Category: Course Student Work

The ESRI Guide to GIS Analysis, vol. 1  (second edition, 2020) by Andy Mitchell

Chapter 4

Density maps show where the highest concentration of features is and are particularly useful when looking for patterns in areas that vary in size, such as census tracts and counties. Before creating a map, the kind of data being used and whether the density of features or feature values will be mapped should be considered. Density can either be mapped graphically (calculating density values for each area or dot mapping) or by density surface. If the data have already been summarized by area or the objective of the map is to compare administrative or natural areas with defined borders, density should be mapped by defined area. If the objective of the map is to see the concentration of point or line features, a density surface should be created. When mapping density for defined areas, calculating a density value for each area involves dividing the total number of features/total value of the features by the area of each polygon while creating a dot density map involves specifying how many features each dot represents and how big the dots are. Density surfaces, however, are created in GIS using raster layers. The specified cell size, search radius, calculation method, and units affect how the GIS calculates the density surface and, ultimately, what the patterns will look like. Density surfaces can either be displayed using graduated colors (usually displayed using shades of a single color with common classification schemes including natural breaks, quantile, equal interval, or standard deviation) or contours (connecting points of equal density). While the patterns on a density map are partially dependent on how the density surface was created, it is important to remember that there may not actually be any features where the highest density is. To see a better picture of what is going in a place, the locations of features from which the density surface was calculated should also be mapped with the density surface or on a separate map.

Chapter 5

Mapping what is inside an area allows for the monitoring of what is occurring inside it or the comparison of several areas based on what is inside each. Depending on the number of areas, what type of features are inside the areas (discrete or continuous), and the information needed from the analysis (list, count, or summary), an area boundary can be drawn on top of the features, the features inside can be selected using a area boundary, or the area boundary and features can be combined to create summary data in order to find what’s inside. A map that shows the boundary of the area and the features is good for seeing whether one or a few features are inside or outside a single area. This method requires a dataset containing the boundary of the area or areas and a dataset containing the features. Creating a map by selecting the features inside an area is good for getting a list or summary of features inside a single area or group of areas being treated as one. A dataset containing the areas and a dataset with the features are needed for this method which involves specifying the area and the layer containing the features so that the GIS may select a subset of the features inside the area. To overlay the areas and features, the GIS either combines the area and the features to create a new layer with the attributes of both or compares the two layers to calculate summary statistics for each. Overlaying the areas and features is good for finding the features that are in each of several areas or finding out how much of something is in one or more areas. Data containing the areas and a dataset with the features are needed for this method. When selecting features inside an area, GIS can be used to create a report of the selected features (count, frequency, sum, average, median, standard deviation). There are also key differences between overlaying areas with discrete features, continuous categories or classes, and continuous values.

Chapter 6

What is occurring within a set distance or traveling range of a feature is understood through finding what is nearby. There are also three methods to find what is nearby: measuring straight-line distance, measuring distance or cost over a network, or measuring cost over a surface. Selecting a method entails determining the information needed from the analysis (list, count, or summary) and defining and measuring “near” which can be based on a set distance or on travel to or from a feature. Using straight-line distance means specifying the source feature and the distance before the GIS finds the area or surrounding features within the distance. This method is good for creating a boundary or selecting features at a set distance around the source. A layer containing the source feature and a layer containing the surrounding features are required to find what is nearby using straight-line distance. Using the area covered by segments of the network  within the distance or cost to find the surrounding features near each source is known as measuring distance or cost over a network. If the objective is to find what is within a travel distance or cost of a location using the locations of the source features, a network layer, and a layer containing the surrounding features, this is a suitable method. Measuring cost over a surface begins by specifying 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 approach is good for calculating overland travel cost and it requires a layer containing the source features and a raster layer representing the cost surface. When calculating cost over a geographic surface, it is important to acknowledge that cost refers not only to monetary value but also to factors like time, effort, or resource expenditure required to traverse a landscape.

