Geography 291: Geospatial Analysis with Desktop GIS

Chapter 5: 

Chapter 5 focuses on why map what’s inside, defining your analysis, 3 ways of finding what’s inside, drawing areas and features, selecting features inside an area, overlaying areas and features. why map what’s inside an area is to monitor whats occurring inside or to compare the area to other areas. Defining your analysis is to find what is inside an area by either drawing a boundary on top of features, using an area boundary to select features or list the features and summarize. To do this you need to know how many areas you have within your data, are the features discrete or continuous. continuous features are seamless geographic phenomena and can be summarized like soil type and precipitation. What information is needed for an analysis like is it a count, list or summary? And do you need to see the features that are only within the area or can features that are partly within an area be counted/ used. 3 ways of finding whats inside are drawing areas and features, selecting the features inside of the area and overlaying the area and features. Drawing is good for finding if features are inside of an area but are visual only = no information. Selecting the features inside of the area is good for getting a list or summary of all the features within an area but does not tell you whats inside each of the several areas. Overlaying the areas and features finds out which features are inside and summarize how many features by area but requires more work/processing. Drawing areas and features uses GIS to draw on top of features making discrete features see-able and allowing for a sense of the range of continuous values to be made. Selecting the features inside an Area is a method to specify the features and the area. The system checks to see if each feature is within the area, and selects the corresponding rows of data to feature inn the data table. To use this data you can create a report on the selected features with a count, frequency or summary of the numeric attributes per the features. overlaying the features and areas is a method to find discrete features and summarize, calc the continuous categories or class inside one or more areas. This is done with overlaying the areas with discrete features or overlaying the  areas with continuous categories or classes.

Chapter 6:

Chapter 6 focuses on why mapping what’s nearby, defining the analysis, 3 ways of finding whats nearby, using straight line distance, measuring distance or cost over network, and calculating cost over a geographic surface. why map what’s nearby is to find out what’s occurring within a set distance from a feature as well as what’s within traveling range. This can help determine areas that are sustainable/ capable of supporting a specific use. Defining your analysis is to find what is nearby and deciding how to measure nearness and what information needed for analysis to help then choose which method to use. For this we should know what are we measuring and whether its using a distance or cost. and if the distance is over flat or rough terrain. The 3 ways of finding what’s nearby is using a straight line, distance or cost over a network and cost over surface. Distance for a straight line is good for defining an area around a feature and creating a boundary around them but it only gives a rough estimate for travel distance. Distance over a cost network is for measurement travel over a fixed infrastructure but requires an accurate network layer. Cost over surface is used for measuring overland travel and calc how much area is within that travel range but requires more data prep to build the cost surface. using straight-line distance is how to see which features are within a given distance of a feature/source. Creating a buffer around this feature can be useful as well as selecting which features within the distance like a buffer but not quite. Creating a distance surface. measuring distance or cost over network is a GIS method that ID’s all the lines in a network within a given distance, time or cost of a source location. these sources are termed centers. calculating cost over a geographic surface allows for figuring out what is nearby when traveling over the land, this needs a raster layer  within each cell value of the travel cost from nearest source cell. To do this we must specify the cost, modify the cost distance, where the information is coming from should also be specified as well as summarizing whats within the distances found.

Chapter 7:

Chapter 7 focuses on why a map changes, defining your analysis, 3 ways of mapping change, creating a time series, creating a tracking map, measuring and mapping change. Why maps change is to anticipate refuter condition’s and then to decide what course of action should be taken as well as evaluation the results of an action policy. defining your analysis is for when the map does change by showing a location and condition of features at each date and then from this we can calc and map the difference in each value for each feature between the 2 dates. for this we need to know types of change, the geographic features, how to measure the time between and how it will affect the geographic patterns on the map and the information you need from the analysis. there are 3 ways of mapping change, time series, tracking map and measuring change. Time series is good for movement or change in a character but visual comparison between 2 maps must be done to comprehend. Tracking map does movement but can be hard to read if there are a lot of features. Measuring change is for a change in character but doesn’t show actual conditions at each time and the change clac between 2 times only, no more. Creating a time series but you’re making a map for several times and dates a couple of times and the need to consider how many maps and the range of values. To show a change in location, change in magnitude or character, the number of maps to show and looking at the results of all of this. Creating a tracking map shows the position of a feature(s) at several dates/time. measuring and mapping change is to calc the difference in values between 2 dates  and map features based on the value calculated. discrete features and data summarized by the area must be known. As well as continuous categories or classes with continuous numeric values.

