Month: January 2024

Charlie Hornacek

C1

The initial exposure to GIS in Chapter 1 provides a foundational understanding of its processes. The step-by-step breakdown of GIS, akin to the scientific method, introduces you to the generic process involved. The distinction between discrete and continuous features on GIS maps is explained, along with their representation using vector and raster models. along with the concept of attribute values, categorized into five types, adds depth to the understanding. The chapter concludes with a discussion on data tables, emphasizing the practical aspect for better comprehension.

C2

Chapter 2 talks about the significance of mapping within GIS analysis. The chapter emphasizes that maps can be powerful tools for recognizing patterns and addressing specific questions. Different mapping methods, such as mapping with a single type of method or mapping by category, are explored. The chapter provides insights into the importance of understanding the audience when creating maps and the challenges associated with choosing symbols and determining map size. Overall, it underscores the practical aspects of mapping within the GIS framework.

C3

Chapter 3 builds on the mapping concepts introduced earlier, focusing on mapping quantities and classifications. It revisits the notions of discrete and continuous mapping, along with a detailed exploration of attribute values like counts, ratios, amounts, and ranks. The introduction of standard classification schemes, such as natural breaks and standard deviation, adds complexity. The chapter also talks about the trade-off between accurate representation and generalization for pattern recognition, emphasizing the importance of dealing with outliers in the mapping process.

Chapter 1

Introducing GIS Analysis

This chapter is informative when it comes to understanding GIS analysis, along with geographic features and attributes. It described the process of GIS analysis as looking at geographic patterns in data and the relationships between features. There are various methods to this which can look simple or more complex. I like how the reading broke up the different parts of the analysis process including; framing the question, understanding your data, choosing a method, processing the data, and then looking at the results. It was also interesting how the book pointed out that when it comes to geographic features, it is important to note that the type of feature you are working with will affect all the steps of the analysis process previously mentioned. These types of features can look like discrete features, continuous phenomena, or even features summarized by area. These are important to break down because I can see how foundational these features are to GIS analysis in enabling understanding and supporting applications. Finally, geographic attributes identify what the feature is and either describe or represent some magnitude associated with it. Some attribute values can look like categories, ranks, counts, amounts, and ratios, and it is crucial to know which one you are working with because this changes the type of analysis you are doing with GIS. 

 

Chapter 2

Mapping Where Things Are

This chapter was helpful in understanding the purpose of mapping where things are, deciding what to map, how to prepare your data, how to make the map, and analyzing geographic patterns. It was unique to me that the reading specifically pointed out the purpose of mapping where things are. You do not typically think about this broad of an idea but it makes sense now why it would be important to remember why people use maps so you can explore causes for the patterns you see. Deciding what features to display and how to display them can be done by reflecting on the information you need and what the map will be used for. It is interesting how the level of detail needed to be displayed can change depending on the purpose of the map. Preparing the data for the map can be done by assigning geographic coordinates and category values. One thing I noticed is how tedious it must be if your data is not already in the GIS database. Entering it by hand and giving location information like street addresses, or latitude-longitude values would take up a lot of time. When the reading discussed how to make the map itself and all the types that can be used, I appreciated all of the examples and pictures that were included. It helped me gain a better understanding of what the results might and probably should look like when using GIS. Finally, analyzing the geographic patterns that are presented is allowed by distinctly given information. 

 

Chapter 3

Mapping the Most and Least

Chapter 3 talks about the use of mapping the “most and the least” and why you should do this. It gives readers a better understanding of what you need to map, quantities, how to create classes, and how to make a map while looking at the patterns it displays. This chapter went into more detail about things previously mentioned and learned in the first two chapters which I appreciated. Mapping the most and the least was a concept I had never heard of before. From the text, I understand this as the process of mapping features based on quantities which is described as adding an additional level of information more than just mapping location and features. Again, the features you are mapping are important as well as understanding the quantities you are mapping. The reading says quantities can be counts or amounts, ratios, or ranks, these reminded me of the attribute values explained in the first chapter. This helps you decide on the best way to present your data. Creating classes was the next section that stood out to me, deciding whether to assign each specific value its own symbol or to group the values into classes. Finally, the author’s explanation of making a map was again supported by a good amount of example maps that presented various ideas and approaches and this was helpful for me. It was really cool to see the 3D maps and all the factors to consider such as viewer location, z-factor, and the light source. Overall, I felt like this chapter covered a lot of things that were already discussed in the first two chapters, but in some ways, it was a good overview and in other ways, it was helpful to see the topic or idea explained more in-depth. 

