Author: shyates

Chapter 9:

Tutorial one taught me how to use the pairwise buffer tool to find select attributes around an area. Tutorial two expanded on this by teaching me how to use the multiple-ring buffer tool, which creates layers of rings around a point. Tutorial three taught me how to use these buffer tools to create a service area around a space.  Tutorial four taught me how to use network analysis to visualize the demand relationships between places. Tutorial five taught me how to perform a cluster analysis using the multivariate clustering tool.

Chapter 10:

Tutorial one was really enlightening.  It taught me more about how to use and manipulate raster data, which is really useful for remote sensing. Tutorial two taught me how to create a kernel density map, which is a useful way to visualize statistic data spatially. Tutorial three builds on this by teaching me how to use a kernel density index to create a risk model.

Chapter 11:

The first tutorial taught me how to explore a global scene, which is a map with elevation. It also taught me how to apply shading to more accurately depict certain times of day, which was cool.  Tutorial two taught me how to work with a TIN, which we just started talking about in remote sensing. Tutorial three taught me how to create z-enabling features, which lets you visualize things like trees. Tutorial four taught me how to use lidar data to generate different types of raster and determine elevations. Tutorial five taught me more about navigating and working with 3D features in arc. Tutorial 6 taught me  how to use procedural rules to visualize buildings, and how to visualize multi patch models. Finally, tutorial seven taught me how to create an animation, which was something I didn’t even know Arc could do.

Chapter 4:

In this first tutorial, I had a bit of trouble finding the catalog pane. I found it eventually, but it took a lot of searching and head scratching. Other than that, this was a really good chapter for data additions and management. Tutorial 2 was also about data, but more so modifying and adjusting it for easier visualization. I especially appreciated learning how to work with the attribute table. Tutorial three taught me how to adjust selecting by attribute and how to save and modify selections to be more specific. Tutorial four was really easy. It showed me how to create a spatial join between features, which is useful for processing data with a relationship. Tutorial five taught me how to make a point layer, which is another way to see the relationship between an area and an occurrence. Finally, tutorial six taught me how to create a new attribute table and join data from other attributes tables to the new one.

Chapter 5:

The first tutorial taught me how to manipulate the world map and search by geographic coordinates. The second  tutorial was similar, but on a country scale, not a world-wide scale.  Tutorial three was similar to the others, but on an even smaller level. It also gave me some m0re practice adding and adjusting the symbology of data. Tutorial four taught me more about shape files and how to use them.  Tutorial five was a lot. I learned where to find things like census data and how to put them into Arc. Tutorial six taught me more about finding and inputting data from national sources, or from other public agencies. This is really useful for future endeavors.

Chapter 6:

The first tutorial taught me how to use the pairwise dissolve tool, which allows data to be shown in a more concise way.  Tutorial two was a refresher on specific selections, and how to extract and clip these selections.  Tutorial three was short and sweet, and showed me how to merge features into one attribute table. Tutorial four was also short, and taught me what the append tool did. This allows me to add new data directly to an attribute table. Tutorial five was a new way to work with the attribute table, through using the intersect and summary tools. It helps organize the data better. Tutorial six also taught me more about the attribute table, specifically how to use the union tool and the calculate geometry tool.  It also let me practice more with joining tables. Tutorial seven taught me how to use the tabulate intersection tool, which makes sure that across lines, the actual population remains.

Chapter 7:

The first tutorial taught me how to manipulate polygons on the map, which is incredibly useful for lining things up properly, making it easier to view and analyze structures. I also learned how to split a polygon into multiple parts. Tutorial two built on one, but teaching me how to create and delete polygons on the map. I also learned how to use the trace tool to create a study area. Tutorial three taught me how to use the cartography tools to do things like smooth polygons. The final tutorial taught me how to transform features, and how to add and export them as a CAD drawing.

Chapter 8:

The first tutorial of this chapter was a bit weird. It taught me how to locate zip codes and use that data. I can see why it would be helpful, but it’s still a but strange to me. The second tutorial was equally as strange to me, as it taught me how to geocode based on street addresses, rather than ZIP codes.

Project:

The preface is making me very excited to get started using GIS. There are so many potential applications for it, in both my field and in others. The start of chapter one explains the basic terminology for ArcGIS, which is especially useful as I did not know some of it beforehand. The most important part was explaining the difference between the gbs extension, which stands for a file geodatabase with feature classes and raster data, and an aprx extension, which contains a project, also known as the map or maps.

Chapter 1:

I got to the first turn section and tried to add the first base map, and the software froze. I rebooted the computer. It worked after this. The 1.1 tutorial was mostly focused on teaching me how to change basemaps and add features. I successfully completed this tutorial. The second tutorial focused on how to explore the map, and adjust the features of the map to see things more clearly. I also learned how to find the attribute table to find specific areas. In the third tutorial, I learned more about the attribute table, how to navigate it. For instance,I used the table to determine that object 204 had the largest population density. I also learned how to use the toolbox to get statistics. In the fourth tutorial, I learned how to adjust and change the symbols on the map. I also learned how to toggle labels and feature classes, and how to see a 3D version of the map, which was especially cool.