Chapter 5: Finding What’s Inside

This chapter discusses why “finding what’s inside” lets you see whether an activity occurs inside an area or how to summarize the information to compare what is inside several areas. By monitoring and mapping what’s inside an area, it will inform people if action needs to be taken. An area boundary can be drawn on top of the features within a single area or several areas. Within these boundaries, there can be discrete features (unique and identifiable features) or continuous features (seamless geographic phenomena). There are also three ways of finding what’s inside by drawing areas and features(a map displaying the boundary area and features), selecting the features within the area (list of features in area), and overlaying the areas and features (patterns in features found in areas). GIS can be used to draw the area(s) on top of features to gain a sense of the discrete or continuous features within, as well as checking the location of each feature to see if it’s inside the area. A helpful tool to keep in mind is GIS can create a report of selected features through statistical summaries, creating a count (the number of features inside an area), and a frequency (the number of features within a given value). Overlaying areas and features lets you find discrete features and summarize them, calculate the amount of continuous categories or summarize continuous values.
A lot of this chapter felt repetitive and could have been condensed probably. I did however get a good understanding of mapping an area in order to find valuable information inside it. Most of the time, GIS is being used to target an area being studied so “finding what’s inside” seems like a way of saying “using GIS to find trends in the study area”.

Chapter 6: Finding What’s Nearby

Chapter 6 discusses how in finding out what’s nearby, you can see what’s within a set distance or range of a feature. The information you need to complete an analysis of what’s nearby involving a list, count, or summary. If you have more than one range that needs to be accounted for, inclusive rings or distinct bands can be used. In order to find out what’s nearby, you can measure either straight-line distance, measure distance or cost over network, or measure cost over surface. Straight-line distance can create a boundary/selecting features within a set distance from a source. This can be done by creating buffers to define a boundary to see what’s inside of it, or features can be selected to find other features within a given distance. Distance or cost over a network can be used for finding what is within a travel distance or cost of a location over a fixed network. For this approach, GIS can identify all of the lines in network (ex: streets, pipelines) within a given distance, time, or cost of a location. Cost over surface can be used to calculate what is nearby when traveling over land. When using this method, GIS creates a raster layer so the value of each cell is the total travel cost from the nearest source cell. In doing so, calculating the cost over a surface can show the rate of change and patterns.
I can see why it is important to find features nearby to help find patterns in the data that you are analyzing. I also appreciated how the chapter outlined clearly what each method should be used for and how, as well as the pros and cons of each.

Chapter 7: Mapping Change

Chapter 7 focuses on how GIS can help map changing conditions to an area over time since things are constantly changing. We map change to anticipate future conditions, decide on a course of action, or articulate the results of an action/policy. In order to map change, it’s important to understand the type of features and the type of change that can aid you in the process of mapping the change. Types of change outlined in the chapter included changes in geographic features, location, and character or magnitude. These involve discrete features that physically move or have gone through geographic phenomena. We can also measure the length of time between changes with three different patterns: a trend, before and after, and a cycle. Important to keep in mind when mapping change is instead of mapping the conditions over two different times, calculate a change in value as it highlights the features that have gone through the most or least changes. There are also three main ways of mapping change outlined in the chapter. First is through a time series for seeing changes in boundaries, values for discrete areas, or surfaces. The second way is through a tracking map which shows movement in discrete locations, linear features, or area boundaries. The last method is measuring change to see the amount, percentage, or rate of change in a place. After mapping change in an area, a time series can be created to show the change over time.
Overall, mapping change is used to calculate the difference in values over time and mapping the features based on the values. Land is constantly changing, naturally and by human interaction so mapping change is important as we analyze land in the past, present, and future.