Chapter 4 centers around the concept of density and mapping it. Mapping density makes it easier to understand which areas are the most concentrated in some type of resource or landmark, for example in the book it references small businesses. Instead of simply plotting each location on a map where they could become overlapped and difficult to understand, you map with darker colors in areas of high density and include a key so that density can be better visualized. Mapping density rather than simply the location of features on a map gives you a measure of their density per area. Density can be mapped using a graph, a dot map, or calculating density for each designated area. Creating a density surface in GIS is usually preferable but it requires the most data input and more individual data on locations rather than data separated by region or county lines. GIS can also take a map density by area map and use the data to construct a dot density map to represent density graphically.
When using GIS to create a density surface there are many factors to consider including cell size, search radius, calculation method, and units of measurement. Another thing to consider when creating a density surface is that data that is summarized by defined areas can be used to make these types of maps but it must be generalized by the centroid of each defined area. This means that the summarized data is assigned to the point at the center of the defined area for which it is summarized. Additionally, for these maps a graduation of colors is assigned to each value so that the density can be visualized. The results of creating these types of maps in GIS are almost entirely dependent on the choices made with the many variables that can be manipulated in the program, meaning the same data can look different in final products where different visualization choices were made.

Chapter 5 discusses the need to map what is inside an area. This is necessary because the bonds for these areas can be “within 1000 feet of a school” or something like that to impose stiffer punishments on crime. This is an example of finding what is inside one area but you can also use mapping to find what is inside several areas such as each district in a city. In either case, you first have to know the boundaries of your area(s). Then, the discrete or continuous nature of the features you are measuring has to be taken into account. You can also use GIS to list features, count them, or get a summary. You also have to consider if the features being measured are completely in the area because discrete features can easily be partially in or out of a defined boundary.
There are three ways to find what is inside the area. First, drawing both the areas and the features, this way you can see the boundaries of your area and what features are inside it. This is specifically good if you only need to know which features are inside and outside of an area. Second, you can specify the area and the layer that contains your features so that GIS selects a subset of the features which is inside the area. This is best for getting a list of the features inside an area. Finally, you can overlay the areas and the features to create a new layer which compares the two layers and summarizes the statistics for each area. Which is best for doing both at the same time, as it is the most flexible.
Using the results of these summaries can be tricky. Some ways it can be used include: the count of a total number of features in an area, the frequency of a number of features with similar values in an area, or to summarize a specific numeric attribute such as the sum of certain features. These similar principles can be applied to much more complicated data, overlaying layers onto each other and creating understandable visualizations of complicated data over a range of areas.

Chapter 6 focuses on mapping what is nearby to a feature. This is important because some features may require notifying anyone living within a set distance. However, “nearby” is a concept that ranges in distance, within GIS you must define the distance which is being considered as nearby. Sometimes it is just straight distance away, or in some cases distance has to be measured using networks of transportation such as roads. Distance and cost can both be used to measure what is nearby, cost can include the amount of time it takes to get somewhere from your location. You also must consider the information you require from your analysis, sometimes it may be a list of everything “nearby”, a count of the total number of restaurants nearby, or a summary statistic for the area.
To determine “nearby” you can use GIS to set an inclusive ring based on straight-line distance, which is best for defining the area of influence around the feature. To do this you have to create a buffer in GIS at a certain distance from the feature you are discussing. Additionally, using this method you can use GIS to find the distance between two features, or to create a spider diagram with your chosen feature at the center. Another option is using distance or cost over a network (such as roadways), which is best used when measuring travel over a fixed infrastructure is necessary. GIS includes a ready-to-use street network which can be used to find whats nearby in terms of distance; however, this is not the only possible network you may want to use so custom networks can be built in the program. GIS will start at your feature and check the distance to the nearest junction in relation to your specified distance, and it will repeat this until a definition of everything “nearby” has been reached. You can also specify more than one center in this type of mapping. Finally, measuring cost (of time or another variable) over a surface is most helpful when you need to measure overland travel and calculate how much area is within your range. This has to be done using a raster layer of continuous distance from your feature.

Chapter 4: 

Chapter 4 dives into the concept of mapping density and its significance in identifying patterns and concentrations of features. Mapping density is especially useful for understanding patterns rather than focusing on individual features or locations. The chapter explains two primary methods of mapping density: by defined area and by density surface. In the defined area method, density can be represented using a dot map or calculated density values for specific regions. On a dot map, each dot symbolizes a fixed number of features, with higher dot concentrations indicating greater density. Additionally, shading areas based on calculated density values helps visualize where concentrations are higher or lower. The density surface method is more detailed and uses GIS to create raster layers, assigning density values to individual cells. This method requires more data and is time-consuming but provides higher accuracy, especially when analyzing specific concentrations. Each approach has its strengths: defined area mapping works well with pre-summarized data, while density surface mapping is ideal for examining specific points or locations. The chapter highlights that tools like dot density maps and raster layers simplify interpreting and visualizing density, enabling users to identify concentrated points or areas with ease.

