Month: September 2026

Chapter 1

     Spatial Data has grown tremendously outside of the scientific world, becoming available to many other sources. GIS answers questions about why things are done the way they are and how they are related. There are two ways to evaluate spatial data, depending on the question being asked and how the information will be used. The first method contains the bigger-picture kind of information and is quicker to access, and the other kinds of methods require more digging and time to process the more specific information. The information found is typically present in many different ways, like tables, maps, etc. Depending on how information is presented, the data is either valid or useful, or it will say that more digging is needed.​

      To use GIS effectively, users should understand the types of geographic features represented in the software. Features on a map can be described as discrete, continuous, or summarized phenomena. Discrete features, such as specific locations, are depicted as lines or dots depending on the settings. Continuous phenomena, like weather patterns such as precipitation and temperature, are measured through equally spaced data points with no visible gaps. GIS software applies a process called interpolation to assign values to areas between these points. Continuous data can also be represented by enclosed boundaries (such as those showing soil or vegetation types), which are used to illustrate large, uniform areas of the landscape. However, these boundaries are not as definitive as discrete features. Features summarized by area primarily indicate the density within a specific boundary—for example, the number of businesses in a zip code or the number of houses within a certain radius.

      Geographic features are shown through two different models, vector and raster. In a vector model, features are displayed in a table and buildings are represented as x,y locations connected with dashed lines. Raster models are presented as a matrix of cells by layer. Each layer is a specific attribute. Cell size is vital to an accurate map because if the size isn’t perfect, then information is lost. 

     There are five different types of attribute levels. These are types of attributes that determine how each feature is analyzed determines what level to use.

Different levels of attributes:

1. 1.  Categories – Groups of different features that are alike in some way and are represented in code or numbers.
   2.  Ranks – Features are put in order from highest to lowest and used when features are hard to distinguish
   3.  Counts – The count is the actual number of features on a map
   4.   Amounts –  The quantity connected to a feature
   5.  Ratios – Comparing two quantities by dividing one by the other

 

Chapter 2

 

     Chapter 2 focuses primarily on how and why features are placed where they are placed. Viewing a map now is much clearer to me because chapter helps me understand how to find patterns throughout a map. The map features are always determined based on how the information is presented and how the map is used. For instance, the police department tracks where crimes are committed and what types using GIS to better monitor high crime areas each month.  Prior to placing features on a map, all features included will have geographic coordinates as longitude and latitude values and be identified as a type (must fall into a category). Mapping can occur as a single type because GIS will use the same kind of symbol and suggest that this map can be explored further. As features are added, GIS will use the applied coordinates to create lines or areas to define shapes for specific areas or smaller / single features will be drawn as a symbol defined by coordinates. Instead of laying all of the features in one layer, smaller patterns can be revealed by creating a subset which can only be represented in an underlying layer instead of just one big layer.

     When one map has a multitude of categories, it is suggested that groups are created to sort the categories into smaller sets of data.

Option 1: Assign each record 2 database codes. One for detailed category and the second for  its general category

Option 2: Create a table containing one record for each category corresponding to its general code. Once the map is ready to be displayed, the table and map will be linked together showing general codes with the features. 

Option 3: Assigning categories by specifying the correlated symbol to go with it. Mostly used for single locations

Chapter 3

     Mapping areas with the highest and lowest concentrations of specific variables is invaluable for businesses in strategic planning and market analysis. For instance, when a physician’s office considers expansion, mapping the ratio of people per existing office per mile can highlight underserved regions. This helps ensure a new location addresses real gaps in access, which increases the likelihood of success and optimizes resource allocation.   

     Understanding the three types of map features—discrete, continuous, and summarized—enhances how landscapes and demographic data are visualized. Discrete features pinpoint specific locations or boundaries, continuous features represent gradients like population density, and summarized features aggregate information over defined areas.

     Standard classification schemes are essential tools in GIS for grouping similar data points, revealing underlying patterns, and making complex data more interpretable. These schemes rely on how the data are distributed. When data points are evenly distributed, classifications such as equal intervals or quantiles can be used for clear, balanced mapping. Charts and histograms help visualize this distribution. If the data have natural groupings or outliers, methods like natural breaks (Jenks optimization) are preferable, as they better reflect the true structure of the data.