Chapter 1

• Because GIS has been around for such a long time the tools and technology that use it have evolved significantly. The number of people that are familiar with GIS has also increased along with the usage.
• The most common uses of GIS seem like they could be used very broadly for a wide variety of fields. I would be interested in seeing an example of each of these uses, particularly the ‘finding what’s inside’ point because I am have a little difficulty imagining what this could be applied for. Maybe what species is inside a geographical region?
• GIS is described as being a process for observing patterns and relationships in features. It does so through the construction of maps or models.
• The way working with GIS is described sound very similar to the way conducting a scientific experiment is; Start with a question, choose methods, gather information, and observe and analyze the results.
• As I was reading I did have a question of the definition of a ‘parcel’ because it was brought up many times and used in a way that I was not familiar with. After a quick search I found that it was simply an area of land with clear boundaries, often split off from a larger chunk. This made the word make much more sense in the context of the book.
• I think the idea of continuous data/ phenomena showing similarities between areas rather than exact information is interesting. It’s seeing more of a relationship between areas that you may not be able to observe as easily without the visual, such as simply using a table.
• Summarizing data and mapping discrete features should use the vector model, and continuous numerical values should use the rester model.
• Categories and ranks are not continuous values because they are assigned one set, whole number. Contrarily, counts, amounts, and ratios are continuous values because they are not assigned a set number and can be anywhere within a range.
• The process to select features seemed a little technical at first, but this section of the chapter seemed to make it make sense and acted as a helpful guide.

Chapter 2

• The first few pages of chapter 2 seemed a little redundant. It established that mapping is important and locational information has many uses across a variety of fields, which is something that the reading we did for last week also elaborated on.
• It’s important to remember that when you’re making maps you should assign geographical coordinates to features and possibly category types as well.
• Mapping by subsets or mapping by whole features/categories can be beneficial in identifying patterns that may not have been observable using the opposite method (they both have valid uses).
• The connection between recommending a maximum of seven categories and the human ability to easily identify seven colors is pretty neat. Having a cut off to ensure clarity also seems like it could prove useful keep in mind for future projects (keeping in mind there seems to be a sweet spot in between having not enough categories and leaving out information and having too many that it gets confusing).
• You can group categories by either providing each category a detailed code and a general code or by creating a table with a detailed code and general code which can then be combined with the feature database table to be displayed using the general code. The second method make it easier to adjust the category groupings. The third method is to use a symbol for each general category, which can be reused if needed later.
• The issue with using symbols is that they are harder to separate than points using color, especially if the shapes are small. I would imagine that combing shapes and color variations may be an even more effective way of distinguishing features.
• ArcGIS provides basemaps that you can use that contains grayed-out reference buildings and landmarks for you to overlay your information on top of.

Chapter 3

• One of the first things I noted was how many examples there were in this chapter. I think it will be helpful to see all the different methods of mapping quantity – through contours, summaries of areas, and gradating colors, for example- that you can use choose from to most accurately and legibly display your information.
• If the areas you are summarizing vary in size you should use ratios (averages, proportions, or densities) rather than counts to be able to accurately observe patterns. This seems like important information, especially since skewed data can become a major problem and fuel misunderstanding of an issue or piece of information (can do more harm than good, despite the intentions).
• The concept of ranking seems intriguing to me, especially when it comes to things that are more subjective like the provided example of the scenic value of a river. What factors are used to determine the ranking? Though this may be helpful to some, what’s the determining factor of the rankings that makes it widely accepted as a ‘correct’ ranking?
• A lot of sections in this chapter appear to be ones taken almost directly from other chapters (ex. river ranking example, business example, and even several paragraphs explaining the relativity of ranks) so it was a little redundant at times.
• Natural breaks (classes are based on natural groupings of values), Quantile (Each class contains an equal number of features), Equal Interval (high and low values of each class have the same difference between them), and Standard Deviation (classes are based on their variation from the mean) are all ways to classify information. They each have their own strengths, weaknesses, and uses. This section of the book appears to be very helpful in determining which scheme to use based on a chart your data produces.
• Graduated symbols, graduated colors, charts, contours, and 3D perspective views are all map formats that you can choose from to effectively present your data. Similarly to the classifications, each map style has its own best uses, advantages, and disadvantages, but it mostly varies based on which type of information you would like to present.