Chapter 5

Chapter 5 emphasizes the importance of identifying and analyzing what exists within a specific area. Mapping what’s inside allows users to identify patterns, summarize features, and understand variations within different regions. This approach condenses complex data into accessible visual representations, helping viewers grasp where certain features or activities are more or less concentrated. The chapter differentiates between analyzing a single area and multiple areas. A single area provides focused, detailed insights, whereas multiple areas allow for comparisons across regions. It also highlights the need to classify features as either discrete (specific, countable items like buildings) or continuous ( less tangible elements like pollution levels). GIS tools offer three main ways to determine what’s inside: drawing areas and features, selecting features within an area, and overlaying areas and features. Drawing areas and features provides a visual representation of the data, while selecting features allows for summaries or counts of what exists within a boundary. Overlaying areas is especially useful for finding overlaps between features and regions. Overall, the chapter underscores the flexibility and efficiency GIS provides for analyzing what lies within specific boundaries.

Chapter 6: Finding What’s Nearby

Chapter 6 focuses on identifying features near a specific location and the methods for doing so using GIS. Understanding proximity is critical for planning and decision-making. GIS allows users to analyze what’s nearby by specifying a distance and then measuring that distance in different ways: straight-line distance, distance or cost over a network, or cost over a surface.The simplest method is straight-line distance, where you set a central feature as the source and define a radius to identify surrounding features. This is often used to create boundaries for proximity analysis. Another method is distance or cost over a network, which is useful for examining distances along roads or transportation networks. The third method, cost over a surface, focuses on analyzing travel costs across uneven terrain or landforms, such as overland travel. A key tool discussed in this chapter is creating a buffer, where you define a source feature and set a specific buffer distance. Once the buffer is established, you can identify, list, or summarize the features within it. Overall, this chapter builds on previous topics by emphasizing how GIS can analyze proximity, offering practical applications for planning and analysis based on what is nearby.

Chapter 1:

Chapter 1 focuses on an overall introduction to GIS. This introduction does not reduce GIS to ‘only a software,’ but also emphasizes the impact it has made across diverse disciplines. Through new technologies, researchers sharing their findings online, and advancements in the software itself, GIS has created a space for itself in disciplines from healthcare to construction. However, while this emphasis of the diversification of uses for GIS is important, what is more important is how the standard use of GIS has not changed. A user must still be able to structure their analysis properly and know which tools are applicable to the tasks they are carrying out. The part of GIS that has always interested me (without even knowing what GIS is) has been comparing mapping changes. Growing up in the rust belt in the early 2000s, much of what I remember as my hometown has been torn down. I remember neighborhoods upon neighborhoods of abandoned homes, however now even the streets they once stood on are gone. Chapter 1 goes on to expand upon what GIS Analysis is and the process of carrying it out. The portion under the subheading Frame the Question, “Or you may need to present results to policy makers or the public for discussion, for scientific review, or in a courtroom,” truly stuck out to me. I am currently taking Dustin’s Scientific Communication class. This concept of angling research and the language of said research to your audience is something that has interested me since beginning my undergraduate career. The way geographic features were described and explained was something that I cannot say I have ever seen before this reading. However, that being said I believe that these definitions are extremely valuable and should be introduced to those working outside the discipline of Geography/GIS. The skill of being able to read maps (both those for travel and information) is something that people my age are extremely lacking in. Taking these concepts such as ‘Discrete Features,’ or ‘Continuous Phenomena’ are elements of maps that I have often seen/heard of. However, this is the very first time I have ever been given a name to put to them.