Chapter 5

Chapter five teaches about “finding what’s inside” and how it lets you see whether an activity occurs inside an area or summarized information. When paired with multiple areas, you can compare them to see patterns and information that you weren’t able to see beforehand. The main focus of this chapter was discussing boundaries that can isolate locations or information to create summary data. You can do this with a single area, which allows you to summarize information and monitor the area. You can also set boundaries on several areas that you would then treat as one. An example Mitchell uses for setting a boundary around multiple locations is if you want to find out the number of businesses within a group of zip codes. It’s important to know that you’ll want to be able to identify each area uniquely, or else you or your audience wouldn’t be able to understand the information presented. You can do this by using names or even numbers to set one area apart from another. Mitchell then talks about using counts, lists, and summaries within a boundary to gather all of the features that you’re looking for within a boundary. Another important factor in mapping with boundaries is whether you decide to include only features that are completely inside your boundary, or if you want to include features outside as well. It’s effective if you choose the latter to use different colors to distinguish the features inside from the ones outside. There are also many methods to go about mapping what’s inside; drawing areas and features is good for finding out whether features are inside or outside an area, selecting the features inside the area is good for getting a list or summary of features inside an area, overlaying areas and features is good for summarizing how many or how much by area. As with the rest of this book, this chapter provides a list of ways to map and present the information you’re studying.

Chapter 6

Chapter 6 talks about finding what’s nearby and how it lets you see what’s within a set distance or travel range of a feature, allowing you to monitor events inside an area. First, Mitchell talks about determining the style of analysis, which mainly includes travel cost and distance, but also talks about planes and whether what you’re analyzing requires taking the planet’s curvature into account. Travel range specifically is measured using distance, time, or cost: finding the traveling range of a feature can help define the area served by a facility and can help delineate areas that are suitable for, or capable of supporting, a specific use. When talking further about cost, Mitchell states that time is one of the most common costs, along with money or effort expended, in which all of these costs describe the term “travel costs”. He then talks more about calculating distance in two different ways, either assuming that the Earth is flat, or if you’re taking into account the curvature of the Earth, which are respectively known as the planar and geodesic methods. The planar method is more efficient when your area of interest is smaller, such as a city, county, or even a state. The geodesic method is more efficient when your area of interest is a large region, continent, or even the entire Earth.  The chapter then goes back to boundaries and talks about inclusive rings, which are useful for finding out how the total amount increases as the distance increases when specifying more than one area. You can also use district bands, which are useful if you want to compare distance to other characteristics in your map. From here we move on to tree different ways to find what’s nearby, straight line distance, distance/cost over a network, and cost over a surface, which all have their own intended purposes.

Chapter 7

The final chapter for Mitchell’s book talks about map changing. Map changing is when you map in GIS where things move, or the changing conditions in a place over time. Knowing what’s changed in an area, or multiple areas, is useful when understanding how things behave over time, anticipate future conditions, or evaluate the results of an action or policy. A common example of map changing is mapping the paths of hurricanes to see whether the patterns change from month to month. By mapping conditions before and after an event, you can see the impact of it, and just like in the first chapter, this helps you determine where you need to take action. I feel that defining the analysis for this kind of mapping is crucial (just like when defining analysis in other chapters) because you can either go about it by showing the location and condition of features at each date, or you can calculate and map the difference in a value for each feature between two or more dates. You can see geographic changes in location or in character or even magnitude, and choosing one or the other can alter the appearance of your map, therefore it’s important define your analysis. When mapping change by location you can see how a certain feature behaves, which can help you predict where they’ll move, and mapping change in character or magnitude shows you how conditions in a given place have changed. From here the chapter moves onto focusing on measuring by time, where it gives you a list of  ways you can measure time: by a trend (change between two or more dates/times), by “before and after” (analyzing conditions preceding and following an event), and a cycle (a change over a recurring time period, such as a day, month, or year). The chapter then talks about knowing what information you need in order to map change effectively. To me this might be the most difficult thing to learn when we start using ArcGIS more, but I’m excited to see what patterns I can create and form with map making.