     Using GIS becomes more straightforward when data is evenly distributed, as outliers and skewed distributions can complicate analysis and visualization. Careful selection of classification methods ensures more accurate, meaningful maps that support better business decisions.

     There are five ways to show quantities using GIS software: 

1. 1. Graduated symbols – includes locations, lines and areas and is best used for minimal featured maps
   2. Graduated colors – includes areas and continuous phenomena and makes patterns easy to read
   3. Charts – Used for specific locations within an area to show categories and quantities
   4. Contours – Used to represent rate of change across large parts of area
   5. D perspective views – Adds visual impacts throughout the map

Chapter 1

 

Maps come in many forms, think of paper maps that show minimal information such as roads and towns.  GIS maps have spatial pictures and can be created to show in depth information.  Chapter 1 is about advance mapping where you can find patterns, trends and work towards solving problems. 

Some key terms I found interesting listed below.

 

Map Features: GIS uses three main shapes to draw everything.  Points, which are tiny dots for certain locations.  Lines, connected paths such as pathways and roads.  Polygons, shapes with boundaries that outline an area such as a county.

 

Discrete Data, has clear edges like property lines.

 

Continuous Data, flows across space with out hard borders such as temperature

 

It is amazing that almost everything can be mapped.  How can you protect private information from becoming part of this system?  I wonder if people can use this tool to commit crimes?

 

Chapter 2

 

This chapter involves plotting locations  and spotting groups clustered together.

Mapping where things are located.

 

Single Symbol Mapping, giving every single item the same icon and color

 

Clusters, tight bunches of dots

 

Outliers, lone dots far away from everything else

 

If you are going to map everything your map could look messy. Map scale has to be right so that your information can be interpreted.  Are there sources to help pick the best map scale?

 

Chapter 3

 

Talks about mapping numbers and the importance of calculating them correctly before putting them on your map.  You do not want incorrect information available to interested parties.

 

Data grouping,  how you split up numbers into groups before picking colors

 

Normalization, fixing raw counts so a fair comparison can be made.

 

Choropleth Map, classic shaded map where areas are colored lighter or darker based on their numbers

 

So you should never map raw totals for large regions. You need to make sure detail is incorporated or your map will just show basic information.

 

How do you choose color shades?

Mitchell, chp. 1,

Andy Mitchell describes GIS as “a process for looking at geographic patterns in your data and at relationships between features.” (Andy Mitchell, 2020, pg 3). This description of GIS narrows down the broad field of GIS mapping into an understandable description of how GIS analysts collect data and record patterns to create a multilayered model of recorded data. As described in the textbook, collecting this data is similar to the typical scientific method. This process consists of asking a question, understanding your data, choosing a method, processing the data, and analyzing results of the process. In GIS, there are continuous phenomena, which are continuous data that starts as sample points. GIS analysts then assign values to the area between these sample points. This process is known as interpolation. This process is crucial for collecting precise measurements and recording data of an area over time. It is crucial to note that you can also treat some noncontinuous data as continuous to create maps that highlight how quantities may vary across a given location. This process helps fill data gaps from unmeasured areas and simplifies complex, intricate data. 

Additionally, GIS utilizes map projections and coordinate systems to ensure accurate results when combining data layers. “A map projection translates locations on the globe (which is almost a sphere) onto the flat surface of your map. All map projections distort the shapes of the features being displayed, as well as measurements of area, distance, and direction.” (Andy Mitchell, 2020, pg 13). The quotation explains that a 3D sphere is translated onto a 2D map, and this process distorts the features to compensate for the dimensional change. This is one of the main complexities in GIS and topography: changing the 3-dimensional measurements into a tangible 2-dimensional mapping system.