Chapter 2:

As I’m reading through the first few chapters of this book, it is doing such a good job explaining these concepts that I often try to, but fall flat with my family/people outside of my major. It is very refreshing to see definitions that use simple language without diminishing content. The example, on page 24, of police mapping where crimes occur seems well intended, however, in practice wouldn’t this need exponentially more context and information? If implemented exactly how the example is written, could the GIS use be directly linked to potential over-policing? I appreciate the sections in the book where it is written in a way that prevents you from overthinking. For example, on page 26, it discusses using appropriate features, implying sometimes ‘less is more.’ Much of this chapter is introducing basic ‘rules’ to follow when mapping. Things such as creating multiple small maps if information is too compact, or choosing bright colors for important information and leaving more pastel/dull colors for necessary yet not critical info are themes that run strong throughout this chapter. All of this information, while it may seem lackluster or somewhat boring, is actually very crucial to making high quality legible maps. This portion of the chapter can also be related back to Dustin’s Scientific Communication class. In order to make your map as effective as possible, you must know your audience. A crucial part of ‘knowing your audience’ is changing the formatting of information without diminishing the quality of said information. In providing the reading multiple different examples of how to communicate the same information, the book is preparing future GIS users on adapting to their audience. One portion of the chapter that I am still not fully comprehending is the discussion of how GIS uses coordinates. I understand the basic premise discussed that you select the coordinates where you would like a symbol, to define boundaries of a land parcel, etc, however, are these coordinates that I have to retrieve on my own? If so, what is the process of doing so? I could be totally overthinking this (which would be a relief).

Chapter 3:

Chapter 3 keeps the focus on this set of ‘rules’ that are important to remember when making effective maps. However, where chapter 2 took a strict focus on the interpretability of maps, chapter 3 focuses on the quantitative aspects of these maps. Opening with the concept of mapping the most and the least, this first topic discusses how to successfully and efficiently communicate your numbers through the map. A very good example of this is the comparison between the mapped Locations of businesses vs. Businesses mapped by number of employees on page 52. The concept of Continuous Phenomena was somewhat difficult for me to grasp at first. I do believe that I was fully overcomplicating it for myself. However I still do have some questions about it. As continuous phenomena can be defined as areas or a surface of continuous values, how would I determine which is more effective? Is this something that I would just have to evaluate on a case-by-case basis? Am I thinking too much into this? Page 56 discusses the different ways that you can present this quantitative data and how this would impact the perspective of your audience. This portion of the chapter focuses on whether the use is ‘exploring the data or presenting a map.’ I have been consistently, pleasantly surprised by this book. I had assumed that these chapters were going to be boring, strictly informational pages discussing the actual usability of GIS. However, this approach of providing a user the practical, real-world uses for the software is very refreshing. It is getting me excited to stare at maps for hours on end. The section discussing counts, amounts, ratios and ranks was very helpful for me. As someone who does not have a brain for math, the explanation of what to use when was exactly what I needed.

Chapter 1:

In the first chapter of “The ESRI Guide to GIS Analysis,” Andy Mitchell introduces the concept of Geographic Information Systems (GIS). A GIS is a powerful tool that helps us understand and analyze spatial data information about the locations and shapes of features on Earth. The chapter begins by explaining the basics of GIS, emphasizing its role in transforming raw geographic data into meaningful information that can be used for various purposes. Mitchell discusses two main types of spatial data: vector data and raster data. Vector data represents features using points, lines, and polygons. For example, a point could represent a city, a line could represent a road, and a polygon could represent a park. On the other hand, raster data is made up of grid cells or pixels, and it is often used for continuous data like elevation or temperature. The chapter also highlights the importance of spatial thinking. It explains how GIS can be used to visualize patterns, relationships, and trends in geographic data. By using GIS, we can make more informed decisions in fields such as urban planning, environmental management, and disaster response. Overall, this chapter lays a solid foundation for understanding the fundamentals of GIS. It introduces key concepts and definitions that are essential for anyone interested in exploring the world of geographic information systems.

Chapter 2:

In the second chapter, Andy Mitchell focuses on the visual aspect of GIS. The chapter delves into the art of map design and the importance of creating maps that are both informative and pleasing. Mitchell emphasizes that good map design is crucial for effectively communicating geographic information. One of the key concepts discussed in this chapter is thematic maps. Thematic maps focus on a particular theme or subject area, such as population density, land use, or climate zones. These maps use various symbols and colors to represent different types of data, making it easier to understand and interpret the information. Symbology, the use of symbols to represent different types of data on a map, is another important topic covered in this chapter. Mitchell explains how choosing the right symbols and colors can enhance the clarity and readability of a map. He also discusses the concept of layering, which involves stacking multiple data sets to create a comprehensive map. By layering different types of data, we can gain a deeper understanding of the relationships and patterns within the data. Overall, this chapter provides valuable insights into the visual aspect of GIS. It highlights the importance of effective map design and offers practical tips for creating clear and informative maps.

