Author: ecdahlstrom

Preface

Based on the preface, it seems like this book will walk us through how to use ArcGIS Pro step by step. Additionally, we will also learn methods in ArcGIS online, ArcGIS StoryMaps, and other ArcGIS software. Specifically with ArcGIS Pro, it will be teaching us how to use the GIS application to create, use, and analyze professional 2D and 3D maps. The goal of reading this book is to learn how to effectively use GIS to integrate it into and address real-world problems. I appreciate the layout of the chapters since it first explains the concepts and then allows you to do the tutorial hands on. After reading this book, I hope to have enough knowledge of GIS to use it in potential research and possibly my future career.

Chapter 1

Chapter 1 served as an introductory course on how to use a variety of basic navigations and tools in GIS. One of the most fundamental tools introduced in this chapter was the use of the contents page. The contents page allows you to add and remove different features or layer classes and is, as I learned later, an important hub for editing for features. Some map making features that were introduced in this chapter include how to add basemaps, how to change symbols, and how to add, remove, and label feature classes. I also learned all about map viewing and zooming. Knowing how to zoom in and out, change the viewing zone, zoom into specific features, create bookmarks, zoom to full extent, and search for specific features will all be useful tools for analyzing maps in the future. I also learned how to export a layout and turn the map into an image with a photo viewer. This skill is useful when I need to share my map and make it accessible to other people. Overall, I liked how the chapter gives you straight forward instructions on how to find and do things so it is easy to navigate. Throughout the chapter, I definitely started to realize that I remembered how to work and locate different features in GIS. However, I found the tutorials a little bit repetitive, as you often do a skill and then delete the work to reset.

Key Concepts/Definitions

Feature Class: Basic building block for displaying geographic features on a map. A homogeneous layer on the map. Vector data that have corresponding attributes for each feature.

Raster: Type of spatial data. An image made up of small pixels. A raster encoded with geographic information can be used as a layer in a map.

Chapter 2

In this chapter, I learned all about how to create, design, and symbolize thematic maps. I was first introduced to symbology, or the visual elements to represent geographic features or attributes. From this, I was able to learn how to change the colors of polygons, symbolize ground features, and make graduated and proportional symbols. Symbology was a very important learning concept throughout this chapter. After these tutorials, I now feel comfortable with implementing symbol changes and where to go to do so. I was also introduced to the process of making two different types of thematic maps: choropleth and dot density. I enjoyed these types of maps because it was easy to see how the values were distributed. I also think that while the 3D choropleth map is not a necessity, it adds another element that helps display features. Additionally, while making these maps, I learned how GIS creates histograms based on the data and how they can be altered. This skill will be useful to know when analyzing the map through statistical analysis. Other important skills I learned in this chapter included how to label features, remove duplicate layers, remove pop ups for features, set visibility ranges, and how to create a definition query.

Key Concepts/Definitions

Thematic Map: Strives to solve or investigate a problem. Consists of a subject layer or layers placed in spatial context with other layers. To make this map you must answer: What layer or layers are needed to represent a subject? What spatial context layers are needed to orient map users to recognize locations and patterns of the subject feature?

Definition Query: Used to filter the features of a layer rather than select a temporary subset of features to work with.

Choropleth Map: Uses colors in polygons to represent numeric attribute values. Uses classification methods, that depend on the data and intent of the map, to display the data.

Map Scale: Ratio between distance A and B (one inch) on your computer screen divided by the distance between the two same points in inches on the ground.

Chapter 3

This chapter was all about making suitable maps to present and how to share your maps with people beyond ArcGIS Pro. The first section of this chapter was how to make a layout. Layouts are mostly used to share information in formal settings such as presentations or reports. The layout contained the map, a title, and a legend. When making the layout, I especially appreciated the ruler and guideline features of GIS. These features ensured the maps were even and gave them a professional look. From these layouts, I learned how to create different charts from the maps and how to highlight certain subsets of features from the charts. For example, in one of the tutorials I highlighted the top ten states with the highest arts employment. 

The rest of the chapter focuses on the online sections of ArcGIS. I first learned how to publish a map I made on ArcGIS Pro to ArcGIS Online. Publishing to ArcGIS Online is extremely useful in sharing your map with a wider audience since it is more accessible than a desktop and ArcGIS Pro. I then received a tutorial on how to create a story through StoryMaps that showcases the data and reason behind a map. To me, StoryMaps would be the most useful for sharing with the general public because the story provides context and instructions on the meaning of the map. I particularly enjoyed the inclusion of accessibility features and sidecar blocks in StoryMaps. These features made the story easy to navigate and further expanded the range of audience. I then learned how to create a briefing. The information was similar to the story section, but formatted the information in a way that would be useful for a presentation. Lastly, I was introduced to the concept of creating a dashboard. Dashboards are useful tools for allocating resources in response to changing goods or services over time.