 

Mitchell, Chp. 2,

The second chapter varies from the first by describing the processes of mapping, where things are in relation to their location on maps. You must first ask what information you need and how you will use the map. After concluding the intent and required data, you must prepare your data, such as coordinates and assigned category values. The category values portion of the data is crucial to assign features to a correlated code in order to categorize them. I found this portion of the reading fascinating due to how you categorize the data by hierarchical types and subtypes in order to create organization within the masses of data to maximize simplicity and efficiency. After you have prepared and organized the data, you can begin actually creating your map. You can map all single features or subset features in order to create more intricate data that reveals patterns that are not always apparent with just single features. The GIS system’s role in this process is to store the location of each feature as a set of coordinates or pairs. Various unique symbols are used to pinpoint the locations of the features that you input. The textbook expresses that you typically want to include 7 or less categories because more than this can create difficulty in seeing the patterns. You can have more than 7 categories in your map however, you want to group the categories into each other to make them easier to identify. In order for your map to be meaningful, you want to utilize recognizable features such as landmarks like highways, towns, rivers, etc. You can also use reference features specific to your map and analysis to observe the relationships in the data. An example of reference features could be if you’re mapping the growth of a fast-food chain, you could map the nearby competitors that contribute to fluctuations in data and have geographic relationships.

 

Mitchell, Chp. 3,

The third chapter expresses the importance of grouping the map data based on quantities and mapping the most and least. Mitchell, Chp. 3 explains this by saying, “Mapping features based on quantities adds an additional level of information beyond simply mapping the locations of features. For example, mapping the locations of businesses gives a sense of where workers are, information that might be useful for a transportation planner. But mapping the businesses based on the number of employees at each business gives a much better picture of where employees are.” (Andy Mitchell, 2020, pg 52). After reading this chapter, this description and example helped me understand the different utilizations of mapping locations and features like I described previously, and mapping quantities in order to add additional information and create a more organized map. The example that Mitchell used highlights how the locations of employees can be extremely useful for certain data, but the quantifiable number of employees at each individual location paints a much better picture of where each employee is across the different locations. The quantities that you are mapping (most and least) can be categorized in counts and amounts, ranks, and ratios. Counts and amounts display the total value of each feature and its extent in comparison to other features being recorded. It is important to note that counts are used for the actual number of features, whereas amounts are used for describing the total value associated with the features. Ratios, however, show the relationship between various quantities that are collected by dividing one by the other to collect ratios like proportions and averages. Rank ‌these features in order in terms of highest to lowest of the recorded data. An example of a rank: maybe if you’re collecting data on thriving tree species in an area, you would rank the strongest trees at the top of the rank and the weakest at the bottom. These 3 forms of data organization help to sort‌ large quantities of data into understandable and observable sections.

Sources:

• “Andy Mitchell’s, May 26, 2020, Esri Guide to GIS Analysis, Volume 1, Second Edition (Chp.1, pg.3), (Chp.1, pg. 13), (Chp.3, pg. 52)

Chapter 1-

Some key concepts from this chapter include what GIS is, geographic features, and geographic attributes. 

Definitions:

GIS analysis- Geographic Information System analysis is a process of looking at data to find relationships, patterns, and the features of the data. 

Geographic Features- The type of feature affects the steps of the analysis process; the three types are discrete, continuous phenomena, and summarized by area. 

Geographic attributes- A way to identify what the geographic feature is by describing it, or representing some magnitude from the feature. 

Comments/Notes on the chapter-

One of the first steps to GIS analysis is framing the question. This is to find what information you need, how it will be used, and who it is for. The second step of GIS analysis is to understand your data and to choose a method of getting information. There are 2-3 types of ways to get information: fast with approximate information, and other types that take longer but have more precise results. Once you have picked a model, the next step is to process the data and look at the results.  There are different types of geographic features. Discrete features are locations and lines; they are either shown or not. Continuous phenomena start out as a series of sample points; on the map there will be no gaps. Continuous data can also be enclosed by boundaries; the boundaries indicate where things are more similar than not. Summarized data represents the counts or densities of individual features within a boundary.  There are two ways of representing data, vector and raster. The vector model is shown as points, sets of coordinates, or enclosed areas. When working with data this way, the analysis involves working with the attributes in the layers data table. The raster model is represented as a matrix of cells in a continuous space. The analysis of raster data involves combining layers of data to create new layers with new cell values. Discrete and summarized data are normally represented by vector models. Continuous categories are represented by either, while continuous numerical data is normally represented by raster models.  There are five geographic attributes: categories, ranks, counts, amounts, and ratios. Categories are a group of similar things, while ranks are putting things into an order from high to low. Counts and amounts show you a total number, a count is the actual number of features on the map and amounts are any measurable quantity with a feature. Ratios show the relationship between two quantities. 