Chapter 3:

The third chapter explores the process of interacting with GIS data through querying and selecting. Andy Mitchell explains that querying is a way of asking questions about the data to extract specific information. There are two main types of queries discussed in this chapter: attribute queries and spatial queries. Attribute queries are based on the characteristics or attributes of spatial features. For example, we might want to find all the cities with a population greater than 100,000. Spatial queries, on the other hand, are based on the location and spatial relationships of features. For instance, we might want to find all the parks within a certain distance of a river. Mitchell also introduces the use of Boolean operators (AND, OR, NOT) to refine queries and make them more precise. Additionally, the concept of buffering is explained. Buffering involves creating zones around a feature to analyze proximity and spatial relationships. For example, we might create a buffer zone around a highway to study its impact on nearby wildlife. Overall, this chapter provides a comprehensive understanding of how to query and select data in GIS. It offers practical techniques for extracting meaningful information from geographic data and emphasizes the importance of precision and accuracy in spatial analysis.

Hello, my name is Jake Marzulli I am majoring in Sports management and getting a minor in coaching. I love running and being outdoors and hanging out with my friends doing various activities Aswell as traveling to warm places!

Chapter 1

Chapter 1 of Schuurman’s book gives a fascinating overview of Geographic Information Systems (GIS) and how it plays an important role in our daily lives. GIS is more than just making maps it helps us understand patterns and solve problems in many fields like farming, government, and business. One interesting example is how scientists use visuals, like the double helix image of DNA, to figure out relationships and cause-and-effect. GIS does something similar by turning data into pictures that make it easier to analyze and make decisions. The part about farming really stood out. Farmers now use tools like GPS and soil analysis with GIS to figure out the best way to plant crops or deal with issues like blight (a crop disease). This helps them save time and money, but it makes me wonder if smaller farmers without access to this technology might struggle to keep up. It seems like technology could create a bigger gap between big farms and small ones. In cities, GIS is used in things like planning garbage collection routes, fixing roads, and creating bike paths. Schuurman shows how it makes life more efficient, but I liked the part about traffic jams during road repairs it’s a funny reminder that even advanced tools can’t solve every problem perfectly. The section on e-governance was also really interesting. GIS helps governments deliver services like registering cars or planning new parks. This can make things easier and fairer, but it also raises concerns about privacy. For example, governments collect a lot of digital data, and people might worry about how it’s used. Overall, this chapter shows how important GIS is for understanding and organizing the world around us. It’s not just about technology it’s about how we use it to shape our society.

First Gis Application

This article discusses how GIS helps police predict and prevent crimes by analyzing historical crime data and identifying hotspots. By visualizing crime patterns, police can allocate resources more efficiently, improving crime prevention and response times.
Source: The Times

Second Gis Application

This is interactive map where users can view reported incidents of various crimes, such as theft, assault, and burglary. The map allows for filtering by crime type and location, offering insights into local crime trends and helping residents and law enforcement better allocate resources to improve safety. The map is designed to keep the public informed about crime activity in the area. Memphis Crime Map – GIS Geography

Chapter 4:  Mapping Density

This chapter goes over the types of density maps, what there uses are and how to created them t o effective show you data. Mapping density shows where the highest concentration of a feature is and lets you measure the feature using a uniform areal unit.  They are particularly helpful in highlighting patterns over very large areas. Before actually mapping it is important to think about what features  you’re trying to map, what data you already have  and deciding if you want to map features or values. To map the density of your desired feature, you can either shade defined areas using a density value or create a density surface.  To map a defined area you can use a dot map (to show specific locations) or calculate a density value for each area (divided the total number or value of features by the area and shade each area based on its density. When creating a dot density map it is important to define the about of feature a dot represents and the size of the dots will depend on what patterns you want to highlight. In GIS raster layers are used to create a density surface by defining a neighborhood (based on your specified radius which depends on the map size), totaling the number of features in said neighborhood and dividing it by the area. That value then gets assigned to the cell (the size depends on how defined you want the pattern to be)  and moves on the next. The final result of the map depends and how effective it is greatly depends on all of the variables you decide to utilize as mentioned above.