Chapter 4

In this chapter, I learned about another way to map data through GIS called mapping by density. You should map by density when you are looking for patterns of individual features or mapping with areas of different sizes because it allows you to see where features are concentrated. There are two ways of mapping density: by defined area and by density surface. 

You should map by defined area if you want to compare areas with defined borders. Although GIS can calculate the density of each area for you, it is important to ensure all feature units match. Shaded fill maps or dot maps are common ways to display density maps defined by area. If you want to see the concentration of points or line features, however, you should map by density surface. When mapping by density surface, there are several parameters that affect how GIS calculates density surface. Cell size determines how coarse or fine the patterns will appear and search radius affects how generalized the patterns in surface density will be. The two ways GIS can calculate the density are the simple method and the weighted method. Overall, I learned how to efficiently create an effective density map through the use of GIS.

Key Concepts/Definitions

Shaded fill map: Uses a range of colors to display density. Density is treated as a ratio. Density value applies for the entire polygon, the actual density at a specific location may vary.

Dot Density Map: Each dot represents a specified number of locations. The dots are randomly distributed, so they do not represent the actual feature locations. The closer together the dots are, the higher density of features in that area. 

Simple Calculation Method: Counts only the features within the search radius of each cell. Results in a series of rings that overlap each other.

Weighted Calculation Method: Gives more mathematical weight to the features closer to the center of the cell. Every cell in the layer is counted and assigned a value. Results in a smoother, more generalized density surface.

Chapter 5

This chapter introduced me to all of the information I needed to know about mapping what’s inside. This type of mapping is used to monitor what is occurring inside of an area or to compare several areas based on what’s inside each. GIS can find out whether an individual feature is inside an area, list all the features inside an area, find out the number of features in an area, or get a summary of what’s inside a boundary based on a feature attribute.

The three ways of mapping what’s inside include drawing areas and features, selecting features inside of an area, and overlaying the areas and features. When creating these maps, it is important to use symbols, boundaries, labels, and colors to help distinguish or emphasize visual aspects of the map. I have found this detail to be emphasized throughout the book. Although the first two methods seemed pretty straight forward to me, overlaying the areas and features proved to be more complicated. When you are overlaying and have discrete features, you can use the same analysis as in geographical selection or you can summarize by area. When you are overlaying and have continuous features, however, you use the vector or raster model. Additionally, when overlaying you may end up with slivers. To offset them, you should merge them into one of the larger adjacent areas. When analyzing the results of these maps, you should use the summary statistics such as counts, frequency, sum, average, median, or standard deviation.

Key Concepts/Definitions

Drawing Areas and Features: Creates a map showing the boundaries and features. Good for the visual approach of seeing whether one or more features are inside or outside a singular area.

Selecting Features Inside of an Area: Specifies the area and layer containing features. GIS selects a subset of features inside the area. Good for getting a list or summary of features inside a single area and finding what’s in a given distance of a feature.

Overlaying the Areas and Features: GIS combines the area and the features to create a new layer with attributes of both or compares two layers to calculate the summary statistics of each. Good for finding which features are in several areas or how much of something is in one or more areas.

Slivers: Borders that are slightly offset.

Chapter 6

In this chapter, I was introduced to the concept of mapping what’s nearby. This type of mapping was particularly interesting to me because I recognized its use in many different fields. Mapping what’s nearby identifies the area and the features inside that are affected by a certain event and determines if an area is suitable for a specific use. Data in mapping what’s nearby is measured using distance or cost. Cost, also known as travel costs, could be the amount of time, money, or energy expended. Before mapping, you should decide whether the map would be suitable for the planar or geodesic method and if you should use inclusive rings or distinct bands. To map what’s nearby, you can measure a straight line distance, distance or cost over a network, or cost over a surface. When measuring distance with a straight line, there are several methods that can be used such as creating a buffer, selecting features within a distance, distance between feature to feature, and creating a distance surface. Distance or cost over a network consists of the measurement of segments in geographic networks within the travel parameters. Lastly, calculating cost over a geographic surface shows the rate of change in distance or cost from the feature. The method you use depends on the data and how you intend to portray the map. Overall, throughout this book, I learned that many of these different maps have the same principles behind them. Knowing how to properly differentiate each type of map, utilize coloring, identify features or categories, define boundaries, and analyze summary statistics are all factors in creating effective maps in GIS.

Key Concepts/Definitions

Straight-line Distance: Use for defining an area of influence around a feature, creating a boundary, or selecting features within a distance. Measures distance. 

Distance or Cost Over a Network: Use for measuring travel over a fixed infrastructure. Measures distance or travel costs.

Cost Over a Surface: Use for measuring overland travel and calculating how much area is within the travel range. Measures travel costs.