Chapter 2-

Comments/Notes on this chapter-

Maps are a big part of GIS analysis. When looking at the distribution of features on a map you can see patterns that help people understand the area and where action is needed. When deciding what to map you have to look for geographic patterns in your data set. The information from the map depends on what you want to know, whether that’s where cops need to be stationed due to crimes or where a new store should be built depending on where customers are.  

When creating the map you want the features to have geographic coordinates and a category attribute for each value. The categories on the map can have subtypes. When making the map you can tell the GIS which features to display and what symbols for each feature. The GIS can store the location of each feature as a pair of geographic coordinates or a set of pairs to define its shape, line, or point. When mapping a category, you can map the subsets as different colors for individual locations to show relationships between the areas. If patterns are complex, you can create separate maps for each category, to see the patterns easier. When mapping roads, you can have different types of roads as different line thickness to help differentiate between highways and backroads for example. When displaying categories, you don’t want more than seven categories; however depending on the scale of the map you could need more categories than seven to show a pattern. When using a large scale, more than seven categories can make the pattern hard to see. When grouping categories, you want to group similar things alike, and to help distinguish the pattern. Depending on how you group things can change how readers perceive the information. The base of the map should include landmarks, and should be a simple monochrome color to not distract from the data you want to show. 

Chapter 3-

In this chapter it discusses how to best compare places, and understand relationships by using maps. When mapping it depends on what type of features you want to map. When looking for relationships or patterns in the data, it is helpful to look at the data in high and low detail and look at different ways to display it. This can help you find patterns easier, and distinguish when it is harder for the intended audience to see the pattern or relationship. When mapping you want to know what type of quantities you are mapping to display the data the best. When mapping with counts or amounts, you can map ratios to help represent the distribution of features. Ranks are useful when direct measures of data are hard to make, or if the quantity represents a combination of different factors. When mapping the determined quantities, you have to decide to assign each its own value or group them together into a class. When using classes you assign them the same symbol on the map, and define the range by determining which features fall into each class. When grouping data there are a few different ways, natural breaks, quantile, equal intervals, and standard deviation. Each grouping way shows different patterns in the data, so depending on what relationship you want to display. Each grouping also has its own advantages and disadvantages. There are also different classification schemes to know when mapping. There are ways to make the classes easier to when, for example making the legend easier to understand. 

Key words/ definitions

Quantities- Quantities can be counts or amounts, ratios, or ranks. 

Counts- The actual number of each feature on the map.

Amounts- The total of a value that is associated with each feature. 

Ratios- Ratios show the relationship between two quantities and are created by dividing one quantity by another quantity. 

Ranks- Ranks put features in order from high to low and show relative values. 

 

 

Chapter 1– I learned about concepts and how to correctly read and identify locations and lines for example…

Businesses, symbolized by the number of employees, are an example of individual locations. Streams are linear features. Parcels, color-coded by land value, are an example of discrete areas.

 

Some new things I learned that I think are really important to remember are… Continuous phenomena such as precipitation or temperature can be found or measured anywhere. EX.) Temperature, precipitation, and elevation are examples. For instance, elevation changes continuously as you move across the landscape rather than existing at only one point. 

Also Continuous data which are areas enclosed by boundaries. Summarize data, which counts individual features within boundaries.

The book then discussed the process of overlaying boundaries and businesses to be able to get a sense of how many business locations are within certain zip codes. 

 

Is cell size referring to pixel size? Also having a hard time understanding the concept of a raster and vector, although I can clearly see the difference within the quality of the map. 

What is a tract??

 

Other terms to keep in mind: 

Categories– Groups of similar things, helps organize data. 