Chapter 5: Finding Whats Inside

The reason why people even map what is inside areas to monitor whats occurring in said area and compare to other areas so that proper action can be taken in the appropriate place. To actually find what is inside you can draw an area boundary on top of the features, use an area boundary to select features inside then list and or summarize them, or combine both the boundary and features to create a data summary.  Your method will depend on how many areas you have, the type of features are in the areas and the information needed from the analysis. By drawing the areas and the features you can determine which features are inside and out of the area you are looking at. When you just select the features inside the area, you can better list and summarize what features are specifically within the area. lastly, overlaying the areas and features  is a good option for finding what features which features are inside which areas and for summarizing how many or how much by area.  When drawing the desired areas and features it is important to keep in mind what will make it easiest to see the features within the area(s).  When mapping individual locations or linear features you can just use one symbol but if there are multiple then different symbols are needed and are to be defined. If you want to show discrete areas how you decide to do that will depend on if you want to emphasize the features inside or the area itself.  If you are mapping continuous data the areas symbolized by their categories and then draw the boundary on top. Once you have your desires results you can create a chart from the data and compare different areas.

Chapter 6: Finding Whats Near By

By using GIS you can find out whats happening within a certain distance of a feature and also what is within traveling range. This allows you to monitor the surrounding area and what is in it. Also the traveling range which is measured using distance, time, and cost can help define a certain area served by a facility and it also is helpful in finding areas that are suitable for or capable of supporting a specific use.  To actually find what is near by you can measure in a straight line distance, measure distance or cost over a network or measure cost over a surface. To determine what method works best for what you are trying to you should ask these questions. Is what’s nearby defined by a set distance, or by travel to or from a feature? Are you measuring whats nearby using distance or cost? Are you measuring distance over a flat plane or using the curvature of the earth? Do you need to list, count, or summary? How many cost or distance ranges do you need? In general straight line distance is best used for creating a boundary  or selecting features at a set distance around the source. Using the distance or cost over a network is good for measuring travel over a fixed infrastructure. Lastly, cost over a surface is used for measuring over land travel and calculating how much area in within the travel range. All of the mapping method have practical uses in many things such as a state forester needing to monitor local logging to make sure it doesn’t cross a set buffer, determining the streets that are within a 3 minute drive from a fire station and finding the best route to get from one location to another in the most time efficient way.

Chapter four focuses on the fundamentals of density mapping in GIS and how it is used to visualize patterns in data. Mapping density helps identify the concentration of specific features or occurrences within a given area, making it an effective tool for analyzing trends. According to Mitchell, density mapping can be performed in two primary ways: by defined area or by density surface. Defined area mapping uses dot maps to represent density geographically, offering accuracy in pinpointing data points. However, this method makes it harder to observe broader patterns. On the other hand, density surface mapping utilizes raster layers to create a concentration gradient, which makes identifying trends much easier. To effectively apply density surface mapping, several factors must be carefully managed, including cell size. If the cells are too large, patterns may become overly generalized, while smaller cells can strain processing resources and slow down analysis. Choosing appropriate measurement units is equally important, as selecting incompatible units can skew data and misrepresent results. Additionally, the chapter emphasizes the importance of selecting a clear color gradient to enhance readability. Without distinct visual differences, data patterns can be difficult to interpret. Overall, chapter four provides a strong foundation for understanding how density mapping can be used to represent spatial data effectively.

Chapter five introduces the concept of adjusting map parameters to analyze specific sections, an essential aspect of GIS mapping. This chapter outlines how mapping within areas can help refine data analysis to focus only on relevant regions. It provides examples such as examining soil composition within floodplains or analyzing man-made structures within protected areas. According to the chapter, there are three main methods to achieve this: drawing areas and features, selecting features inside an area, and overlaying areas and features. Drawing areas and features is the fastest and easiest method, but it is purely visual and does not provide quantitative data. This makes it a good starting point but unsuitable for more detailed analysis. Selecting features within areas allows users to gather quantitative data, but the GIS software treats the entire selected area as one unit, which limits further segmentation. Overlaying areas and features offers the most precise results, allowing for detailed analysis of subsections. However, this method is resource-intensive and may not always be practical for time-sensitive projects. Once the appropriate method is chosen, users can visualize the data using tools like bar charts, pie charts, or tables. Each visualization method has specific use cases, and the chapter offers guidance on selecting the most appropriate one based on the data. Chapter five highlights the importance of narrowing down data to specific areas for better pattern recognition and analysis, making it a critical aspect of GIS mapping.

