dataset and it’s a lot easier to understand the data with subsets, and I like how that also translates to maps! Like the last chapter, I think a lot of information is being presented here and it’s a little confusing/overwhelming now, but in a couple of weeks when we begin implementing all of these terms, it will all come together. One interesting thing I did not know that this chapter said was that people can typically only distinguish up to 7 factors on a map, which does make sense. I think that it’s helpful that the book includes directions on what not to do- basically things that may make a map look confusing or hard to see data points. This part will be good to look back on when we make maps. It also brings up ways to make maps with lots of data less confusing, such as using text labels. I like that this chapter introduces ways to analyze the data. I think it will be important to discover the trends in the data being mapped and not just simply to make a map to look at for no reason. 

Chapter 3: This chapter seemed slightly daunting at first because of its length, but luckily it was a lot of tables and pictures! I feel like the beginning of this chapter was slightly repetitive, as it introduced some of these concepts earlier. However, it’s nice that they go more in-depth with each of the ideas and show more examples of maps demonstrating certain concepts. I think I’m slightly confused about classes and the four different schemes, but as I’ve been saying I’m sure it will make more sense in practice and I can come back and look at this part of the book for reference. I do like how the chapter compares the different classification schemes by listing the pros and cons for each and also giving a general explanation of how they work. I think displaying concepts like this in a textbook really helps me understand the material. I think this chapter will be extremely helpful to look back on later when choosing a map type. The 3D perspective maps are really interesting and I didn’t realize that GIS was capable of doing this! I don’t have as much analysis or reflection on this chapter since it was mainly maps, but again I think showing the maps is obviously a very good way of introducing ideas and comparing different terms. 

Chapter 1- 

The first chapter starts out by saying that more and more people are starting to use this software and spatial analysis. GIS analysis is a certain process that looks at geographic patterns and finds relationships between features. It’s important to ask good questions in order to understand and collect the right set of data. Posing the original questions correctly is the key to correct GIS analysis. Selecting the correct method is also important. There are two different models that GIS can be used with: vector and raster. In my opinion, the raster model is easier to see, but the vector model gives more data for the area. It’s important to mention that maps usually distort what they are portraying. With small areas and towns, the distortion is barely noticeable. Data tables are also very crucial with the use of GIS. Three common methods used with data tables are selecting, calculating, and summarizing. Selecting is just selecting the features you will be working with. Calculating is measuring the data and putting it into certain areas for reference. Summarizing is combining all the data and looking it over. 

Overall, I liked this chapter because it gave a simple intro to GIS and why it’s commonly used. I learned about different features: discrete, continuous phenomena, and summarized. All three of these show different types of information collected. 

I also learned that there are five different ways to describe a feature. The easiest one for me to see is ratios. This attribute value shows the relationship between two quantities.  A commonly used ration is population (density) and proportions. It’s also very easy to see the data collected using ratios because everything is color coordinated and in separate boxes and lines. 

Chapter 2- 

It’s very crucial for us to be able to map where things are so we can navigate, communicate, and educate ourselves about a certain area. Police use maps to be able to look and see where the most amount of crimes are. In those areas, more police officers can be dispatched to help keep the neighborhood safe. Deciding which map to use is also difficult because it needs to portray the information correctly and match the needs of the viewers. A good point the book makes is about an audience that is unfamiliar with the area. If viewers don’t know what kind of map they are looking at, it might cause some confusion or just straight bewilderment. Landmarks or certain roads or boundaries might relieve some of this confusion. Different colors (green for forests, or yellow for cities) might also be a solution. 

This chapter went into more detail about how GIS works in relation to our everyday lives. I liked looking at all of the photos because they gave examples of the different types of maps that can be created by using GIS. A lot of the map examples in this chapter show streets, neighborhoods, and crime rates. The maps about neighborhood location with family size and industry really shows how cities are broken up, and where people tend to live. Office buildings and industries are downtown, with housing being more in the suburb areas. 

Chapter 3: 

I’ve never really thought about this before, but maps are usually mapping most and least data. This is quantity data. Mapping lets people see where the most and least things are, for example, businesses. Discrete features are a good way to determine simple most and least data. How thick the line is or how big the circle is determines how many of something there are in a certain area. Always keeping the purpose of the map in the back of your head is an important way to determine what needs to happen to the data collected. In other terms, is it about the data or presenting a map? 

When constructing a map, patterns are good to look at. Patterns represent different features on a map, such as land use or vegetation. Patterns also aid in visual representation on different areas on the map. This chapter was focusing on how to turn the raw data into a pleasing map for viewers and other scientists. The map needs to be scientifically accurate but also simple to understand. Having a key to explain what the data is, is also a critical part because without a key, then people have no idea what the map is talking about. 

