Category: Course Student Work

The ESRI Guide to GIS Analysis, vol. 1  (second edition, 2020) by Andy Mitchell

Chapter 1

GIS analysis is defined as a process for looking at geographic patterns in data and at relationships between features. When performing an analysis, the first step is to frame the question or figure out what information is needed. Understanding the data by evaluating its features and attributes helps to determine what needs to be acquired or created. In conjunction with consideration for the initial question and how the results of the analysis will be used, the type of data informs the specific method to select. After choosing a method, the data is processed by performing the necessary steps in a GIS and the results of the analysis may be displayed as a map, values in a table, or a chart.

It is crucial to be cognizant of the types of geographic features and how they are represented as the geographic features of the data impact every aspect of the analysis process.
3 Types of Geographic Features:
1. Discrete Features – Discontinuous and have definite feature boundaries (Esri definition I found online)
2. Continuous Phenomena – Can be found or measured anywhere – blanket the entire area mapped.
3. Features Summarized by Area – Represents the counts or density of individual features within area boundaries.

Vector (feature shapes are defined by x,y locations) and raster (features are represented as a matrix of cells) are the two models of the world that represent geographic features in a GIS. Discrete features and data summarized by area are usually represented using the vector model while continuous numeric values are represented using the raster model.

All data layers should be in the same map projection (translates locations on a globe onto the flat map) and coordinate system (specifies the units used to locate features in two-dimensional space and their origin).

Geographic features have one or more attributes. Attribute values include categories (groups of similar things), ranks (order features from high to low), counts (actual number of features) and amounts (measurable quantity associated with a feature), and ratios (relationship between two quantities). Working with tables that contain attribute values and summary statistics is a vital component of GIS analysis. Selecting features to work with a subset or to assign attribute values to just those features, calculating attribute values to assign new values to features in the data table, and summarizing the values for specific attributes to get statistics are all common operations performed on features and values within tables.

 

Chapter 2

Maps are often used to see where or what an individual feature is. However, looking at the distribution of features on a map can reveal patterns about the area being mapped, informing where action should be taken or potential causes for observed patterns. Before looking for geographic patterns in a data set, the features to display and how to display them must be decided based on the information needed and how the map will be used. The features being mapped must also have geographic coordinates assigned and a category attribute with values before map creation begins.

Telling the GIS which features to display and what symbols to use to draw them is the first step to creating a map. All features can be mapped in a layer as a single type (drawing all features using the same symbol) or displayed by category values (drawing features using a different symbol for each category value). When mapping by category, including different categories may reveal different patterns because features may belong to more than one category. Often, no more than seven categories are shown on the same map but, if the patterns are complex or the features are close together, separate maps for each category map be created. Grouping categories by assigning each record in the database to two codes (detailed or general), creating a table containing one record for each detailed code, or assigning the same symbol to the various detailed categories that comprise each general category are methods of grouping categories to make patterns easier to see when there are more than seven initial categories. The symbols used to display categories can also help reveal patterns in the data. It is important to remember that colors are easier to distinguish than shapes and using similar colors for related categories rather than randomly assigned colors can make patterns more obvious. A map that presents information clearly will display evident patterns in a dataset.

 

Chapter 3

Mapping the most and the least means to map features based on the quantity associated with each to see which places meet the criteria or understand the relationship between places. Determining the type of features being mapped and the purpose of the map will assist in deciding how to best present the quantities and see patterns on the map. Symbols must be assigned to features based on an attribute that contains a quantity (counts or amounts, ratios, or ranks) to map the most and the least. After determining the type of quantities in the data, the quantities must be represented on the map either by assigning each individual value to its own symbol or grouping values into classes. To look for patterns in the data, a standard classification scheme (natural breaks/jenks, quantile, equal interval, or standard deviation) should be used to group similar values. Creating a bar chart with attribute values on the horizontal axis shows how the data are distributed across their range, informing classification scheme selection. Once the data values are classified, a map type should be chosen based on the type of features and the data values being mapped.

Graduated Symbols – Used to map discrete locations, lines, or areas.
Graduated Colors – Used to map discrete areas, data summarized by area, or continuous phenomena.
Charts – Used to map data summarized by area, or discrete locations or areas.
Contour Lines – Used to show the rate of change in values across an area for spatially continuous phenomena.

To visualize the surface of continuous phenomena, three-dimensional (3D) perspective views are utilized. When creating a 3D view, the viewer’s location, z-factor (specified value to increase the variation in the surface), and location of the light source are manipulated to determine what the view will look like. A map that presents information clearly will display where the highest and lowest values are.