 

Chapter 5

This chapter explains how and why GIS users analyze data inside an area, and specifies the advantages and disadvantages to using various mapping methods. First, Mitchell examines why people map different areas. He states that people map “to monitor what’s occurring inside it, or to compare several areas based on what’s inside each.” For example, a police officer would be interested in analyzing how many people on parole are still in their specified areas; if a person is outside of their specified region, then a warrant may be issued. Next, the author emphasizes the importance of determining what information is necessary when attempting to map out a problem. The following questions are ones he deems critical: are you mapping a single or multiple areas?; are the features continuous or discrete?; do you need a list, count, or summary?; and do you need to see the features completely or partially inside the area? Then, Mitchell analyzes three different mapping methods: (1) drawing areas and features, (2) selecting features inside an area, and (3) overlaying areas and features. He provides short synopses for what each method is good for, what you need to utilize the method, and how GIS visualize these methods. Finally, the author goes into further detail about each method and provides tips and trips to better assemble and analyze maps.

Overall, I found this to chapter to be helpful in providing tips into better defining map data so as not to confuse observers, but also in creating better analyses for the user. Although I did find this reading to be very redundant with the majority of points being made multiple times throughout. I will be utilizing this chapter in particular to troubleshoot if I run into any issues analyzing data.

Chapter 6

This chapter explains the significance of mapping the distance around an area and specifies three manners in which the process can be done. First, the author states why people map near specified areas and examines various questions that he finds to be important in configuring how to better define problems. Then, he states the three types of mapping processes utilized to map nearby: (1) straight-line distance, (2) distance or cost over a network, and (3) cost over a surface. Before defining each individually, Mitchell compares each type with one another and clarifies which mapping method is best for different situations. Next, he begins to describe the straight-line distance method, which he says is when “you specify the source feature and the distance, and the GIS finds the area or the surrounding features within the distance.” For example, you might have a toxic waste spill at a nuclear plant and need to know how many houses or businesses are within a 10-mile radius of the nuclear plant to properly evacuate the region. In addition, Mitchell examines measuring distance or cost over a network. This is when “you specify the source locations and a distance or travel cost along with each linear feature, and the GIS finds which segments of the network are within the distance or cost.” Furthermore, Mitchell defines the final mapping method, calculating cost over a geographic surface. This is when “you specify the location of the source features and a travel cost, and the GIS creates a new layer showing the travel cost from each source feature.” For example, you may have a river that has been commonly used as a dumping ground for animal waste by a local farmer, and the river sits on an uneven surface over a large stretch of land. You may need to use GIS to calculate the cost distance of river runoff to help better prepare for cleanup.

Chapter 7

This chapter primarily explains the importance of mapping change and provides the necessary logistical tools to create an easily digestible map utilizing different data. First, the author examines the various types of change that can be defined through geographics. He says, you can either map the change in location, which “helps you see how features behave so you can predict where they’ll move,” or the change in character or magnitude, which “shows you how conditions in a given place have changed.” For example, one mountain may shift a few inches a year due to plate tectonics, so scientists may be interested in plotting this information in GIS. Then, Mitchell defines the various methods of mapping change including time series, tracking maps, and measuring change. He states that time series are “good for showing changes in boundaries, values for discrete areas, or surfaces.” In other words, good for locations that are constant, or never move. Tracking maps are “good for showing movement in discrete locations, linear features, or area boundaries, which is like time series, but can include features for several dates and times. Finally, he explains measuring change shows “the amount, percentage, or rate of change in a place.” For example, you may measure change within a small village following a mudslide or a tornado to understand the full impacts of the natural disaster event.