Chapter 2:

Tutorial one taught me more about adjusting symbology. The colors it had me choose for the map weren’t great, though. Not a lot of contrast. Tutorial two taught me more about the labelling tab, as well as how to change the information in the pop-up display. However, I couldn’t actually see any information in the pop-up beside the name of the neighborhood, even after I went back and triple checked that I did everything. Tutorial three taught me how to make definition queries, and let me practice adjusting symbology more. I attempted tutorial four, however, I could not adjust symbology due to an error, in which there was no data associated with the neighborhood, later renamed over age 60 receiving food stamps. I will try again later, when I can ask for advice. Tutorial five taught me how to display data in two different ways, quantile intervals and defined intervals. In tutorial six, I learned how to adjust and import symbology data, allowing for data comparisons. In tutorial seven, I learned how to create a dot map. In tutorial eight, I learned how to adjust labels, so that they can be seen only at certain levels of zoom. This is especially useful for keeping the map uncluttered.

Chapter 3:

Tutorial one was very big, but covered a lot of very interesting information. I enjoyed learning how to compare two maps on the same sheet. The create chart part did not work. The second tutorial taught me how to publish maps, and how to view published maps through ArcGIS. This is especially useful to know. Tutorial three is really useful for me, because one of my classes gives the option of making a story map for on the assignments, and now I know how! I’ll definitely be using this in the future. Finally, tutorial four taught me how to make a dashboard, which makes it easy to view information and share information with others. All in all, this unit has improved my understanding of arcGIS a lot.

Chapter four was all about how density mapping works in GIS and how to perform it effectively. Mapping by density is an effective way to see patterns in data, and is a sort of progression. to most and least mapping, which we learned in the previous chapter. Basically, being able to see the concentration of an occurrence/feature on a map allows one to get a general idea about the aforementioned feature. According to Mitchell, there are two main ways of mapping density using GIS: by defined area and by density surface. Defined area mapping means that you use a dot map to show density geographically, and is more accurate to the actual data points, but at the trade of it being harder to see a pattern emerge. Mapping by density surface, however, makes it easier to see the pattern, as it utilizes a raster layer to create a concentration gradient. There are many factors involved in choosing which form of density mapping to do, as well as how to effectively do said mapping. For instance, in density surface mapping, the cell size needs to be picked correctly, as if it is too large, it can make the pattern harder to discern, or if it’s too small, it can make data processing time much longer. It’s a balancing act of getting the most accurate data possible, without decreasing efficiency. This is also apparent when picking what units to use as the area in density mapping, as using the wrong unit can make skew the data. This chapter also empathized using a good color choice/ gradient, like chapter 3. This is because without easy to see differences, the data pattern can be hard to make out. Overall, this chapter was very effective at teaching the basics of density mapping.

Chapter five was a bit of a hard chapter. It starts introducing how to actually adjust/ modify the map parameters to show results for only certain sections. This is obviously a very important aspect of GIS mapping, but it’s a little complicated too. There is a lot of examples for why this is used, such as seeing differences in things like precipitation level or soil content inside of a floodplain, or observing the man made features inside a protected area. Analysis is one of the main purposes of mapping, as it allows for understanding patterns against geographic location, so being able to narrow down the parameters to just what a person is interested in is very important. According to this chapter, there are three main ways to do this: drawing areas and features, selecting the features inside an area, and overlaying the areas and features. Out of the three, drawing areas and features is the easiest and fastest to do, but it is purely visual and provides no concrete data. It can be used as a starting point, but is not proper for deeper analysis. Selecting features is better for getting quantitative data, but it cannot be separated into other areas, as it is treated as one by the GIS software at that point. Overlaying is the most accurate way of getting quantitative data, as it allows subsections inside the area a person is interested in. However, this method takes the longest and uses the most processing power, so it is not always suitable. Once you’ve picked which method to use, there are various ways to actually view the data, such as bar charts and pie charts, or tables. Choosing which of these to use to observe your data is also case dependent, but the chapter provides a good baseline for when each is most appropriate.

Chapter six was packed with a lot of complicated, but important information. This chapter taught me about how to analyze data based, not on what is inside a certain area, but what is around a certain area. This is obviously very useful for mapping, as it allows for things like analyzing distances between features or observing overlapping areas between features. What I found most interesting, however, was the idea of using cost to analyze a measure, as opposed to distance. In hindsight, it makes senes that not all mapping data is best viewed by distance, especially for things like urban planning. After all, things like traffic can make distance less reflective of the actual time taken. I especially enjoyed learning about how cost is changed by the geographic surface, and how the software can calculate said change. It is just very interesting for me to think about, and I find that one can use GIS to measure by cost to be very promising. Besides that, the chapter introduced a lot of new map making concepts, which is good, but also a bit hard to wrap my head around. For instance, spider diagrams are used to show the distance between a feature and a location, which can allow for one to see overlapping areas. This mapping technique has not been brought up before, and it is far from the only new one. Regardless, when there are so many types of data and data analysis, having a wide range of tools to observe this data is important. I also think that the information about setting a maximum distance for analysis is very important, as too much data could crash the computer, which is highly annoying to deal with. Nevertheless, I am excited to learn how to use the software.

