Author: kpsisler

Chapter 7- Digitizing 

The learning goals of this chapter include creating, editing, and deleting polygon features; creating and digitizing point features; using cartography tools to smooth features; working with CAD drawings; and spatially adjusting features. The first tutorial in this chapter introduces moving and rotating existing buildings, adding vertex points, and splitting polygons to edit them to match buildings. When two buildings are drawn as one polygon, the split tool will separate the polygons. The second tutorial is about creating and deleting polygon features. This is important because planners need the open polygons to see the surface and for transportation engineering studies. I created a polygon and deleted 4 polygons. The third tutorial taught me how to use cartography tools. These tools are useful to improve the cartographic quality of polygons. The tool that helps with this is called the smooth polygon tool. Some data has features digitized with a few lines that don’t match the true geography. The smooth polygon tool can help smooth features, which will fix the problem. When smoothing, the smoothing tolerance is important; a lower number gives a more detailed path but will take longer to process. The last tutorial taught me how to transform features. When dealing with computer-aided designs (CAD), the drawings or models aren’t usually in the same units as the GIS software, so this is important to remember. 

Chapter 8: Geocoding

Geocoding is a GIS process that matches locations in data to corresponding fields in existing feature classes. When matching sources to reference data, it is not possible to make exact matches. So there is a fuzzy-matching algorithm that does its best to match the source address to the actual address. The system attempts to use the thought processes and rules that an expert would use to complete the task. This algorithm starts each source with 100 points; each problem encountered when trying to match the source would remove points from the score. If there is more than one candidate, then the candidate with the higher score is chosen for that estimated location. On the off chance that there was a tie between two sources, the GIS software picks one, or the user can choose to have the GIS leave ties alone. The first tutorial in this chapter taught me about geocoding data using ZIP codes, which is a good way to geocode because people normally put the correct ZIP code compared to everything else. I learned how to change the geocode match scores through the geocoding options. I have learned how to rematch addresses and add my own addresses from a point on the map. The last thing I learned in this tutorial was how to use the collect events tool. This tool counted the attendees in each ZIP code and applied a symbol to each ZIP code based on the number. The second tutorial is about geocoding with street addresses. I used the create locator tool again in this tutorial to geocode attendee data by street addresses. I reorganized the fields in my attribute table to compare specific values in the data. 

Chapter 9: Spatial Analysis

This chapter focuses on spatial analysis. Sometimes the map won’t have all the data for users to answer questions and solve problems. There are different types of analytical methods that may be needed to answer the questions and solve the problems. These methods are buffers, service areas, facility location models, and clustering. This chapter introduced a new spatial data type, the network dataset. A network dataset is used for estimating travel distance or time on a street network. Tutorial 1 explained what a buffer is and how to specify a buffer’s radius using the buffer tool. This tutorial had me find the buffer zones around swimming pools; this was to determine how many kids are most likely to use the pool. The second tutorial was about creating multiple ring buffers. The third tutorial was about creating multiple ring service areas, calibrated with a gravity model. I followed along with the instructions to create a buffer zone around each open pool on how long it would take to get there. I was able to create the attribute table with the estimated number of pool tags in each area. The fourth tutorial was about using the network analysis tool to locate facilities and determine which ones to keep open. This was determined by maximizing attendance between the pools and creating a map that showed the relationship between pools and block centroids. The fifth tutorial taught me how to perform data cluster analysis. The tool that was used in this tutorial was the multivariate clustering tool. This tool helped create clusters of the data based on gender, age, and the crime committed. From the data, I was able to see a table of information to see the data more easily compared to the map. 

Chapter 4:

The first tutorial for this chapter focused on importing data into your project. This taught me how to import data from external sources, such as the free websites mentioned in the book. When importing data, you have to know how it’s stored; if it is a Microsoft Excel workbook, it needs to be saved as a .csv file to properly import it. Using the GIS software, you can create your own databases. The second tutorial was about modifying the attribute table; this helps you display what you want to the user more easily. From this tutorial, I learned how to join tables together to display wanted information. When joining tables, if you don’t export the data table, then the change won’t be permanent. The third tutorial was about linking tabular data to the spatial feature classes. This allows the map to have symbols based on the values found in the data. There are different types of attribute queries. The different types are what and when; for example, what type of crime and the date it happened on. The second type is a refinement of when; this would be weekday vs. weekend or morning vs. afternoon. The third attribute query would be who or what; who did the crime or what was the crime are examples of this. The third tutorial really solidified how to do each type of attribute query. The fourth tutorial was counting the burglaries by neighborhood. The fifth tutorial was creating a central point for each area/polygon. The last tutorial in chapter 4 taught me how to make a table for many things; this helps a user understand what the numbers mean and how to interpret the data. 