Shaw Week 

Chapter 1

 

• GIS is an acronym for Geographic information systems
• GIS has grown immensely since the creation of it, spatial scientists realized its potential and now helps analyze most world issues 
• While spatial analysis has made great strides in advancement and accessibility learning the basics is still required to get a grasp on how to use tools
• GIS analysis is a way of looking at data and geographical patterns and finding relationships between them. 
  • Starting each analysis by doing something as simple as forming a question and finding an area where you want to explore.
• Types of features in GIS
  • Discrete Features: locations and lines, the actual location can be pinpointed 
  • Continuous phenomena: entire area between boundaries, no differences in soil, land,vegetation.
• Geographic features can be represented in GIS using two models of the world vector and raster
  • Vector: Each feature is a row in table, and feature shapes defined by x, and y locations in space.
  • Raster : features are represented as a matrix of cells in continuous space, each layer represents one attribute.

 

• Map projections and coordinate systems are all the data layers being used should be the same in map projection and coordinate systems. 

 

Chapter 2 

• Mapping is used to see what, or where an individual feature is.
  • This can help show an individual where they need to take action/ what areas meet your criteria you are looking for
• • This map allows wildlife officers to track the behavior of bears and assign officers to spots of need.
• There are many features for different layers.
  • Each feature on the map needs a location in geographic coordinates 
  • The GIS stores the coordinates that are saved and draws the features.
• Using a subset of features allows you or the user to narrow down the the category value to something more specific or even make the range more broad
• Mapping features by category can provide understanding on how a place functions
• When showing categories on a map you want to only go up to 7 because most people can distinguish up to 7 categories on a map. 
• In smaller areas that are being mapped, individual features are easier to distinguish, so more categories will also be easier to distinguish

Chapter 3 

• People map where the most and least are to find places that meet their criteria and take action, or to see the relationships between places. 
• To map the most and least you map features based on a quantity associated with each
  • Adds an additional level of info beyond mapping the locations of features
• To map the most and least you assign symbols to features based on an attribute that contains a quantity.
• Ratios show you the relationships between two quantities, and are created by dividing one quantity by another, for each feature. 
• Proportions show you what part of a whole each quantity represents. 
  • To calculate a proportion, you divide quantities that use the same measure. 
• Densities show you where features are concentrated.
  • To calculate density, you divide a value by the area 
• Ranks put features in order, from high to low. 
  • Ranks are useful when direct measures are difficult or if the quantity represents a combination of factors

Chapter 1:

Overall, it is quite interesting to view GIS from an introductory standpoint. Since I know very little about what GIS actually is, it is quite nice to grasp the basic background behind what GIS is. The chapter first starts off with the generic process of what GIS entails. The simplistic steps behind GIS remind me of the steps found within the scientific method. The chapter then goes into the types of geographic features found within the GIS maps. Discrete features are the features on the maps that can actually be defined, which are generally represented as dots or lines. Continuous features are a little more complex to me, but they seem to be features that can be measured pretty much anywhere. There can also be features that can be summarized by area, which is a more density based data. The chapter then goes on to explain how geographic features can be represented. The first way is the vector model, which seems to be a more discrete method, which seems to pinpoint exact points and areas by using coordinates for instance. The raster model seems to be a more continuous representation, where there are layers representing the entire region of the given map. Overall, the differences between vector and raster models seem to have some overlap between them and therefore can be quite confusing. The chapter then talks about attribute values, which relate to geographic features. The five attributes (categories, ranks, counts, amounts, ratios) all make sense to me. The chapter then closes off with understanding the use of data tables. The three features that you use for the data tables are selecting, calculating, and summarizing. Overall, this part seems quite complicated, and I think that actually practicing it will make it easier to understand. 