 

Introduction:

• Hello! My name is Liberty Brock, and I am a senior here at OWU. I am double majoring in Botany and Environmental Science. I’m from a small, rural town in the foothills of Appalachia Ohio. I have always loved being outdoors so that is where a lot of my passion for nature comes from as well as my motivation behind my majors. My hobbies include hiking, reading, anything artsy/crafty, running, and spending quality time with my friends. 
• 

Schuurman Reading: Chapter 1

• After reading the first chapter of this book, I feel more confident with taking this class. I have little to no knowledge or past experience in GIS and I’ve honestly had a little bit of a love hate relationship with the thought of GIS. Before reading this chapter, I didn’t really understand the basics of GIS and I think that’s kind of what has turned me away from wanting to take one of these courses. Now, I understand the versatility and importance of this system and how it can even improve the overall well being/quality of life. Even though this system is more complex than it’s face value of being a mapping system, I think that almost makes it easier to comprehend. From my interpretation, it seems as though the GIS system is comprised of algorithms and stages rather than being a whole system functioning at a base level. There are a multitude of different pieces that allow the whole system to function as one similarly to how a puzzle works. Each piece of the puzzle doesn’t really represent the entire image of the puzzle when looking at the pieces alone, but those pieces interconnected together create this … I really enjoyed learning about the different functions of GIS and that they extend beyond fields in Environmental Science and Geography. Before reading this, I didn’t realize that GIS was prevalent in social work issues as well such property definitions, tax assessment information, and etc. Additionally, I really enjoyed learning about the history of GIS and how the roots of GIS trace all the way back to 1962 from a landscape architect, Ian McHarg, who created the concept of overlay.

GIS Application

• I’m really interested in how GIS could be used to map invasive species in an area. Using google, I searched for “GIS mapping applications” and “invasive plant species” to see how GIS is being used to track the movement of invasive species. It seems like there is limited information over this topic though, which makes sense because I can imagine that this is difficult to track. https://www.stanleyparkinvasiveplants.com/SPinvasivePlantMapping.pdf
• GIS image
• I’m also interested in how GIS is used to optimize agricultural production.  Using google, I searched for “GIS mapping applications” and “agriculture” to see how GIS is improving crop outputs. https://smallfarms.cornell.edu/2017/04/use-of-gis/

Hi, my name is Ethan Shaw and I am majoring in Economics with a minor in Accounting from Woodland Park, New Jersey. I am hoping to find a job in finance or consulting after I graduate this May. I have never used ArcGIS or any GIS software, this class seemed interesting to take. 

 

I never realized how much GIS is used outside of the environmental field of work. I was interested in taking this class because in the professional world especially in economics when looking at developing nations or areas in the US. I did not know there was a difference between mapping and spatial analysis and that there were different variations of mapping in GIS. I also never knew that GIS was a technology that has been around for over 50 years and always thought of it as a new technology that was just being discovered, it is also amazing to me that GIS started without using a computer and just handwriting code out. GIS is now being used in many different industries. I was completely unaware of just how much GIS is used in our day to day lives and what decisions are made by it.  GIS is used in many municipalities when determining crime rates and how these are affecting the areas. These maps are also able to tell you why areas see more crime than others and why there might be a spike in a certain crime. GIS is also used in many large companies to help with growth within the company. Large fast food companies use GIS to determine based on all sorts of factors where the best place would be for their restaurants or stores. 

 

The map below is of the crime rates in Essex county NJ. Mapping this out allows officials and people to know generally what areas are seeing more problems than others and what type of crimes are prevalent in these areas.

This map shows the urbanization of Teton county Wyoming. This is showing like most sought after vacation spots in the US how masses of people moving in are slowly taking over and leaving these places almost unrecognizable.

1. Introduction: Hi, my name’s Haley Roberts and I’m a first-year environmental science major. I’m from Bowling Green, Ohio, which is just under 2 hours North of here. In my free time I enjoy drawing, reading, camping, and rollerskating. I don’t really know much about using ArcGIS, but it seems like a valuable skill to have in an environmental science profession, so I’m excited to learn more about it.

2. Schuurman: The first thing that stood out to me in the reading was how widespread the use of GIS is. It definitely made me rethink what I thought I knew about GIS- I wouldn’t have even considered it as something that could be applied to police training or organ donation. I think it’s really interesting how the concept of GIS was initially expressed with layered tracing paper in the ’60s. Even though this makes sense, I always associated GIS as a very modern concept used on computers with special software, so hearing that GIS dates back about 60 years was shocking. Reading about the overall timeline and evolution of GIS was also fascinating. Comparing the image in the reading of one of the first computerized GIS images to what modern technology is capable of makes me in awe of the long strides that we’ve come in technological advancement. I liked how the reading compared GIS’s impact on the quantitative revolution to the calculator’s impact on mathematics. This seems to emphasize how much more we are capable of now that we have technology that can do tasks nearly instantaneously when they used to take weeks to years. The fact that GIS is known for its ability to provide a very visual demonstration of data is neat, especially as someone who is a very visual learner like myself. After the reading I can understand just how much GIS impacts people even outside the academic communities that use it the most frequently (ex. farming and consuming farmed goods, taxes, and other uses of GIS apply to the general public). The reading also helped me realize that I’ve used GIS concepts before in other classes like CNX100 or even for personal research, I just didn’t recognize it for what it was at the time.