Chapter 5:

Location is very important; when working with data, it is important to know the latitude and longitude coordinates corresponding to the precise location. These coordinates can tell us whether or not something is by a river, in a certain area, or even reachable. This chapter focused on spatial data. The first tutorial in this chapter taught me how to change the coordinate system for the map that you are creating. The second tutorial taught me to work with projected coordinate systems. The third tutorial followed the second with more projected coordinate systems. This one had me add a new layer to set a map’s coordinate system. I was able to change the map’s coordinate system for a specific layer in the data. The fourth tutorial reviews file formats that are commonly found with vector spatial data. The tutorial also covers how to import a shapefile, which is a different format that spatial data suppliers use because it’s simple. A shapefile consists of at least three files, which include .shp, .dbf, and .shx. The tutorial taught me how to import and change the coordinates because the imported data might not match the coordinate system of the map. The fifth tutorial was about working with US census map layers and data tables. A good website to get data would be the Census Bureau’s website. I downloaded the TIGER and tabular data, then refined it to be more useful. From this refined data, I followed the tutorial to create a choropleth map. The last tutorial for this chapter was about extracting raster features for a specific county. I did find this tutorial a little difficult to follow compared to the other ones. 

Chapter 6:

Geoprocessing is a framework and set of tools for processing geographic data; these tools are used to build areas of study and perform tasks. This chapter taught me how to extract a subset of spatial features from a map using spatial queries. The first tutorial was about dissolving features to create neighborhoods. The tool we used in this tutorial was the pairwise dissolve tool. This tool takes data, a dissolve field, fields, and statistic type to dissolve block groups to create neighborhoods. The second tutorial was about extracting and clipping features of an area to study them. The tool used in this tutorial was Clip; this tool clips streets to study the area. The third tutorial taught me how to merge two or more layers into a single layer. The tool used in this tutorial was the merge tool; it was used to create a single water feature from 5 different water features. The fourth tutorial taught me how to use the append tool, which added features to an existing feature class. The fifth tutorial used the pairwise intersect tool, this tool creates a feature class combining all the features and attributes of two inputs feature classes. The sixth tutorial taught me how to use the union tool. The union tool overlays the geometry and attributes of two inputs to create a new layer. The tutorial also taught me how to calculate geometry attributes. This allowed me to look at the acreage of the polygons. The last tutorial used the tools intersect and union. The tutorial was about the tools to create a feature class with combined features and data. When using these tools, the data is not split into parts for the new features. One of the tools I used was the Tabulate Intersection tool, which estimated the number of features within the boundary. 

Chapter 1:

This chapter introduced ArcGIS; it was easy to understand and follow along. The first tutorial in this chapter focused on understanding the software and where everything is. I learned about basemaps, how to turn different layers on and off, and how to reorder features on the map. I’ve learned how to use a pop-up window. When navigating maps, you can use bookmarks to help get there more easily. I wasn’t able to create my own bookmark on my map, but I understand how to. The attribute table has rows and columns of different data. Attributes provide data needed to solve a problem or investigate patterns and allow the user to search for useful information and mapped features. When analyzing, there are tools that can have the GIS create an attribute table based on the type of information you want. In tutorial 3, I created an attribute table of the minimum, maximum, mean, and standard deviation of the population density. Tutorial 4 was about adding a feature class to the map from a geodatabase, symbolizing it, and then removing it from the map. 