Chapter 1 , Introducing GIS analysis

GIS is constantly changing due to the rapid evolution of new technology. GIS is evolving because people are finding new uses for GIS. It is becoming more than just mapmaking. GIS for analysis can be applied to many field to get the most accurate data and information. GIS analysis is defined as looking for patterns in your data and at relationships. Simply making maps is a form of analysis.  Steps important to analysis are listed: ask a question, understand the data, choose a method, process the data, look at the results. I enjoy lists and found this useful. Some parts are self explanatory. Understanding the Data requires finding information on what kind of data and how specific it is to determine how fit it is for the project. Looking at results includes stuff like deciding what information is helpful. Discrete: the feature’s actual locations can be pinpointed. Continuous: the features blanket the entire area you are mapping and aren’t pinpointed to one location.  Summarized data represents density of individual features within area boundaries. Categories are groups of similar things. Ranks put features in order. Counts are actual number of features. Amounts are a measurable quantity associated with a feature. Ratios show the relationship between 2 quantities. Categories and ranks are set number values within the given data layer. Calculating and summarizing are different. Calculating evolves assigning new values to features and summarizing involves using data tables to find a piece of data. This chapter contained a great overview of GIS and these were the points that stood out to me. I would be curious to see at the end of this course whether these concepts were the most important things in this chapter.

Chapter 2,  Mapping where things are

This sections covers the actual placing of articles on a map compared to the introduction found last chapter. Mapping the locations of individual features allows you to see the distribution of the feature as well as the patterns that may help mapping. It is important to create a map that shows features relevant to yourself and the audience. There are many things you can alter to help. Only included relevant data and have clear concise categories. Geographic coordinates and codes must be assigned; you will need to assign them if they are not in a GIS database.  You can map single features by repeating a symbol which may reveal patterns to your audience. You can choose subsets of your features to map. I enjoyed the example of  all crime vs. burglaries to help understand the concepts. Using different symbols can show different category within your data. You can adjust the size and range of your categories to adjust the way GIS displays your map. Keep in mind that the map needed to be discernable. Stick to less than 8 colors or symbols. Adjusting the grouping can help help keep the map clean and remain under 8 categories. Choose symbols with define shapes and colors. All of these are key to making patterns visible to your audience. I really enjoyed learning the different parts that go into making a map. This makes me view maps differently because I can imagine how simple it could be to manipulate data. I also am grateful for the opportunity to learn GIS somewhere where I can learn the ethics behind GIS as well as the application.

Chapter 3, mapping the most and the least

This chapter focused on mapping based on quantity associated with each feature. There was a lot of information present and was difficult for me to understand and summarize. It adds more information than mapping features. There are several options for displaying most and least depending on what type of feature you are looking at. Simply put, you can “map quantities associated with discrete features, continuous phenomena, or data summarized by area.” . Discrete features are defined as individual locations, linear features,  or areas. Next, this chapter discuses how the context you are mapping effects the look of your map.  . When exploring data you can map as many features as is helpful for you in pattern recognition. When presenting this should be streamlined and made ‘cleaner’.  Ratios are created by dividing one quantity. Averages are used to compare those with few features to those with many. Proportions show you how much of a whole each part represents. Densities show the concentration of features. Cases are created in 4 basic way natural breaks, quantile, equal intervals, and standard deviation. Which one use use depends on the data. Graduated colors and symbols are use similarly.  You can also use small chats such as a bar graph or pie chart. They can cause issues identifying patterns if not used in the right context. contour lines are used to show rate of change such as elevation or precipitations.  3d renderings can allow the audience to better understand the change of a continuous phenomena. Perspective can be influential when using 3d  models. This chapter was very definition heavy but I feel the concepts are easy to understand but hard for me to describe.

Chapter 4 mapping density

Mapping density shows you the highest concentration of a feature. By simply mapping features you could see patterns in density however density mapping allows for you to see the visual difference easier. They are most commonly used to map areas such as population. There are two ways to map density you can go based off of area or density surface.  each method has positives and negatives and it is important to pick the method based on your data. The chapter goes into detail about dot density maps and the proper way to display dots to be impactful but still effect in showing the data. I do not see the appeal in the dot density. Other methods seem better than others but hopefully going through this course I will understand the benefits of all types of modeling. Density surface is created using a raster layer. from my understanding it creates a new layer that overlays the gradient on the map. It is noted that this method takes more time. This process uses graduated colors and contour lines. The chapter goes into very specific details regarding the process behind making these density maps. I will likely use this chapter as a reference. My thoughts were quite scattered while reading this. There is a lot of information on may different aspects that I do not fully comprehend.