 

Ranks– Feasturers in order from highest to lowest

 

Counts and Amounts– Count is the total number of features in a map and amount is the measurable quantity of that feature. EX.) how many employees at a business. 

Ratios– Relationship between 2 quantities and are created by dividing one feather by another for each feature.  

 

Continuous and noncontinuous values– Categories and ranks are not continuous values. Counts, amounts and ratios are continuous values. 

 

Polygon/Area: A representation of a feature covering an area, such as a county, lake, parcel, or park.

 

I have just come to the understanding that GIS is very much like a quantitative/stats class that involves coding. 

 

Chapter 2– Goes over why location matters, deciding what to map, preparing the data, creating the map, and analyzing the patterns that appear.

Mapping where things are can help people make decisions. Someone could map crimes to see where certain crimes occur so they can make a decision on where they might want to move, businesses to see consumer patterns, or environmental features to understand where habitats or populations are located. We need to figure out what we need to actually map.  We might not have to map every feature. Categories describe different types of features. 

EX.), crimes could be separated into assaults, burglaries, thefts, and auto thefts. Displaying too many categories on one map can make the map difficult to understand. It is recommended keeping a single map to around seven less categories to avoid confusion. 

We have to learn how to symbolize the features. Different symbols and colors can represent different categories. The symbols should make the map reading and  patterns easy to understand. Features might be clustered in certain areas, spread evenly throughout an area, we can  compare categories to determine whether different types of features seem to occur near each other.

Distribution- The way geographic features are arranged across an area.

Geographic pattern- A recognizable spatial arrangement of features.

Category- A group of features that share the same characteristic or type.

Categorical data- Information that places features into named groups instead of measuring an amount.

Symbol-A visual representation of a geographic feature on a map.

Symbology- The system of colors, shapes, lines, and other symbols used to represent map features.

Map scale- The relationship between distance on a map and distance in the real world.

Coordinate pair- Two coordinate values used together to identify a geographic location.

Data preparation-Organizing and checking geographic information before performing GIS analysis.

Attribute table- A table containing descriptive information associated with mapped features.

Cluster- A group of features located relatively close together.

Spatial distribution-The arrangement of features across geographic space.

I need to figure out the definition and concept of a parcel.

 

Chapter 3– Instead of only showing the location or category of a feature, GIS can represent the quantity of a feature. This makes it possible to compare places. EX.) Instead of only mapping businesses, you could show the number of employees at each business. Quantities can include counts/ amounts, ratios, and ranks. A count might be the total number of people living in a county. A ratio compares one quantity with another. Population density, for example, compares population with land area. A rank puts features/categories in an ordered position based on their values.

Again showing every individual value may make the map too complicated. Instead, GIS can group values into ranges called classes. EX.)Counties could be divided into groups representing the range of low, medium, and high populations.

Natural breaks looks for natural groupings and gaps in the dataset and places class boundaries around those groups. It is useful when values are unevenly distributed. Standard deviation groups features according to how far their values are above or below the dataset’s mean. Outliers are another important issue. An outlier is a value that is extremely high or low compared with the other values.

There are also several ways of visually showing quantities EX.) graduated symbols, graduated colors, charts, contours, and 3D perspective views. Graduated symbols change size according to magnitude, while graduated colors use differences in shading to represent value ranges. Contours for continuous phenomena. 

Quantity- A numerical amount associated with a geographic feature.

Class– A range of numerical values grouped together for mapping.

Classification- The process of dividing numerical data into classes.

Class break- The numerical boundary separating one class from another.

Natural breaks – A classification method that creates classes based on natural groupings and gaps in the values.

Quantile– A classification method that places approximately the same number of features into each class.

Equal interval– A classification method that divides the total range into classes of equal numerical size.

Mean- The average value of a dataset.

Standard deviation– A measurement describing how far values tend to vary from the mean.

Outlier– An unusually high or low value compared with the rest of the dataset.

Histogram– A graph showing the distribution of numerical values; it can help determine appropriate class breaks.

Graduated symbols– Map symbols that increase or decrease in size according to the quantity being represented.