Chapter 2:

This chapter talks about the importance of mapping, and the process of how to undergo mapping through the GIS software. Personally, I find maps interesting, which is one of the reasons why I took GIS. From what I know about maps, they tell you where places are and what unique features are present in different locations. However, I find it interesting that GIS can use maps to help pinpoint certain areas that need particular attention. The chapter talks about the process of mapping. The questions that it asks seem similar to the questions found in chapter 1, which takes the process as a step by step methodology. With using GIS, there are many ways that one can map their data. Mapping with a single type method can show simplistic and universal features, which helps those find a distinct pattern. Another mapping process is through mapping by category. This adds a key to help distinguish different areas found on a map, which helps to create an idea of where different regions are located. Also when it comes to categories, you want to make sure that you don’t have too many,or else it becomes complicated for the reader. If you need to have a large amount of categories, then you might just want to generalize the categories to make things more simplistic. It is also important to know what symbols to use for defining each category in your key. Overall, the purpose of mapping with GIS is to help one analyze certain patterns going on with their data. It can be as simple as zooming in or out or removing certain features on your map that will help you pinpoint certain patterns. 

Chapter 3:

This chapter talks about mapping the most and the least, which I honestly had no idea what that meant prior to reading this chapter. However, I have learned that it is a process of mapping that helps researchers correlate patterns or find areas that need to take action. Basically, it is diving deeper into the general ideas of mapping that were discussed in Chapter 2. It also takes in certain ideas from chapter one, as the beginning of the chapter talks about discrete and continuous mapping, along with ideas from the five attributes. Although this information was a little on the repetitive side, it was still good to relearn the information, along with understanding the importance of it to the overall idea of the chapter. After the review session in the beginning of the chapter, it talks about how to properly represent the data on a map. Using counts, ratios, and amounts would generally yield maps that show different classifications. The overall idea of using classes for mapping made sense to me. However, what was a completely new concept was the use of standard classification schemes. There are four of these schemes, which consists of natural breaks, quantile, equal interval, and standard deviation. I have only heard of one of those, and the other three seem a little confusing for me to fully understand what they mean. However, it was easier to understand the overall methods in choosing what classification schemes to use depending on what data you have. The end of the chapter discussed other important aspects, such as determining how many classes you need, and how to deal with outliers.

Chapter 1
This chapter was extremely helpful in offering a step-by-step breakdown of the process I would need to go to in order to properly perform an analysis. Map-based analysis can be really daunting, so having it broken down into smaller, easy to follow steps is definitely a benefit of this chapter. Frame the question, understand the data, choose a method, process the data, and look at the results- these all help to break a large task into something easily digestible. The textbook also does a good job at explaining the phenomena we would be working with. Continuous phenomena will be found everywhere, with no gaps across the area of the map. This can be helpful for measuring elements such as rainfall or temperature. Summarizing data can represent the density of features within a boundary, which can be useful for analyzing things such as number of businesses or amount of streams within a set area. Another thing I hadn’t known before was the different ways data can be represented. There are two main ways to represent geographic features; vector and raster. The vector model takes feature shapes and defines them by their x and y locations within the location. Basically, the GIS places dots and connects them to draw lines and outlines. These spots can also be represented as points with geographic coordinates. The raster model, however, is made up of groups of cells in a continuous space. Each layer of cells usually represents one attribute, and more layers are combined in order to analyze the map. While raster maps are personally more easy for me to see and understand, it seems that they also lose some of the detail that vector maps can display. They definitely seem to have their own unique benefits, though I imagine I will need to use them myself before I am fully able to understand them.