Chapter 1:

When reading this chapter there was many things that interested me as well as new concepts that stuck out ot me. Firstly starting out with the first few pages of the first chapter I was not surprised to find the meaning of GIS to be geographic mapping of many different things. We specifically covered many of the things GIS can do with the previous weeks reading, so this information was expected and not new to me. Next the term continuous phenomena was something I have never heard in regards to mapping temperature and regarded as blanketing a map with no gaps. There are many other mapping methods too that I did not know completely like the raster model and vector model (I do realize that these are the main two representations of geographic features). It was interesting to see the comparison of these methods side by side with the same mapping set. I do wonder why one is more preferable to certain subjects over the other? There was also many vocabulary when put into the GIS context like categories’, map projections and coordinates. However I did find ranks to be interesting, organizing and placing data relative to values, at least in terms of GIS I never thought this would be something that would be useful. The ratio section of this chapter reminded me of when we map data using specific plot data in R-studio. The layout as well as the key guide prove similar to this comparison. Lastly data tables being so significant to the GIS process, yes I know that data itself is extremely important, as these maps are made based on the data provided however I though the map created would prove to be more useful than the data table. Chapter one was a good overview of the systeming expected to come along with GIS mapping.

Chapter 2:

Reading chapter two with the knowledge gathered from chapter one, I had many more thoughts along with more answers to GIS as a whole. Firstly I found it interesting that GIS mapping can be used for businesses to pin point customers by age or other traits to help classify their clients and utilize this information to create a better sales or business strategy. When it comes to preparing the data I find similarities again with GIS to R studio, the type of data prep and coding as well as the categorizing of certain data points all read within the same lines as R studio code and category. This similarity can explain why some maps look similar to some data graphs I have seen within R studio. I do wonder if mapping just a single type data set or features is more beneficial than the latter? Could more data features help widen an answer or set of data? I also find it very interesting that the most categories you can map is seven due to the intake people can handle. What I mean by this is that people can only distinguish between a certain amount of colors or symbols, thus going over this threshold makes the maps too complex. I guess this answered my question in some ways as there is a sense of too much data that is portrayed within GIS. Now with this being said mapping over seven can be done but must be done so with grouping, so simply seven categories alone is almost more substantial than the latter. I also thought it was interesting that choosing your symbols can help reveal patterns within the data and these symbols can be read as their own data on a map. I would never think symbols would be that important, however it would make sense as GIS proves that grouping factors pave the way for an ideal map. It’s good to know that mapping a correct GIS map can prove to show patterns, some that you were not expecting. Chapter two broadened what I know about GIS maps even more and proved essential in learning the value of mapping and the patterns presented from such.

Chapter 3:

Finally when reading the final assigned chapter of this week I had more thoughts and things I learned and  found interesting through this chapter. Firstly I’m noticing a lot of vocabulary from chapter one and two being pieced together to explain why someone chooses to make GIS maps one way over the other. I also like how Mitchell reminds us to have a purpose to the map, whether we want to explore the data set created or have something precise and cohesive. This connects to having a purpose when creating a GIS map. I also find it interesting the way that finding and choosing the quantities you want to utilize create a framework for the map, again I would’ve supposed data points would have a bigger makeup of a GIS map, but it seems that quantities are equally important. One thing I learned is the meaning of class is the groups of similar features assigning them together typically with a symbol. Another thing I learned is all the types of classification schemes, it’s interesting to see how each one can be useful depending on what you are looking to create, it’s also interesting that disadvantages for each are included, this allows the map creator to have full control over how they present their data. Chapter three was very informative when it came to how to create trends and maps and what data would be more beneficial to use and utilize, I learned more definitions and things I did not know applied to GIS.

Chapter One

I think the definition that Mitchell provides for GIS is very effective because of how simple it is: “GIS analysis is a process for looking at geographic patterns in your data and at relationships between features.” This definition is short and to the point but this description allows me to better understand all of the capabilities of GIS rather than just “maps.” I also think it was useful to approach using GIS in terms of a research question you are trying to answer, like starting with framing the question and really understanding what you are trying to get out of the project at hand will help guide you on what type of data you need to acquire and then which methods to use to then process the data and eventually try to interpret the results. I found the breakdown of types of features to be very useful. Terminology such as “discrete features” and “continuous phenomena” were not terms that I have really heard before and it was useful to understand that discrete features are used for locations and lines when an actual location can be pinpointed, whereas, continuous phenomena is used for an entire area. ‘The two ways of representing geographic features’ also brought two new terms I was unfamiliar with which were “vector” and “raster.” Vector uses rows and tables and is more of the traditional x and y approach. Raster models “use a matrix of cells in a continuous space.” From my understanding, the raster model layers different data points for analysis. In the next section, I learned how map projections use a sphere to project coordinates onto a flat surface and how it distorts the shapes, area, measurements, etc. Coordinate systems use a 2D system and have specific units. I noticed that the types of attribute values (categories, ranks, counts, amounts, ratios) are very similar to different types of data in statistics (nominal, ordinal, interval, and ratio), which was a great segue into talking about data tables!