Chapter 5 of the book talks about mapping “what’s inside.” This is useful because it can help to monitor those occurrences, compare those occurrences with others, and conclude when and how to take action. Areas are defined by drawing boundaries and data can be found in a single area or several and discrete (identifiable) or continuous (seamless) features. Which method is used can be determined by examining what kind of information the user needs from the actual analysis. Some examples of this information may be lists, counts, summaries, or feature views. This chapter discusses three different ways of finding the things inside of an area. The first way is drawing a map that shows the area boundary and the features to see what features are within the boundary. The second way is by specifying the area boundary and features for a summary. The last method is separating the area boundaries and features into different layers, overlaying them, and having the system combine and compare to make summaries. This chapter next discusses how to actually draw the maps, talking about using/mapping locations, lines, discrete areas, and continuous features. Then, it talks about choosing the features that the user wants to use within a boundary, which can be done by the GIS. These results can then be compiled into a report or spreadsheet in many kinds of summaries, including the popular ones of count, frequency, and numeric attributes (sum, mean, median, standard deviation, etc.). Lastly, this chapter talks more about the method of overlaying, discussing the two big categories of using this method with discrete areas and continuous categories. The continuous way uses one of the two methods: vector (compares cross areas) or raster (compares cells). After reading this chapter, I feel more comfortable with the concept of using areas and their contents to draw conclusions and summaries when mapping. 

Chapter 6 of the book talks about finding what’s around a feature, which is used to determine the area that is impacted by an event. First, the book explains the importance of specifically defining the analysis, which includes possibly determining distance, travel to and from, cost, and planes (whether it includes earth curvature or not). Next, the user must ask what information is needed from the analysis, which could be a list, count, summary, or distance/cost ranges (may need inclusive rings that show relationships between totals and distances or district bands that compare distances to other attributes). Then, the chapter explains the three ways of discovering what’s nearby, which include straight-line distance (creates a boundary/selects characteristics at a set distance), distance or cost over a network (finds what’s within a manageable distance/cost), and cost over a surface (finds overland travel cost). This chapter then goes very deeply into using straight-line distance, talking about the potential of making and using buffers, just choosing features within a certain distance and the different ways to do/use that, using the GIS to find the distance between features and how to obtain/utilize the results, or creating a distance layer in the program and using it to create specific distance buffers. Next, the chapter talks about measuring over an entire network in the GIS, which means that the system finds all lines in a network within certain parameters. To do this, the user may have to specify the layer for the network, assign segments to centers, set travel specifications, choose surrounding features, and make the final map. Lastly, this chapter talks about finding cost in a geographic surface, which involves specifying cost, personalizing cost distance, collecting the information, summarizing the results, and creating the final map. This chapter was a bit more abstract for me, but I’m sure the concepts will be more clear once we’re using these skills. 

Chapter 7 of the book talks about mapping changing conditions or movement in order to predict future happenings, choose a method of action, and interpret the effects of some kind of policy. The first topic in this chapter is defining the analysis, which then goes into the types of change that can be mapped, which include change in location (discrete features and events) and change in character/magnitude (discrete features, data summarized by area, continuous categories, and continuous values). The chapter then moves on to the concept of measuring time, which can be mapped in one of three patterns: a trend (shows increasing/decreasing or direction of movement), before and after (shows impact of event or action), and a cycle (shows patterns in feature behavior). Time mapping can consist of showing the locations at multiple times or the data can be summarized. In both of these methods, the user must choose how many/which dates to include. Then, the user must determine what information they need from the analysis, whether that ends up being how much or how fast the data changed. Next, the chapter talked more about the methods of mapping change which are using a time series (uses snapshots), a tracking map (shows feature movement), or just measurements (shows difference in a characteristic). The book then explains these methods further, talking about ways in which each of them can be used to show change in both location and magnitude/character, methods in constructing the map itself, and how to examine/use the results. Finally this chapter concludes by talking about ways to report the results and methods in summarizing. This chapter was one that felt very straightforward. I found it useful that it showed ways to use each method as well as showcasing the pros and cons of each, which will be helpful when choosing what way to do things.