Chapter 2
This next chapter explains the practice of choosing what to map and how to present it. It explains that mapping features of an area can be extremely useful for recognizing patterns within an area. I can see this being helpful in measuring things such as animal population, or potentially the amount of deforestation in a specific area. It’s also helpful to know that analyzing with GIS does not necessarily need to be complicated. Sometimes, all we need to know are two different variables in order to sufficiently identify a pattern or problem. The chapter also explains the importance of understanding your audience in order to make the most helpful map. For example, if the audience is unfamiliar with the area, it can be helpful to include data such as geographic features, as well as city-specific zoning (industrial, commercial, etc.). Creating a map is definitely a daunting process, as you sometimes have to manually input the location of each feature via coordinates or address. Adding value codes also seems confusing, although that could simply be a result of having not practiced it yet. Either way, it was certainly very interesting to learn what the GIS does with the data I input and how it can be such a beneficial tool for identifying patterns and analyzing them. It’s also very helpful for looking at specific subsets, such as if I want to identify the population of a specific animal from within a larger group. There is also definitely a dilemma in choosing to feature a smaller or larger map. Larger maps can show more categories and details, but they can also be overwhelming to unfamiliar audiences. Smaller maps have the opposite problem, with important information being potentially left out in order to compartmentalize categories.

Chapter 3
This chapter, while a bit repetitive, goes into more depth about quantities (being counts, amounts, ratios, and ranks. It also begins by explaining the “most and least”, which is when you map features based on the quantities associated with them, then use that to either find places that meet certain criteria to take action in, or to see the relationship between those places. The book once again describes continuous phenomena and summarizing data, this time featuring many example graphs in order to better showcase exactly what they are talking about. I find these graphs very helpful, although it can be difficult to understand some of them due to the amount of information they are detailing. My personal favorite graph is the one ranking rivers based on the quality of their fish habitats. While some of the lines can be too similar to know exactly which rank they are, it is a relatively simple and easy to understand map. This, along with the several other maps are excellent for showing the range of both use and complexity that GIS can be used for.
While I am not personally the best with numbers, this chapter does a good job at breaking down what each quantity type means, and how they might be used. They also feature a few maps for each type, which makes it easier to understand what they are talking about. The book also does mention that there is often a trade off between showing accurate amounts and generalizing the values in order to see patterns on the map. One way to get around this is by mapping individual values. However, this takes a lot more work since the values are no longer grouped together. It is, however, possibly the best way to do it if you are unfamiliar with the data or area being mapped, or want to see the raw data. This map can then help you figure out how to group the values.

CH 1

This book (site it) defines GIS analysis as “a process for looking at geographic patterns in your data and at relationships between features.” This chapter walks you through exactly what GIS analysis looks like. Sometimes it’s just creating the map, while other times it is a lot more complex by adding layers and different data that’s been previously collected. Frame the question, understand your data, choose a method, process the data, and look at the results are the steps the book suggests a person should take when running the analysis. Different methods could make the information easier to gather but slightly vague or more tedious to gather and precise. It is up to the creator to decide which is better for the question that they are trying to answer. The book also walks the reader through the types of maps and the types of data that can be shown through mapping. These include categories, ranks, counts, amounts, and ratios. Categories group similar things together and determine if there is a geographical pattern. Ranks order the data from highest to lowest. An example of this could be precipitation in a given region or libraries within each school district. Counts and amounts are expressed on a map as the actual value. This might be universities in a state or grocery stores in a county. These allow the viewer to understand the scale at which the feature is prevalent in the space. Ratios show a direct relationship between two pieces of data. Continuous values would be projected using ratio counts and amounts. These features will have a range of data so it is considered continuous. Noncontinuous values are usually quantitative. These would be categories or ranks. GIS analysis allows you to individualize the data by selecting and calculating the exact type of data that you want to express. 