Chapter Two

This chapter talks about why we map things and immediately I was met with the quote “mapping where things are can show you where you need to take action” which is literally so important for public health. For example, John Snow used maps and data points to understand that the cholera outbreak was coming from the Broad Street pump and was able to identify the problem this way. I also think the section on how to use the map was important because it mentioned using the appropriate map for your audience. This is very relevant to any type of work related to policies where you are trying to persuade lawmakers or decision makers. I learned how one of the foundational parts of starting to map data is importing or assigning coordinates and category values. The paragraph explaining what GIS does was very helpful to understand how it goes from data to mapping this information. I also found the visual example on page 31 to be helpful because in the first image it starts with one set of coordinates, then in the next picture it starts to connect the coordinates, and in the last photo, it shows the highlight of the parcel of land mentioned in the text. In the category section  I also appreciated the more in depth explanation of what GIS does and how it looks up symbols based on category. I didn;t know the simple example of line thickness on road maps was using GIS before! I also learned that most people can’t distinguish more than seven categories which honestly makes so much sense because I think when I look at figures that have more than seven I get very overwhelmed! I also think it is interesting how much of an impact grouping categories can have on your data and it is something that I have not really thought about! Overall, this chapter was very insightful and provided a lot of useful information!

Chapter Three

I found the concept of “Mapping the Most and Least” to be very thought provoking. At first, I didn’t quite understand this concept but once I read through the public health example of physicians per 1,000 people it made more sense. I also found the section on Ratios to be very useful. Although this is a concept I have learned a few different times in my academic career, it is always helpful to have a reminder of the different types of ratios and how they can most effectively be used, especially in terms of mapping data. I was a little confused by ranks at first but once it explained it in terms of text and then provided a visual example on page 62 it made much more sense! Classes were also a useful refresher in terms of what their purpose is, as well as an example on page 63 which uses poverty rates. Standard classification schemes was another concept I was not as familiar with. The text gave a good overview that explained it as grouping similar values to find patterns. I liked how it was broken down into the four categories of natural breaks (natural groupings), quantile, equal interval, and standard deviation. The information about how to choose a classification scheme was also useful and something I made note of: uneven data: natural breaks, evenly distributed data and want to emphasize differences in features: standard deviation, evenly distributed data and want to emphasize relative differences: quantile. Outliers are always something that will come up in data sets and can be very impactful to what you are trying to portray. I appreciated the tips and trips on what to look for with outliers. I found the entire section on making a map to be very useful, especially the table with all of the breakdowns of features, values, advantages and disadvantages. The checklist for choosing a map type will also be useful in the future!

Hi! My name is Emily and I am majoring in International studies and Environmental studies, with a minor in Spanish. I love traveling and just got back from studying abroad in Chile. I love animals and nature, I have three cats, two dogs and a turtle at home.

 

 

 

 

 

Before this reading, I had no idea what GIS was, or the importance it has. It was interesting that the history of GIS goes back to the 1960s, yet many people like myself are unaware of the significance of GIS analysis. It has become essential in many different fields from urban planning to public health. What I thought was most interesting was that GIS can be defined as both a system and a science. GISystems focused more on software and hardware, and GIScience is the more theoretical parts of spatial data and analysis. This introduction chapter peaked my interest in the applications of GIS and challenged me to think more critically about spatial data and how it influences real world outcomes.

For the first GIS application, I explored its use in water resource management. I am specifically interested in water depletion. GIS can be used to analyze and visualize water depletion by mapping various factors contributing to water scarcity such as groundwater levels, water usage patterns, land use, soil types and climate data. This provides information on where water depletion is more severe and why. 

I searched up “water depletion GIS California” and found  information on groundwater depletion in California’s central valley. Residents in this region rely on groundwater for agricultural growth, and this study found that 45 selected urban areas with a population average of 7 million people are at risk of Aquifer depletion.

 

Source: https://storymaps.arcgis.com/stories/0c1fce0700c4465180b3258c4751ecbb

For my second application, I searched “GIS application for animal shelters in Ohio” and I came across a website titled “Get started tracking at-risk animals using GIS data”.  This seems to be information on a project happening in northern Ohio. They use GIS to target at-risk animals in communities so shelters can understand where at-risk animals are coming from and determine where it makes sense to target planned interventions. GIS, in this case, is used to help animals.