Graduated colors- Colors or shades that change according to different ranges of values.

Contour– A line connecting locations having the same value, such as equal elevation.

Data distribution- The way numerical values are spread throughout a dataset.

Magnitude- The size or amount of a value.

I completed the GEOG 291 quiz.

My name is Kylie Redman. I am a junior from Richwood, OH studying Zoology. I took this class to gain a better understanding of GIS and its purpose. I think that taking this class will help me to gain a better understanding of conservation and how I can have an impact in my career of working with animals.

Before I read this chapter, I did not know how widespread GIS was or that it was of any significance. I thought that it was just a map. I now know that in addition to being a map, it also involves the analysis of maps, and includes many different uses. 

One surprising thing about GIS is that the topic struggles to have a distinct identity with just one use, as it can be used in two completely different ways. The first way that GIS can be used is as a software tool. Municipalities and local government organizations use GIS mainly as a software program. It is used to map out exact lines of properties and urban zones, organize databases, and analyze the effect of building a road along a new route. In a more scientific approach, researchers, scientists, and university professors use GIS to solve complex theoretical equations. This can include drawing clear boundaries on maps, and the tracking of disease spread. The Author makes it a point to make a distinction between mapping versus spatial analysis in GIS. Simple mapping displays spatial geographic data, while spatial analysis involves using multiple data layers to develop new information that is not shown on a regular map.

This chapter reviews the history of GIS in the development from basic computer maps to the modern spatial analysis tool. The history section includes landscape architect Ian McHarg, who invented the technique for map layers to route highways. Early computer Cartography, and pioneering systems were also involved in the history of GIS.

In the latter part of this chapter, challenges are discussed. In order to add geographic features into a computer, there needs to be sharp boundary lines, which can be difficult as many borders of cities and towns do not have distinct boundaries. Date models, categorization, visualization, and scale were also shown to be challenges.

In all, GIS is so much more than just a tool to navigate to a new city. GIS is very important for spatial analysis to solve complex problems.

Application 1: highways cutting through habitats of animals frequently result in heightened animal mortality rates. To address this rising issue,  researchers used GIS to integrate tracking data from bears, bobcats, fishers(small mammal) to design a road system that involves strategically places underpasses and overpasses to reduce animal fatality.

Application 2: When creating nature reserves, standard borders often fail to cover the full areas where endangered plants and animals actually live. To fix this, conservation scientists use GIS to combine field sightings with environmental data like climate, terrain, and soil type. GIS combines all of these to map habits of all three species to help scientists protect wildlife while also benefiting land needs for people.

T

These maps show the calculated minimum cost-distance habitat linkages for a) black bear, b) bobcat, and c) fisher. the three images were merged to form the functional habitat linkage (image 4)

 

Source: Geo Contributor. (2024, August 12). How GIS is Being Used in Conservation Biology. Geography Realm.

 

Chapter one

GIS can be used for more purposes than building geodatabases and making maps. Most notably, it can be used to address pressing issues and world problems. GIS is used to look at geographic information/patterns in data and address relationships between features. The features can be quite simple, and they can also be quite complex. To begin, you must start with an analysis; to do this, you need to figure out the information needed. It is important to be as specific as possible with your question. Next, you must understand the data to be able to decide the method you use. Once you have your method, you can process the data to then be able to interpret it.

Discrete features: have locations and lines, and the actual location can be pinpointed at any given spot.
Continuous phenomena: precipitation or temperature that can be found or measured anywhere. This will blanket the whole area that we are mapping.
Continuous data: often begins with sample points that can be regularly or irregularly spaced out. It can also show areas closed in by boundaries if everything inside the boundary is the same.
Features summarized by area: can represent the counts or density of individual features that are in certain boundaries. An example mentioned by the book is the number of businesses in each zip code and the total length of streams in each watershed, and lastly, the number of households in each country.
Categories: groups of similar characteristics/things.
Ranks: ranks features from high to low, mainly used for direct measures when they are difficult or if the quantity represents a combination of factors.
Counts and amounts: a count shows the true number of features on a map. The amount is any quantity associated with a feature that is measurable.
Ratio: shows the relationship between two different quantities.
Continuous and non- continuous values: counts, amounts, and ratios are continuous values.