Planar Method: When you are assuming the earth’s surface is flat. Area of interest is relatively small.

Geodesic method: When you take the curvature of earth into account. Area of interest encompasses a large region.

Inclusive rings: Show how the total amount of features increases as the distance increases. Distinct bands: Show the differences between feature amounts and different distances.

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.

Part 1

*I reviewed the course syllabus and schedule to complete the GEOG 291 Quiz.*

Part 2

Hello! My name is Emma Dahlstrom and I am from Lexington, Kentucky. I am a sophomore this year at Ohio Wesleyan University. Currently, I am a declared Environmental Science Major and intend on eventually double majoring in biology or a related field. Although I do not know exactly what I would like to pursue after school, I have always been interested in working in the field of conservation. I am taking GEOG 291 not only for my major, but also because I have heard so much about GIS and was intrigued to learn more about it. Outside of my classes, I am on the university’s softball team and a member of Women In Stem.

Part 3

Originally I thought that GIS was just used in geography related fields and as a form of mapping. However, upon reading this chapter, I learned that its technology was used for so much more. One area that stood out to me particularly was how heavily it impacts agriculture. Coming from an agricultural based community, it was interesting to learn about all the ways GIS impacts its businesses. I was also surprised to learn that GIS was used in medical settings, planning cities, regulating commerce, e-governance, and so much more.

I also found it interesting the GIS had an identity problem. I was unaware that there are two sides to GIS: the “where”  spatial entities are and the “how” we encode spatial entities and the repercussions of different methods of analysis on answers to geographic questions. This identity problem allowed them to differentiate the important difference of spatial analysis and mapping to me. Spatial analysis is extracting the information from spatial data while mapping represents geographical data in a visual form.

Although I was somewhat familiar with GISystems, I was unaware that there was a second face to GIS called GIScience. I learned that GIS is now widely considered a “black box” system because it has become so widely established that it is simply assumed to be true and justifications are no longer required. However, GIScience was established to research and question the accuracy and underlying assumptions of these systems. This established the point that when using GIS, you must responsibly analyze the data to reach an accurate conclusion.  

Lastly, I found that the ability of GIS to visualize spatial relationships and objects makes interpreting the analytical pattern more accessible. This not only applies to the general public, but also to researchers as well. For example, the chapter details how the visual map of the cholera outbreak in London allowed epidemiologist John Snow to identify the location of the outbreak’s origin. 

Overall, this chapter introduced me to the history of GIS and the vast amount of fields and problems that it impacts in our everyday lives.

Part 4

Source 1:

Owusu‐Sekyere, Adriana, and George Ashiagbor. “Mapping the Paths of Giants: A GIS‐Based Habitat Connectivity Model for Forest Elephant Conservation in a West African Forest Block.” African Journal of Ecology [HOBOKEN], vol. 63, no. 2, no. 70028, Mar. 2025, https://doi.org/10.1111/aje.70028.

The Bia Goaso Forest Block in Ghana is home to a vital population of African forest elephants. Historically, the elephants had more extensive ranges and moved across a broader landscape. However, in recent years the population has been isolated which could cause several biological issues for the species. Through the use of a GIS-based habitat connectivity model, scientists were able to find a strong solution that enables the integration of landscape and ecological data on elephant habitat selection and movement. This map shows the variables influencing the choice of movement for the forest elephants based on proximity to water, land use, elevation, proximity to roads, slope, proximity to community, and terrain ruggedness. In addition, it details a variety of locations in the forest block that are suitable and unsuitable for forest elephants. By taking all of the variables into account and eliminating the unsuitable habitats for elephants, scientists were able to identify core channels and areas for elephant movement. This allows for the protection and maintenance of those pivotal areas for the conservation of the elephant species.

Source 2:

Kucsicsa, Gheorghe, and Cristina Dumitrică. “Spatial Modelling of Deforestation in Romanian Carpathian Mountains Using GIS and Logistic Regression.” Journal of Mountain Science [Heidelberg], vol. 16, no. 5, May 2019, pp. 1005–22, https://doi.org/10.1007/s11629-018-5053-8.

This study focused on the Carpathian Mountains which is an area of land that is heavily affected by forest loss. The goal of the study was to examine and analyze the various variables of deforestation in the area and to model the probability of deforestation through the use of GIS. This map displays the difference in forest coverage between 1990 and 2012. In the combined map, the persistent forest coverage stayed green, while the areas affected by deforestation were represented by red. This provides a clear visual of the affected areas. The map also sections off the area into four parts. This displays which parts of the mountains were being most affected by deforestation. By doing this, the scientists were able to identify the variables and their significance in the area. Understanding the driving forces of deforestation in affected areas allows conservationists to adopt appropriate policies and decisions in forest management and conservation.