Source: https://www.aspcapro.org/resource/get-started-tracking-risk-animals-using-gis-data

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.

Hi! My name is Claire Heumasse, and I’m a Junior from Scarborough, ME. I am majoring in Biology at Ohio Wesleyan University and am involved in the Cheer team, Women in Science club, and Rock climbing club. In my free time, I enjoy ice skating and reading books.

In reading Schuurmans first chapter of GIS: A Short Introduction, I expected a boring, technical overview, but I was surprised by how easy it was to understand and how interesting it turned out to be. Schuurman highlights how GIS is not only a practical tool but also a lens to understand and analyze complex spatial data. I also found the historical development of GIS fascinating, particularly how overlay techniques evolved from physical maps to digital platforms. What stood out most was the discussion on GIS’s versatility. From urban planning to public health, the potential applications of GIS are seemingly endless. I was especially intrigued by how GIS is used to map crime patterns and analyze their spatial relationships—a tool that can influence public policy and improve safety.

For the first GIS application, I explored its use in Indonesia. GIS is employed to monitor deforestation in Kalimantan and Sumatra. By mapping forest cover changes over time, researchers can identify illegal logging hotspots and assess the impact of deforestation on biodiversity. This application is crucial for protecting endangered species, such as orangutans, that rely on these habitats.

 

Source: https://www.arcgis.com/home/item.html?id=60e5dfae803c48ac932a9117f28c6694

For the second application, I searched “crime mapping GIS” and found an example in Houston, Texas. GIS is being used to analyze violent crime patterns in the city, helping law enforcement allocate resources effectively. By creating heatmaps of high-crime areas, officials can identify correlations between crime rates and urban features like poorly lit streets or abandoned buildings. For instance, GIS data has highlighted specific neighborhoods where targeted interventions, such as increased police presence and community programs, have led to measurable reductions in crime.

Source: https://www.arcgis.com/apps/instant/sidebar/index.html?appid=1427304b9e6048a488e0be90b3aa1cd7

Hi, my name is Jes Powell.  I’m a senior and I am majoring in Studio Art.  I am from the Cayman Islands and I live/grew up on the beach.  I love photography and writing.

Chapter 1 of Schuurman’s GIS: A Short Introduction discusses the importance of Geographic Information Systems (GIS) and how it can be found everywhere.  GIS is used for a variety of different tasks and oftentimes people don’t realize how extremely impactful it can be.  To each individual GIS is important and effective for various different personal reasons.  For example in a city GIS can be crucial when it comes to planning residential, industrial, and commercial zones; this is just one of the many ways that GIS can be used.  GIS uses mapping and data analysis to find solutions and allows for data to be interpreted in a way that can be an aid for planning and research.  There are two main components of what the acronym GIS stands for; this being GISystems and GIScience.  GISystems more so focuses on ways of analyzing and mapping out data and is more commonly thought of when considered the acronym GIS.  On the other hand GIScience focuses more on the overall explanation of questions related to how GIS software puts out its output.  I think it’s interesting that there are two different meanings to the acronym of GIS and that it is not just simply Geographic Information Systems.  The most important part about these two faces of GIS discussed in this section of the chapter is how spatial phenomena is translated into digital terms; this is essentially what connects both GISystems and GIScience.  GIS is an extremely diverse tool that impacts everyday life for a majority of people.  I think most people don’t realize that GIS goes beyond just something that is technological as it can be the deciding factor for numerous things.  GIS technologies have a major role in food production and agriculture, and can impact government and business decisions.  GIS technologies impact every part of our life and it is an important tool to understand what is used for and what exactly it means and what type of data is getting taken in and what data is being outputted.

GIS Applications

1. I looked up how GIS applications are used for the Cayman Islands and I found how it can be used in Grand Cayman (the main island)  to determine which areas are more exposed to flooding and which areas are more exposed to specific hurricane categories.  I think this is important information to take into consideration as it can be necessary for future plans of how land is used and what developments are made.
   
   https://link.springer.com/article/10.1007/s11069-010-9539-0
2.  The second thing I looked up related to GIS applications is how it can be used to see the specific areas in the Cayman Islands that are turtle habitats.  This is important as these areas are protected during turtle nesting season and there are specific turtle nesting sites that you are not allowed to go to so that the process isn’t disrupted.  I think the use of GIS applications to be able to see this information is crucial because it ensures that these marine animals are able to safely and effectively go through their normal process of nesting and returning to the ocean without natural and man made obstacles that would otherwise prevent them from doing so.
   
   https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2021.663856/full

 

 

Hi my name is Daniela Flores (she/her) I am a sophomore majoring in environmental science. I’m from Philadelphia PA, I love listening to music and going on walks.