It seems like you have to be very careful and technical with how you use GIS. One part that I read talked about cell size: if you use a cell size too big, some information can be lost, and if you use a cell size too small, then it takes up too much storage space.

Chapter two

Maps are used to see where and what a certain feature is. If you look at the allotment of features on the map, you can notice patterns that better help you understand the area that is being mapped. GIS can be used to map the location of different features to see if certain features occur in the same place. The book gives examples of businesses mapping customers by age, a police station creating maps based on crimes that vary in type, or seeing if assaults and thefts happen in the same area.
When planning a map, make sure that geographical coordinates are assigned and that each feature has a different category. Each feature needs a code that is unique to that feature. The GIS will store the location of all the features with a pair of geographic coordinates that will define their shape(line or area). Symbols will be assigned to the features as you specify them.
For linear features (streets), the GIS will draw lines to connect the points of interest that define the shape of each street. For areas like land, the GIS will draw the outline, or it will fill them in with a certain color or pattern.
When dealing with a subset of features, it is important to map the features in a data layer. Mapping within subsets is more commonly used with individual locations.
It is important when mapping an area that is large area to have fewer than seven categories. This makes it easier to see patterns. And if there are more than seven categories, then grouping some of the categories will help lessen the initial number.
Freeways are often drawn wider than highways.

Chapter three

Maps show location, but to add more factors to elevate the amount of information that a map shows, you can add different features based on quantities. Some features that can be mapped are: discrete features, continuous phenomena, and data summarized by area.
Quantities can be: amounts, ratios, or ranks.
When summarizing by area, if you use counts or amounts, they can skew the patterns if the areas happen to vary in size
The most common ratios are averages, proportions, and densities
Proportions: show you what part of a whole each quantity represents and are often shown as percentages.
Densities show you where the features are concentrated. (value/area=value per unit of area). Density is used to show distribution for the areas that are being summarized
Ranks put features in order from high to low. Ranks are used to show relative values instead of measured values. Sometimes direct measurements may be hard. Ranks also tend to be mapped as individual values. Also, it is worth noting that you should assign one symbol for each rank. And if you have too many ranks (more than seven), put them into classes.
Classes: Classes are counts, amounts, and ratios grouped. Using classes is helpful when the map is used for public discussion since it makes the viewer able to compare areas more quickly. How you decide to define the class will determine what features fall into each class and what the map will look like.
Individual values: Individual values can present a clear picture of data since the features are not grouped. If you map individual values, then you can search for certain patterns in the raw data, this can help if you are unfamiliar with the data or the area that you are mapping when looking for subtle patterns in the data.
Natural breaks: a classification that finds groups and patterns that are inherent in the data. The values in a class are probable to be similar, and the values between different classes are different.
Equal interval: each class has an equal scope of values (the difference between high and low values is the same for each class).
Standard deviation: “each class is defined by its distance from the mean value of all the features”

Chapter 1

GIS analysis is the process of looking at geographic patterns in your data and at relationships between features. Understanding GIS analysis is important in making accurate decisions about what to expect and how to prepare for future conditions. Throughout this chapter, I was able to learn the steps of performing a GIS analysis and the necessary geographic features and attributes. To start an analysis, you need to form a specific question based on the information you need and how it will be used. Based on the chosen question, you then must choose an analysis method that best fits your data and features. There are three types of features used in GIS: discrete, continuous phenomena, or summarized by the area. Each geographic feature has one or more attributes that help identify it. These types of attribute values include categories, ranks, counts, amounts, and ratios. Features can be represented by two models: vector or raster. After choosing the method, you then must process the data and analyze the results. Analysis is done through summary statistics. The three most common types of summary statistics used in GIS include selecting, calculating, and summarizing. Finally, after the analysis, it is important to decide whether your information is valid and useful or if it is necessary to rerun the analysis. 

Key Concepts/Definitions:

Discrete features: Features with specific locations that are either present or absent at any given point. 