Chapter 2:

This chapter was all about map design. The chapter had 8 tutorials in total, the first tutorial taught me how to symbolize features by their code. This reminded me of one of the chapters by Mitchell about how it talked about giving certain features a specific symbol. The second tutorial focused on how to label features and how to configure pop ups. This tutorial taught me how to remove duplicate labels from my map, this helped declutter the map and be easier to read. The third tutorial helped sort through the data by creating a definition query, which is a filter with features of a layer. A definition query allows you to display only the features you’re interested in. The fourth tutorial was about creating a choropleth map, a choropleth map that uses color in polygons to represent numeric attribute values. I had a little difficulty creating the 3-d choropleth map. Tutorial six was about how to create your own scale for the data, I found this kind of fun being able to manipulate the groups of the data. Tutorial seven taught me how to create a dot density map, and tutorial eight was about setting visibility ranges. I found this helpful for displaying names of schools or counties within a certain distance to not overwhelm the map. 

Chapter 3:

In this chapter the textbook covered ways to display the maps that you create in the GIS software. It also covered how to share the maps online via the arcgis online website. When trying to share my own map to the web, the software wouldn’t load, and never finished uploading. This chapter taught me how to properly align the maps through the guide tool, by making rulers along the page. Some other tools that I learned how to use from this chapter include creating a legend, with/ without a title, and how to create charts. The legend allows the map’s audience to interpret the map’s symbology and understand what the map is portraying. The third tutorial was about how to properly present your graphs in a presentation style though arcgis online. I found this tutorial a bit easier compared to the rest because it was mainly copying and pasting from the word doc. However I do understand when making my own presentation of the data it won’t be that easy because I will have to come up with everything for the text boxes.  

Mitchell Chapter 4-

There are two ways to map density: by defined area and by density surface. You can map density by defined area using a dot map, where dots are randomly placed within the defined area to represent a certain number of features. These dot density maps show density graphically, rather than showing the actual density value. These kinds of maps are generally easier to read; however, the user has to make sure the dots are an appropriate size to not overlap and hide the pattern. Mapping density by defined area is normally displayed as a shaded map of the areas, with a range of colors. The density value applies to the entire area and may vary in that shaded region. 

The second method of mapping density is by density surface. Density surface maps are created as a raster layer; each cell has a density value. This approach is more detailed but does require more effort. You can create a density surface map from locations, sample points of data, crimes, or even bird nests. A cool type of density surface map is a contour map, which compares all the density values within a certain defined radius. From that compared value, the point is then given the average and shaded to that average. The cell size of the map determines how coarse or fine the patterns are. If you want the map to be smooth, the cell size needs to be smaller, but the process will take a long time to process. To find the cell size, you have to convert density to cell units, divide by the number of cells, and take the square root. When displaying the density surface map, you have to be careful how you classify the values, whether that be natural breaks, quantile, equal intervals, or standard deviation. Each grouping shows a different pattern in the densities. 

Mitchell Chapter 5-

I found it interesting that people map things to know what’s inside the area to monitor things like crime, or to compare many areas based on what’s inside of them. The data can be of things in a single area, or multiple surrounding areas. There are two types of features that reside inside an area, discrete and continuous. Discrete features are unique, where you can count them. Where continuous features represent geographic phenomena, like vegetation type. The information that you want portrayed from the analysis can tell you a lot. For example if you want the features to be completely, or partially inside an area, or if you want the surrounding area to be highlighted. The different types of mapping these features can tell you different things. 

There are three ways of finding what’s inside an area. The first is drawing areas and features, it’s quick and easy but only visual. This makes it harder to get information about the features inside. The second is selecting features inside the area, this is good for getting information inside a single area, but not several areas. The last method is overlaying the areas and features, which is good for showing what’s inside several areas, but takes more processing. After selecting the best method and creating a map, you can use the GIS to create a report of the features. A numeric attribute can be a sum, average, median, or standard deviation. When drawing features and highlighting them you can have the non highlighted parts be gray, or a lighter version of the features inside. The second option provides some information about what the features are. When overlaying areas, you can summarize the features by area. You can also summarize by category or value, it is important to account for variations in the areas. When making a map with overlaying areas on areas, it is important to look for slivers, and merge them with the adjacent larger areas. 

Mitchell Chapter 6-

This chapter focused on what’s nearby on the map. It discusses the importance of traveling ranges, and how to measure different ways to travel. A person would want to see what’s nearby for specific reasons, one of them could be to see how long it would take for police or firefighters to respond. 