Chapter 1

When people think of GIS, they believe it’s only software for geographers because of its ability to document and log locations. In reality, everyone uses it, and it is a helpful tool for anyone in any subject or job position. GIS can help with basically anything that is in any place that can be documented. 

With GIS we can visualize things we couldn’t when it was just with pen and paper. We can see the repercussions of potential construction in areas and how it can damage the environment without doing anything to the area. GIS reminds me of a layered cake, layering different layers of the land, soil, forest, housing/buildings to create one map that includes all the characteristics of one area. One thing I like about GIS that this chapter talked about was how when using GIS the facts and data don’t have to be as precise, there can be guesstimates to see how things would look while finalizing data or making hypotheses while mapping. GIS is also good for visual learners, they can see the separate layers of the area and learn about it in an easier format instead of reading long articles about data. With this visual format, it can be easier to solve problems as they are now imitating what someone is trying to hypothesize. With GIS we are not only able to address environmental concerns but also human concerns like crime, femicide, and social changes. GIS can help with anything you can think of, it is a powerful, and accessible tool that anyone can use. I wonder if GIS has been purposefully used to urbanize and gentrify certain areas because they seem like good areas to build businesses without identifying the places that were there before. 

Two GIS applications 

One GIS application I looked up was feminicide, I found one based in Antioquia, Colombia. This paper focuses on studying feminicide from a geographical perspective, and seeing how the relationship with drug trafficking in geographical locations impacts feminicides. 

Source: The spatial heterogeneity of factors of feminicide: The case of Antioquia Colombia

The second GIS application I looked up was Landslides in Colombia. They used GIS to estimate groundwater levels and compare them to rainfall events. They also compared it with earthquakes to see their relationship and how they could predict landslides. 

https://onlinelibrary.wiley.com/doi/epdf/10.1002/%28SICI%291096-9837%28199609%2921%3A9%3C853%3A%3AAID-ESP676%3E3.0.CO%3B2-C

 

Hi! I am Jade Fondran, a sophomore studying Zoology and minoring in Environmental Science. I am from Euclid, Ohio a suburb of Cleveland. I have a dog, two cats, and three fish.

Before reading this article I was unaware at how prevalent GIS is in each of our lives. I was surprised to know that a company like Starbucks uses GIS in order to strategically place each of their locations. I found this specific quote explaining GIS to be interesting “It is not a piece of software, but a scientific approach to the problem: ”how do we define crisp boundaries to demarcate fuzzy and changeable phenomena?” ” I thought this was an insightful way to explain how GIS can be used for many different things.

The identity crisis of GIS began in the 1960s when Ian Mcharg was determining how to fit a highway into the landscape properly. He used overlays of paper with forests, streets, buildings, etc on each layer and determined the best route. This overlay method became the basis for GIS and other spatial analysis techniques.  This concept of overlaying paper was translated into one of the earliest GIS systems on a computer. I always find stories of how some of the first computers worked and how they were created to be very fascinating.

In a later section, What Does the Acronym GIS Stand For? The Two Faces of GIS , it explains how  important  the translation of spatial phenomena is made into digital terms. Slight differences can change the results for analysis, and it is important for GIScience. I found it interesting that GIS is multifaceted and is not just one thing. Overall, I found this reading insightful and thoroughly introduced me to what GIS is and how important it is to society.

1. “GIS Application on Endangered Sharks”

GIS is used very often when determining where animals are most threatened. Making it very important to those who work in conservation. For example, the picture I found shows areas in which habitats of certain animals are protected under the Endangered Species Act. This specific example was made by NOAA Fisheries in order to make it easier for the public to identify protected areas.

2. “GIS application on plants”

GIS application can be used frequently when dealing with agriculture. For example, it can be used to help determine crop growth while analyzing fertilizer, soil type, and terrain. This map shows “Fertilizer application assessment based on data from field equipment, processed with EOSDA Crop Monitoring.” GIS software is very important in many aspects of agriculture and benefits all who utilize it in order to have the most efficient practices.

https://sites.owu.edu/geog-291/wp-content/uploads/sites/208/2025/01/print.pdf

Sources:

https://www.fisheries.noaa.gov/feature-story/new-app-makes-endangered-species-habitat-easy-find

https://eos.com/blog/gis-in-agriculture/