CH 2

GIS analysis allows you to layer information to identify possible correlations between two variables. This chapter is entirely about mapping and how to use mapping to identify important pieces of information. It is so interesting to me that so much information has already been entered into the GIS database. Each time I read something else I realize that GIS is so big and it’s something I have not been privy to at all. When creating a map there are so many possibilities and GIS allows you free reign to adapt and curate the perfect map for the information that you are trying to display. You can map a single type which would be something like roads or forests. You can type and subtype layers of your map. The example in the book is all crimes are a type that would be entered into GIS. Then you can subtype the crimes into different categories. This makes the map more or less detailed based on what is needed. Category mapping is using different colors to differentiate within a category. This could be stored with the subcategories being which stores. The book uses roads and crime as an example. The book says that you should not display more than seven categories because otherwise it could become blurred and people may have a hard time distinguishing between different shades of colors. Mitchell goes on to discuss that it is important to use scale when creating a map. Using too many or too few categories can make the map confusing or too vague for the viewer. Categories can be grouped in different ways. One way is to give each record a general and detailed code that can be used when creating the map. The second option is to create a table for each detailed code within the general codes. This one is more tedious but it is easier to edit once it has been input. Assigning symbols to each piece of data is the third option. This is the least invasive for the dataset, but it does not save in the dataset itself. The biggest thing to consider when picking symbol designs is that color is easier to distinguish than shape, and using a variety of widths and colors will make reading the map easier.

CH3 

Chapter three begins by describing different types of maps and the different figure types. “Discrete features can be individual locations, linear features, or areas.” These discrete features are represented with different levels of a single dot. The example given is smaller and bigger dots representing the locations of businesses by number of employees. Continuous features can be an area or surface with continuous values. This might look something like a COVID-19 infection map. Continuous maps usually have shades of color to display the values that they are trying to represent. The person creating the map must know what type of map they want. What question are you trying to answer? It is also important that the numbers that are being represented are accurate and the values are understandable to a viewer. Mitchell goes on to describe how to create ranks and classes in the GIS analysis. Standard classifications are natural breaks, quantile, equal interval, and standard deviation. The best scheme will be evident based on the type of data and the goal of the map. Natural breaks can be determined by viewing a chart of the data and seeing a jump in the intervals. That would be a good time to split the data. Quantiles might cause the data to present in a deceiving manner if this is not the best classification. It displays the data and then identifies the quartiles within the data. Equal intervals break down the range into four even groups to display where the majority of the figures are. The standard deviation is decided based on the intervals away from the mean. Standard deviations would be good for seeing which features are outliers and which are above and below the mean. This type does not show the actual values which would not be beneficial in certain situations. Outliers can be dealt with in different ways depending on what they might represent. In some cases you can use a different symbol to identify outliers, another example would be to group them in their class or a class with other outliers. Mitchell goes on to outline a way to determine the best map that is available. This job is subjective, but it’s important to know the pros and cons of the different types.

Chapter 1

• A bit of review because I took GEOG 292
• GIS has evolved from simply making maps to analyzing some of the world’s most pressing issues
• Beginning of chapter focuses some of the creation of GIS maps 
  • Framing a question and why we would even create the map in the first place
  • Understanding the data that has been collected for the map. Allows you to think and produce a map in a way that the viewer can absorb the information well and possibly think critically about the information.
  • This is a part of the “choose a method” phase it talks about in order to adequately show the data.
  • Also talks about processing the data and looking at the results. All apart forming the basis of a map.
• Understanding geographic features in a map and how the data plays into that. 
• Types of features
  • Discrete features
    • Location, lines, and actual location pinpointed
  • Continuous phenomena
    • Blanket entire area of mapping-no gaps
  • Features summarized by area
    • Represents the counts or density of individual features within area boundaries
  • Two ways of representing geographic features
    • Vector Model: each feature is a row in a table and feature shapes are defined by x,y locations in space
    • Raster model: features represented as a matrix of cells in continuous space
• Map projections and coordinate systems
  • All data layers being used should be in the same map projection and coordinate system.
    • Ensure accurate results when layers are combined to see relationships
• Types of attribute values
  • Categories
    • Groups of similar things, helps organize and make sense of data
  • Ranks
    • Puts features in order from high to low. Used when direct measures are difficult or if the quantity represents a combination of factors
  • Counts and Amounts
    • Show total numbers
    • Counts is the actual number of features on a map and an amount can be a measurable quantity associated with a feature
  • Ratios
    • Show a relationship between two quantities and are created by dividing one quantity by another for each feature