3. Applications: One of the applications of GIS that I kept seeing was to use it for natural disaster management. One of the examples of this that I found the most intriguing was using it to map power outages caused by hurricanes. Especially in a time where storms are, on average, steadily increasing in intensity, using GIS to brace for power outages and recognize which areas as the most frequently impacted seems like it could of great importance.

https://appliedsciences.nasa.gov/our-impact/story/evolving-gis-technologies-advance-disaster-management

Another application of GIS would be to map the movement patterns of certain animals. This article chooses to look at a species of frog in California, but despite being an older article I think a lot of the methods could still be applicable today. I could see using GIS in a similar manner to monitor the movement of endangered species or to observe whether or not a factor such as a wildfire, deforestation, or global warming impacted a species’ movement patterns.

https://scholarworks.calstate.edu/downloads/xs55mf25c

Hello, my name is Evan Miller. I am a senior, and my major is Zoology. I run both cross country and track and field here at OWU. I also have a passion for birds, as I want to pursue conservation work in the field of ornithology down the road.

Honestly, I never heard of GIS until a friend of my recommended the class to me. Knowing that I enjoy looking at certain maps, I am shocked about the importance and the magnitude that GIS is used, as many major companies and city planners use GIS. When I first heard of what GIS is about, I thought it was a fancy form of mapping. However, it turns out that mapping and spatial analysis are two completely different ideas. As mapping shows physical geographical features present, spatial analysis uses other data to make comparisons with the already known geographical features, which is uniquely interesting. I also had the initial thought of GIS being relatively new, due to more recent computer advances and the fact that I have never heard of GIS until recently. However, GIS has been around in the 1960s, even around the time when computers were considered a new innovation at the time. Going along with the history of GIS, the overall idea seems more complicated and controversial than I initially imagined.  For instance, it seems that some view GIS as solely a quantitative tool, while others view it just as a mapping tool. Although that I currently have not used GIS, it seems that GIS uses both quantitative and mapping mechanisms to help whatever the researcher is looking for. Also, I really did not know there were differences between GIScience and systems, even though there are some distinct difference between the two.  Overall, I really did not understand how much GIS is used and how widely important it is in out everyday society. For instance, GIS plays a significant role in helping agricultural yield, as it helps to provide visual data over certain fields. The fact that GIS is used in a wide variety of ways has made me more curious on how it works and how to use it.

Since I have interest in bird conservation, many bird populations have been undergoing a severe decline in their population sizes over the years. One of the ways to help understand and monitor their populations is through analyzing certain species’ migration patterns. Some researchers have used GIS to help determine more optimal sites to help collect migratory data.

https://www.esri.com/about/newsroom/arcuser/bird-migration/

Going along with conservation work, GIS can be used to help determine where to prioritize conservation for certain species. For instance, GIS can map where the specific type of habitat a particular species likes to reside in, which can help conservationist where to prioritize the protection of their suitable land.

https://www.birdconservancy.org/big-data-for-bird-conservation

Hey there! I’m Fahad, a Computer Science and Data Analytics major. I am from Lahore, Pakistan.

It’s fascinating to see that geographers have mixed feelings about GIS, and I’m starting to get why after this intro. The impact of GIS on our modern world is huge, and being new to this field, I’m excited about how widely it can be applied. I’m still wrapping my head around the difference between spatial analysis and mapping, but it seems like there’s a lot of potential for pulling out different kinds of information. The whole concept of “black boxes” got me thinking – there are so many things in our lives that work in mysterious ways, and we just accept them without really understanding how they do what they do.

Diving into GIS applications, one area that caught my attention is the analysis of crime rates in the U.S. GIS enables the visualization and interpretation of crime data, offering valuable insights for law enforcement and policymakers. It goes beyond traditional statistical reports, providing a spatial perspective that can aid in identifying patterns, hotspots, and trends. I found a compelling map that illustrates crime rates in major U.S. cities, shedding light on the geographical distribution of criminal activities.

https://hub.arcgis.com/maps/esri::crime-in-the-united-states/explore?location=35.278608%2C-94.433020%2C3.90

Another pressing issue that GIS can address is the analysis of mass shootings in the U.S. By mapping the locations, frequency, and other relevant factors, GIS plays a crucial role in understanding the spatial dynamics of these tragic events. Such analyses can contribute to developing strategies for prevention and response. A map depicting the occurrence of mass shootings across different states serves as a stark reminder of the need for comprehensive solutions.

https://www.arcgis.com/apps/dashboards/1e728cb3660f473fb4d00db8709d4f96