Chapter 1:

This chapter had 3 main topic, what is GIS analysis, understanding the geographic features and understanding the geographic attributes. It explained that GIS analysis is the “process for looking at geographic patterns within the data and the relationship between features.” This is done by framing the question or what information is needed. The question poised that creates the need for a map often decided how to approach the analysis. So you need to understand your data and then choose a method. From there process the data and then look at the results. This last step can help decide whether the information used is valid or whether you should return to step one and re-run the analysis with different data or a different method. For understanding the geographic features, the type of feature can affect the steps of the analysis process. The types of features are discrete, such as lines and locations that can be pinpointed. Continuous phenomena, which is like a temperature or precipitation and is given a value. Features summarized by the area are the counts/density of individual features such as population and number of things in a region. There are also 2 ways of representing geographic features, vectors and rastor. A vector model has a feature in a row on a table and the features are given a address with a x and y location in space. these features can be discrete, events lines or areas.  For a rastor model, the features are a matrix of cells in a continuous space, with each layer representing an attribute. Any type of feature can be represented using either vector or a rastor model but discrete and data summarizations by the area are usually represented through a vector model. For understanding the geographic attributes, the values need to be known. Categories, ranks, counts amounts and ratios are all attributes.  Categories group similar things together, ranks put features in order from high to low and are used when direct measures are hard or represents a combination of factors. Counts and amounts show a total number and is the actual number of features on a map. ratios shows the relationship between two qualities and rare made by dividing one quantity by another for each feature. For continuous and noncontiguous values, categories and ranks are noncontiguous while counts amounts and ratios are continuous values.

Chapter 2:

Chapter 2 focuses on why map thins, deciding what to map, how to prepare your data, making the map and how to analysis geographic patterns. Pertaining to the first question, mapping things can show you where action is needed, or what locations meet a criteria. For deciding what to map, you need to decided on what information you need for an analysis. Such as the location of the features in comparisons to a deciding factor like the example the book had, crimes compared to the police departments location. how the map will be used is also important because some features are not relevant to a topic and can muddy a maps purpose. For preparing the data, assigning geographic coordinates is something usually done via the data brought in, the same for assigning a category for the values. Making the map, there are many different types of maps, such as mapping only a single feature, such as only showing the roads or buildings. Knowing what GIS does with the locations of each feature and how it stores the location within the map. using a subset of features, this is more commonly done for individual locations. Mapping by category and displaying a feature by the type can be used. Choosing the symbiology of a map is also important as if you’re mapping individual locations using a single marker in a different color for each category of the locations can break of the map to be more legible. Changing eh locations to all have the same color but different shapes is harder to read and thus wouldn’t be recommended for this type of map. taking in to account how the map will be viewed also can help with the symbiology such as is it digital or a physical map on a poster. Analyzing geographic patterns is to ensure that the map presents the information clearly.

Chapter 3:

