Month: September 2026

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.