Continuous phenomena: Can be found or measured everywhere. 

Summarized by the area: Represents the counts or density of individual features within area boundaries. 

Vector Model: Each feature is a row in a table and feature shapes are defined by x,y locations. Areas in the vector model are defined by borders and are represented as closed polygons. Discrete, summarized by area, and continuous categories.

Raster Model: Features are represented as a matrix of cells in continuous space. Each layer represents one attribute and most analysis occurs by combining the layers to create new layers with different values. Continuous numeric values.

Selecting Statistics: Select features to work with a subset or assign a new attribute value to just those features.

Calculating Statistics: Calculate the attribute values to assign new values to features such as rank or ratios.

Summarizing Statistics: Summarize the values for specific attributes to get the statistics such as mean or frequency.

Chapter 2

Throughout this course, I learned that GIS’s ability to map where things are is an important visual in solving real world problems. In order to do this however, one must have a deep understanding of GIS analysis and the ability to create a suitable map. In this chapter, I was introduced to a variety of steps and suggestions to convey an appropriate analysis of data through mapping.

When deciding what to map, the information must be appropriate for the audience and the issue being addressed. To prepare your data, each feature in your map needs geographic coordinates. You can also map by type, categorize similar features, or map by subset categories. I was then intrigued to ask when it is most beneficial to divide major categories into subtypes? The chapter later explains that the general rule of mapping is no more than seven categories. However, if the features are dispersed or the map is smaller, your number of categories can vary. Later, the chapter explains when making your map there are several different ways you can display data including single type, subset feature, or by categories. Mainly, what I have gathered about the mapping process is that there is a delicate balance between being too informative and including as much data into the map as possible. The chapter, however, gives several map making tips on grouping categories, choosing appropriate symbols, and mapping reference features to make the process easier. The chapter concluded by introducing several patterns to look for in analysis such as clustered, uniformly spaced, and random distribution.

Key Concepts/Definitions:

Single Type Map: To map features of a single type. Same symbol used for all features. Basic map to reveal patterns. May suggest differences in the features to further explore.

Subset Feature Map: A map of all features in a data layer or subset based on category value. Can reveal patterns that aren’t apparent when mapping all features. Commonly done for individual locations.

Category Map: Maps features by category. Features represented by different symbols for each category value. Provides understanding of how a place functions.

Chapter 3

In this chapter, I was introduced to the features and process of accurately mapping the most and least features. Mapping where the most and least occur is extremely important in visualizing the relationships between places. This type of mapping is based on the quantity associated with each feature. When the data is discrete or continuous, you should map using counts or amounts. When summarizing by area, however, using counts or amounts can skew the patterns so it is useful to use ratios or ranks instead. Since there can be many different values in mapping, mapping by class allows the reader to compare the data more efficiently. The four most common classification schemes are natural breaks, quantile, equal interval, and standard deviation. When choosing a classification scheme, you need to know how the data values are distributed across the range. Creating a bar chart is a helpful way to see that data. If there is an outlier, you need to pay close attention to it as it can heavily skew your data on the map. One of the most useful things I learned throughout the chapter, however, was how to appropriately use graduated symbols, graduated colors, charts, contour lines, and 3D perspective views to map effectively. Having this knowledge on how to map the most and least is crucial in creating an informative and respectable map through GIS analysis.

Key Concepts/Definitions

Counts: Actual number of features on the map.

Amounts: Any measurable quantity associated with a feature.

Ratios: The relationship between two quantities and are created by dividing one quantity by another for each feature. Can display the average, proportion, or density of certain features.

Ranks: Feature in order from high to low. Show relative values rather than measured values.

Class: Features with similar values represented by the same symbol. 

Natural Breaks: Set where there is a jump in values so block groups having similar values are placed into the same class. Unevenly distributed data.

Quantile: Each class contains an equal number of features. Evenly distributed and emphasis on the relative difference between features.

Equal Interval: The difference between high and low values is the same for every class. Evenly distributed and emphasis on the difference between features.

Standard Deviation: Features are placed in classes based on how much their values vary from the mean. Evenly distributed and emphasis on the difference between features.