Chapter six shifts the focus from what is inside a specific area to what is around it, introducing the concept of proximity analysis. This approach is useful for studying relationships between features and understanding spatial interactions. For instance, proximity analysis can be used to measure distances between features or observe overlapping areas. A particularly intriguing aspect of this chapter is the introduction of cost-based analysis, where time or effort is used as a measurement instead of distance. This approach is particularly relevant for urban planning, as factors like traffic can make distance an inaccurate measure of accessibility. The chapter also explores how cost is influenced by geographic surfaces and how GIS software can calculate these changes. This adds depth to proximity analysis and provides new ways to evaluate relationships between features. Other tools introduced include spider diagrams, which visually show connections between locations and features, helping to identify overlapping or nearby areas. Additionally, the chapter emphasizes setting a maximum distance for analysis to avoid overloading systems with excessive data, which can lead to crashes and delays. These insights are particularly useful for practical applications, such as planning sports facilities near communities or analyzing travel times for athletes. Overall, chapter six provides an in-depth look at how GIS tools can analyze spatial relationships beyond immediate boundaries, offering a wide range of possibilities for data-driven decision-making.

Chapter 4

When reading chapter four I learned many new terms and found many things interesting. Firstly starting mapping density is very interesting, I like how it is well explained how this differs from other maps and that it can be more efficient than when blocking concentration of areas. Along the sames lines as this density surface being created by GIS is also cool to see and be explained in this book. I would have never thought the calculation process would be a complex as it is, the images shown to depict this are also very interesting. Also the significance of cell size is something I never considered to be a detrimental factor to GIS. The word Quantile is something new that I learned which essentially means that each class has the same number of cells in it. Contour lines are also something I found very interesting especially since when I have seen them before it is typically associated with the documentation of hills and ground patterns. To see it here being used in GIS not just for land but in terms of value and change like for example used with mapping local businesses. I also find it interesting how much data impacts the map we see more data points equals an increase in density which creates a more cohesive and readable map, while only a few points can cause a more empty map and leave it harder to read. Overall chapter four gave more clarity and purpose for density mapping and how this can be more efficient as well as holds important.

Chapter 5

When starting chapter five there were again many things I learned as well as found interesting. Starting with the difference between single area mapping versus multiple area mapping. Firstly this is something I knew coming into this chapter the difference being that single areas focus on just a single plot point data set area. While multiple areas plot multiple sets of data and points in a given area that then compares these data sets. I can see how both would be desirable as data sets, however I find that seeing inside multiple areas can be really useful. I also feel like discrete and continuous has been something discussed in earlier chapters, the same seems to apply to these features when applying it to finding what’s on the inside. I also found the linear features can lie outside of features as well as inside. When looking at the map example images given this looks very interesting I also found how mappers utilize this feature as an example of wanting to include parcels within a 300 foot buffer, the usage of this method seems to prove useful. Finding what’s inside is explained very thoroughly and as such is an easy concept to grasp. I also appreciate the table with the comparison and the good features and trade-offs for each method is very nice. It’s also very nice how you are able to select certain feature within an inside area. I honestly did not really concept what GIS is capable of, however it does really remind me of the coding site R studio, in that they both are very capable of doing a lot that allows for data to correctly be read. It also seems like the software we are going to be using within this class ArcGIS has some handy tools to make utilizing results easier. Overall this chapter seemed to explain a how to use GIS with the contents of finding what’s inside, it seemed a lot of the methods and concepts seemed to apply to earlier chapters  and thus I feel as though I was able to grasp these terminologies more.