Chapter one is a beautiful introduction to the geographic information system basics, as well as the basics of mapping. Before reading this, while I had a general idea of what GIS is and what it is used for, it was largely undefined and nowhere near the proper scope of this tool. Mapping and geospatial analysis are more relevant to my line of study than I previously realized, by a large margin. I’m already thinking of a multitude of ways that this software can help me in my future research endeavors. Besides an introduction to mapping as a whole, this chapter also introduced a lot of concepts that will become important later down the road. Of these, I think the most important concept is the process of performing an analysis. It reminds me a lot of the general scientific method, which makes sense as it is a way to perform scientific research, however it is more specific than the usual method. With mapping, the main purpose is to get an idea about large amounts of geospatial data through visual media, which can allow conclusions to be drawn more easily than by just looking at the raw data, so the method for performing analysis reflects this notion. I also find the clarification on things such as geographic features and geographic attributes to be highly useful. Being able to put information into neat categories is something I prefer when learning, so having these broader categories, such as discrete features versus continuous features, or the difference between sorting by counts and amounts is very nice. I will likely be referring back to this chapter a lot in the future, as this class continues.

Chapter two is focused on the nuances of mapping itself. It focuses on teaching the reader how to effectively make a map, and how to ensure that it is easily readable and understandable. This is an important thing to consider, as mapping is a form of data analysis, and if done incorrectly, could cause results to be inconclusive or skewed. A good chunk of the chapter is focused on how to properly group visual data into categories, and what using different styles of map can do to a reader’s understanding of a map. It goes over many types of maps, such as single-type maps, which are maps where only one category or feature is visualized, such as all crime in an area, or all roads. These maps can be useful for getting basic data about the distribution of the category, but are not highly detailed, meaning more complex conclusions cannot be drawn from them. This chapter also begins to introduce factors of how GIS creates maps, such as how it uses a coordinate system to assign locations on a map, or how it uses tables of data sets to form results. One big part of this chapter is a discussion of how much detail should be included in a map. To put it simply, it depends a lot on what one is trying to show with the map, and what would be too complex for the reader to understand. For example, if a map is too complex, it can draw away from the conclusion one wants, such as including too many vegetation categories and being unable to distinguish the broad interactions. This is also important when it comes to map scaling, as using too much or too little of a location can make it difficult to understand the distribution of results. Not to mention, the scale can affect how many categories one should use for visualizing data, as at smaller scales general data is less useful.

Chapter three is all about how mapping changes when using numerical values as opposed to general categories. Specifically, it focuses on how to show the variance between amounts in the data as an appropriate visual. This is more difficult than mapping by category, as there are more factors to consider. For one thing, the numbers need to be split into categories in order to show any data, but deciding what kind of split is highly dependent on the data being used. There are four main ways to split data, all of which have their own positives and negatives.  These are defined as natural breaks, which are when the data is grouped based on natural groupings in the values, quantile, which is when the data is grouped so that each class has an equal amount of features, equal interval, which is when the data is split evenly across the entire value set, and standard deviation, which is when the data is organized based on how many standard deviations it is away from the mean. The main concern with most of these is skewing the data, either through outliers causing the distribution to appear different, or ensuring that data is not grouped too much. Regardless, there are cases where each of these types is the most useful, such as equal interval being very useful for mapping continuous data, or standard deviation being useful for displaying what features are apart from the average. This chapter also goes in-depth about the five styles of mapping quantitative data, and what situations they are most useful in. This is a highly important chapter, and I will likely be using the skills described in it a great deal.

My name is Spencer Yates, and I am a microbiology and zoology major. I’m currently applying to graduate schools with areas in virology.  The reading was very interesting to me. I had no idea that GIS software was so important to modern research and engineering. I thought it was just for geographic research, but it’s much more broad than that. The creation of the GIS software is also fascinating, as it involved so many people all across the world over a large period of time. It is kind of hard for me to understand so far, as I’ve never really done mapping before. However, I am determined to master GIS by the end of this course. I think that this skill will be really useful for me in the future.

When I looked for applications of GIS that are interesting to me, I chose two categories: professional interest and personal interest. For professional interest, I looked up if GIS is useful for tracking the progression of diseases. There are a lot of examples of this, but I found a recent malaria study using GIS mapping to explore the prevalence of the disease in Nigeria to be the most fascinating. The paper used GIS mapping to show the changes in prevalence in areas of Nigeria over a 20-year period, which is incredibly useful to know.  Source: https://link.springer.com/article/10.1007/s00436-024-08276-0#Tab2

As for a more personal interest, I chose butterfly migration and conservation. In this category, monarch butterfly migration and habitat appeared to be a highly studied area. I found an interesting example of mapping the amount of suitable overwintering habitat for monarch butterflies in Mexico. While this map is only for one point in time, making similar maps in the coming years can allow for the tracking of habitat gain and loss, which can let researchers know if conservation efforts are effective or not. Source: https://creeksidescience.com/what-we-do/gis-analysis/

The blog is not letting me upload either of the maps I found, but they are in the links if you want to see them.