Chapter 2

• Better to look at distribution of features rather than individual to gain better understanding
• Different features for different layers
• Cater map towards audience
• Each layer needs geographic coordinates and map features must have a type of category value to identify each easily
• Map features of as a single type must all be using the same symbol
  • Easily shows patterns even within the simplest of maps
• GIS is able to put the data, location, and feature types all together in order to make a cohesive map 
• Using a subset of features allows you or the user to narrow down the the category value to something more specific or even make the range more broad
• Mapping features by category can provide understanding on how a place functions
• Features may belong to more than one category, using different categories within the map can reveal different and addition patterns on the data
• Too many categories within the same map is detrimental. 
  • Display no more than seven different categories
  • When mapping an area that is large relative to the size of the features, using more than seven categories can make the patterns to hard to determine(map scaling)
  • In smaller areas that are being mapped, individual features are easier to distinguish, so more categories will also be easier to distinguish
    • Using too few categories can cause important info to be left out

Chapter 3

• People map where the most and least are to find places that meet their criteria and take action or in order to observe relationship between places and data
• To map the most and least you map features based on a quantity associated with each
  • Adds an additional level of info beyond mapping the locations of features
• By mapping the patterns of features with similar values you’ll see where the most and least are
• You can map quantities associated with discrete features, continuous phenomena, or data summarized by area
• Must keep the purpose of the map and the intended audience in mind in order to help decide how to present the info on your map
• Once you determined what type of quantities you have, need to decide how to represent them on the map
  • Either assigning each individual value its own symbol or by grouping the value into classes
• Mapping individual values you present an accurate picture of the data since you don’t group features together
  • May require more effort on the part of map reader to understand the info
• To decide which scheme to use, need to know how the data values are distributed across their range
  • Create bar chart and set horizontal axis to be attributed values and vertical axis the number of features having a particular value
• Look at outliers closely as they may be result of an error in the database or anomalies based on small data samples or may be completely valid
• Once decided how to classify data values, you’ll want to create a map that presents the info to map readers as clearly as possible
  • Keep map simple and present only the info necessary to show patterns in data

Chapter 1: This first chapter highlighted the various ways in which GIS is used, as well as the different types that are utilized. This chapter also shows how patterns are used to map out the geography of a space and how different data sets can be shown on one map. This book so far does a decent job at giving visuals to help the reader better understand what exactly GIS maps are and the types of information the maps convey. This chapter details the specific terms of GIS features, those being discrete GIS data, continuous phenomena, and area summarization. Each of these components have the potential to be used at once to map out specific areas. The ability to keep record of several key companies with GIS can help researchers monitor environmental changes in a variety of ways. 

     These maps help scientists map out large areas with coordinates. Measuring a large area can be difficult, so using GIS coordinates can help solve part of that problem. I was not previously familiar with the terms “vector and raster” before, but this first chapter helped me understand what these two words are and what they mean in the context of GIS data (vector being exact geographical points and lines and raster being a mix of “cells” that represent certain information). 

 

Chapter 2: The second chapter builds off the first and goes into detail about how the maps function and how they work. It outlines how to set up the maps and how to appropriately apply collected data to said maps. It shows the difference between smaller maps as opposed to larger ones, as well as what can be used to mark points of interest. One thing I found interesting about this chapter is the fact it suggests that no more than 7 data sets should be represented on the map. I can understand why they suggest this, but after doing some research on GIS maps, I feel like I’ve seen maps with a lot more than 7 points on them. I’m sure they suggest the smaller number to make the map easier to understand for those that are new to GIS, but once you learn how to use them and how to read them, using a few more data categories isn’t too big of an issue. 

 

Chapter 3: This chapter seems to me like it’s testing your knowledge of the first two chapters. The first two chapters served as a tutorial of sorts to introduce you to what GIS is, what it’s used for, and how to read it. This chapter poses questions to the reader to take you through the processes of creating your own GIS map. This section also makes the reader think about what data they’re putting on their map and what matters more. The types of data that’s available on the maps make it easier to compare and contrast different regions about what that area may lack compared to another. 

     This chapter goes into more detail about how to color code categories and classes of information on a map. These colors can be used to differentiate waterways from roads as well as show man made landmarks vs. natural landmarks. Contour lines can also be used to show elevation and pressure changes within a given area. 