Chapter 6

Finally when starting chapter six I again learned many new things as well as found other things very interesting. I will first start with the concept of chapter six, being finding what is nearby, this being able to find and monitor events within a given respected area is a concept I again never thought GIS would be able to do. I will say that one thing I have found when reading this book is that I am constantly finding out all that GIS can do and it is typically more than what I believe it can do. Steering back my interests and learning ot chapter six, I did not know to find what is nearby in GIS you need to consider the measuring of either distance or cost, specifically cost being the measurement of time. This is something I again would have never thought GIS could do.  I also like the incorporation of different mapping types that can be utilized to find this data and the  three differing ways of finding what is nearby. Again the chart used to show the differences and the pros and cons of each of these methods makes for  linear and cohesive learning experience for me as the reader. When looking at the types of maps that can be made for finding what is nearby (excluding the continuous maps) I find similarities to these and the graphs you can produce with R studio. Overall this chapter was a longer one that seemed to explain yet another new method of mapping just as the previous chapter (chapter five) did. With this being established I found it helpful how all measures were explained and shown with examples.

Chapter four was all about how density mapping works in GIS and how to perform it effectively. Mapping by density is an effective way to see patterns in data, and is a sort of progression. to most and least mapping, which we learned in the previous chapter. Basically, being able to see the concentration of an occurrence/feature on a map allows one to get a general idea about the aforementioned feature. According to Mitchell, there are two main ways of mapping density using GIS: by defined area and by density surface. Defined area mapping means that you use a dot map to show density geographically, and is more accurate to the actual data points, but at the trade of it being harder to see a pattern emerge. Mapping by density surface, however, makes it easier to see the pattern, as it utilizes a raster layer to create a concentration gradient. There are many factors involved in choosing which form of density mapping to do, as well as how to effectively do said mapping. For instance, in density surface mapping, the cell size needs to be picked correctly, as if it is too large, it can make the pattern harder to discern, or if it’s too small, it can make data processing time much longer. It’s a balancing act of getting the most accurate data possible, without decreasing efficiency. This is also apparent when picking what units to use as the area in density mapping, as using the wrong unit can make skew the data. This chapter also empathized using a good color choice/ gradient, like chapter 3. This is because without easy to see differences, the data pattern can be hard to make out. Overall, this chapter was very effective at teaching the basics of density mapping.

Chapter five was a bit of a hard chapter. It starts introducing how to actually adjust/ modify the map parameters to show results for only certain sections. This is obviously a very important aspect of GIS mapping, but it’s a little complicated too. There is a lot of examples for why this is used, such as seeing differences in things like precipitation level or soil content inside of a floodplain, or observing the man made features inside a protected area. Analysis is one of the main purposes of mapping, as it allows for understanding patterns against geographic location, so being able to narrow down the parameters to just what a person is interested in is very important. According to this chapter, there are three main ways to do this: drawing areas and features, selecting the features inside an area, and overlaying the areas and features. Out of the three, drawing areas and features is the easiest and fastest to do, but it is purely visual and provides no concrete data. It can be used as a starting point, but is not proper for deeper analysis. Selecting features is better for getting quantitative data, but it cannot be separated into other areas, as it is treated as one by the GIS software at that point. Overlaying is the most accurate way of getting quantitative data, as it allows subsections inside the area a person is interested in. However, this method takes the longest and uses the most processing power, so it is not always suitable. Once you’ve picked which method to use, there are various ways to actually view the data, such as bar charts and pie charts, or tables. Choosing which of these to use to observe your data is also case dependent, but the chapter provides a good baseline for when each is most appropriate.

Chapter six was packed with a lot of complicated, but important information. This chapter taught me about how to analyze data based, not on what is inside a certain area, but what is around a certain area. This is obviously very useful for mapping, as it allows for things like analyzing distances between features or observing overlapping areas between features. What I found most interesting, however, was the idea of using cost to analyze a measure, as opposed to distance. In hindsight, it makes senes that not all mapping data is best viewed by distance, especially for things like urban planning. After all, things like traffic can make distance less reflective of the actual time taken. I especially enjoyed learning about how cost is changed by the geographic surface, and how the software can calculate said change. It is just very interesting for me to think about, and I find that one can use GIS to measure by cost to be very promising. Besides that, the chapter introduced a lot of new map making concepts, which is good, but also a bit hard to wrap my head around. For instance, spider diagrams are used to show the distance between a feature and a location, which can allow for one to see overlapping areas. This mapping technique has not been brought up before, and it is far from the only new one. Regardless, when there are so many types of data and data analysis, having a wide range of tools to observe this data is important. I also think that the information about setting a maximum distance for analysis is very important, as too much data could crash the computer, which is highly annoying to deal with. Nevertheless, I am excited to learn how to use the software.