To find what’s nearby there are a few different ways to measure distance. One of the methods is measuring what’s nearby, this can be measured by cost or distance. When measuring response time, you would want to measure by time, not distance. When measuring distance there are two different ways, the planar method and the geodesic method. When measuring smaller areas its best to use the planar method, and when measuring large areas like a continent its best to use the geodesic method. When measuring using the straight line distance, it’s good for creating boundaries, or setting distances around a source. When mapping for distance travelled,  its good for finding what’s within a travel distance of a fixed area/network. Mapping cost is good for calculating travel cost over land like forest or roadways. When displaying the information from several sources, there may be areas of overlapping distances or features labeled. If a spider diagram is used it is easy to see the features (like customers) that are in a certain distance from the source (like stores). A network layer is a geometric network composed of edges, junctions, and turns. You can set travel parameters, and costs to each road, turn, or stop sign. This means that you could set costs to turns, intersections or individual segments.When setting a cost, you have to create a turntable. When you create a boundary, you can find what’s inside the boundary by using information from chapter 5. You can compare distances of rings surrounding a source.

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. 

I read the syllabus and schedule, and I took the Geog 291 quiz!

Hello, my name is Kiley Sisler. I am a current sophomore and I am from Powell, Ohio. I am still currently undecided for my major; I am leaning towards astrophysics and computer science though. I am taking this class because I wanted to add ArcGIS Pro to my resume. Outside of Ohio Wesleyan, I partake in Tang Soo Do, and I am training to get my fourth-degree black belt right now.  

Chapter 1. 

I had never heard of GIS until I attended a career fair last year. I originally thought GIS was just used to map things like plants, forests, the way water flows and ecosystems. GIS originally started out in 1962, when Ian McHarg wanted to build a highway with the least amount of disturbance to everything around it. He used pieces of paper to create layers to find the spot of least disturbance to build the highway. I find it interesting that computerized spatial analysis was not really explored until the early 60’s, because the physical maps were acting as a decoy of the impact spatial analysis could have. 

There are many identities of GIS, GISystems, GIScientists, and GIScience. GISystems are assumed to be true by most of the users. It took a while for a new identity of GIS to be created/found. The next one was GIScience, which is the theoretical basis of GISystems. GIScientists are people that question the models, and if they would work in different scenarios. The work of these GIScientists starts before any of the data is put in digitally as well. GISystems has different processes compared to GIScience, such as classifications, spatial analysis, and digital encoding. Where GIScience has more theoretical bases and justification for these processes. Both GISystems and GIScience are dependent on spatial data. 

The definitions of boundaries are a heated topic, especially when it comes to resources. GIS is now used to help predict future outcomes from previous data. Some of the power that GIS has is from the power it has from visualization. Geographic visualization is both traditional cartography and the ability of expressing physical relationships with spatial data visually. GIS is used in agriculture, finding which crop is best based on the soil tests, and it is also used by the government for tax purposes. I never knew that GIS was used so much and on such a wide scale.  

Application 1

GIS for Carnivorous Plant Distribution & Conservation

Source:  Distribution Map – Carnivorous Plant Database 

Carnivorous plants—such as Drosera, Nepenthes, Sarracenia, and Utricularia—often inhabit nutrient-poor wetlands and highly specific microclimates. GIS helps researchers map species distributions, model habitat suitability, and track environmental changes affecting these sensitive plants. Some key GIS uses for carnivorous plants include mapping global species occurrences, modeling climate, identifying biodiversity hotspots, and helping support conservation planning in threatened wetland ecosystems. 

General GIS applications in environmental monitoring (contextual environmental GIS research)

Application 2

World Resources Institute. “Global Forest Watch.” WRI Data Explorer, World Resources Institute, 2026, https://datasets.wri.org/applications/global-forest-watch-app?utm_source=chatgpt.com 

GIS Application: Monitoring Deforestation

One important application of GIS in deforestation is Global Forest Watch (GFW), an online platform that uses satellite data and interactive maps to monitor changes in forests around the world. GIS allows users to see where trees are being lost and compare forest changes over time. Global Forest Watch can also show information about protected areas, land use, and deforestation alerts. This makes GIS useful for governments, researchers, and conservation organizations because they can identify areas experiencing forest loss and determine where conservation efforts may be needed. For example, a researcher could use the map to examine tree-cover loss in the Amazon rainforest and compare it with roads, protected areas, or agricultural regions. Global Forest Watch provides near-real-time information about where and how forests are changing, making it an important GIS application for monitoring and responding to deforestation.