Ch. 1 

Chapter 1 laid some groundwork for understanding and using GIS Analysis. This section focused on geographic features and data. Some of these topics were: how to use data and decide how you want to represent your data, understanding geographic features and ways to represent them, utilizing data tables, summarizing, etc. Another topic that was addressed that I am excited to learn more about is coordinate systems. It seems that they are very important to understand that your data will appear accurately. 

Something I found important was the different types of geographical features. Understanding that there is not just one type of feature used in GIS helps me comprehend part of why GIS is so advanced and useful. The 3 different types of features (discrete, continuous phenomena, summarized by area) are something I feel like everybody knows but it sits at the back of your head and it’s not really something you’re ever conscious of.

It was interesting to see (through images and writing) how GIS allows you to visualize different data sets together using overlaying. It seems like such a simple and common thing and I’ve never thought about how data is layered to create maps like these. 

Reading about the different geographic attributes and when to use them was very valuable. It’s definitely something I’ll come back and refer to when we start using the software. 

I found the data table information difficult to understand. It took me a few read-throughs to make sense of the information. Data is obviously a crucial part of GIS so I made sure to grasp the information.

Ch. 2

Chapter 2 focused more on the actual mapping and how to use different mapping techniques to achieve different outcomes. It also addressed how maps should be presented with the audience in mind. An audience familiar with the area wouldn’t need as much detail and as many references points as an audience that isn’t familiar with the area. Also, not all maps will have the same amount of details, depending on size (although this seems to be more for aesthetics than practicality). 

This section also addressed how inputting data and creating the map will look. I learned about using a subset of features. This is useful when you want to be able to separate different features on a map. Although I learned more about subsets and when to use them/what to use them for, I think I am still a little confused on what they actually are. But, as I read on, I did understand how mapping by category can be more logical than mapping with subsets. Mapping by category makes different features distinguishable.

Displaying features by type is a productive way to display large amounts of data. It allows you to combine a lot of data onto one map in a way that is not cluttered. It also offers an option to make multiple maps in order to separate large amounts of data. Another way to simplify the data is to group categories together. The text provided multiple ways in which to group categories effectively. Of course, it notes that a con of this is that important information can be lost. In this case, if it is really important, you could just split the categories up onto multiple maps.

Lastly, this chapter describes how to interpret geographic data patterns. The 3 types of patterns were clusters, uniform, and random. Looking at geographic patterns is useful when observing maps in order to understand why a community works a certain way or when planning a visit. 

Ch. 3

This chapter addressed mapping quantities and the different ways that can be useful. When using quantitative data and summarizing by area, ratios should be used so that the distribution of the data is accurately represented. The text mentioned the most common ways to find ratios in GIS: averages, proportions, and densities. It talked about when each of these are useful and how to calculate them. 

Ranks is another feature that was addressed. Ranks put things in order and don’t show exact values, but values in relation to each other. This is useful when the feature you’re using is hard to get an exact measure on or if it takes multiple data factors into account. I learned why it is wise to group values together because if you didn’t, the map would be confusing and would not convey any valuable information.

Classes should be used when comparing data to a specific value or trying to see which data meets a certain criteria. Classes allow you to group data based on your needs and what you are trying to gain/understand. 

A new topic to me, standard classification schemes, was introduced in this chapter. These are valuable when looking for patterns in your data. There are four common schemes. Natural breaks is one where classes are broken up by the natural grouping of the data values. There can be an uneven number of features in each group using this method. Another common grouping, quantile, contains an equal number of features in each group. The next scheme was equal interval. The way I understand it is that the max and min of each interval are the same distance apart. I am not sure if this is completely correct though. The last one is standard deviation. This one, I am familiar with. This organized features based on how far their value is away from the mean. The text then went into depth about these and when to use each as well as combating problems that may arise.

This chapter was long, so it covered quite a bit more material throughout the rest of the chapter. This included how to choose, use, interpret, and find patterns in different map types. I anticipate this information to be extremely helpful once we start to create our own maps.