Chapter 3 focuses on why to map the greatest and lowest values, what needs to be mapped, how to understand the qualities within the map, creating classes, making the map with these in mind and looking for patterns. Mapping the extreme values can help people find what meets their criteria and to take action. or to see the relationships between locations. What to map is based on knowing what features you’re mapping as well as the purpose for the map. these factors will help decide how to present the features and qualities to see patterns in the map. Feature type and what is being explored within the data or presented in the map also help with what to map. Understanding the quantities of thing like counts and amounts which show total numbers are important for qualitative maps. Ratios for these maps show the relationship between two quantities and are useful when summarizing by area, with the most common ratios being averages, proportions and densities. Ranks are useful when direct measures are difficult or the quantity represents a combination of factors. Creating classes within a map groups values into their own symbols or being in the class. this requires a trade off between the presentation of the values are the generalization of said values. Mapping individual values present an accurate picture of the data when the features are not grouped together. but this requires the readers to understand more information especially if the map contains lots of values. Using the classes to group similar values features helps by assigning them the same symbol. you can do this by creating classes manually. Classes can also be created using a classes based on a larger set of features such as a population census. Making the map discusses that the GIS program gives you different options for creating your map such as graduated colors, graduated symbols, charts, contours and 3D perspectives. each have advantages and disadvantages based on the information they provide and the limitations of using such a option.  Map type is also important as it may show discrete lines or area and whether or not you have spatially continues phenomena’s that are used. Creating 3D perspectives are used most often with continuous phenomena and help viewers visualize the surface of an area such as the height and magnitude of the area. Looking for patterns helps to present that map more clearly and can be used to compare different parts of the map. The relationships between locations of features such as the highs and lows of values help understand how the phenomena behaves.

Chapter 4:

Chapter 4 features on a maps density, deciding what to map, the two ways of mapping density, mapping density for defined surfaces and creating a density surface. Map density show the highest and lowest concentrations of features and where. Deciding what to map helps to decide what method to use based on the information needed for the map. Two ways of mapping density show that you can map by defining the area or by density surface. Defined areas can be a dot or calculated a density of each surface. Density surface is usual created in GIS as a raster layer with each cell layer getting its own value providing more detailed information but requires more effort by the creator. Mapping density for defined areas, based on the two methods for mapping density. Calculation the density value for each defined areas. Creating the dot density map is a method where each area is mapped based on the total count/amount and each dot must be specified on its representation. The dots don’t represent actual locations of features. If there are individual features but want to map density summarized by defined areas, GIS can summarize features for each polygon area. Creating a density surface are raster layers that GIS calculates a density value for each cell layer.

Chapter 1:

This chapter really sets the table for the idealization and tenants of how you need to have when in the mindset of making a map, both physically and mentally. These two ideas are different from each other but also very important, because as it is made known by this section, simply having data to map is not all that is needed to start on the creation of said map.  Firstly, there are different types of physical data that can be used (vector and raster), which both can be used to represent most if not all types of feature types. Being comprised of X and Y coordinates, vector data is most usefully utilized in discrete features and area bound data, while raster data is most commonly utilized with continuous numeric data like elevation maps. Despite this chapter being very wordy with its introductions of the many types of features and approaches that can be done in mapping, I found it very interesting to look through, especially with the colored illustrations to compliment the text. It seems very elementary but showing how two different approaches at showing data can be done both in words as well as with pictures (especially when the one way of mapping something is very clunky or scattered) to compare them and see which is more advantageous for the end goal of the map was a great idea. I thought the final sections about attribute values was an apt summary of how you can play around with your data to make it accessible to the viewers. Many of these reminded me of the population project in GEOG 112, where we were given big census data and allowed to play around with it as much as we wanted, but eventually made to chop it down into digestible, readable data for the viewers. Utilizing ratios and counts/amounts is perfect for this, especially when there is so much raw data that you do not absolutely want to use every last piece of.

Chapter 2:

The beginning of this chapter jumps into deciding what to map, and from this answer, how to map such idea. While this is a rather personalized question to ask, it is quite important as it is really easy to map too many things and confuse the meaning of the map. I learned this from experience, especially when you are given a bunch of types of data from a specific area and want to provide your reader with as much of it as possible. It is here where you have to keep your specialized reason for mapping in mind, as the point and execution of your map will be most clear if you keep as many extracurriculars out of the map interface as possible; you would not want to confuse your reader from your main point. The part about categorical mapping was pretty neat, especially the part where it expressed that in general you should not exceed seven categories of data, since after seven it is apparently difficult to distinguish one from another. This is probably due in part to (1) there are only so many colors that can look totally different from each other with a background color and a separate color for boundaries and (2) seven may just be the arbitrary limit of a map having too much going on in terms of categories. Scale is also very important, which I learned from the GEOG 112 project, when working with categories of data. Having smaller scaled sections of data with many categories can be tricky, as sections that are similar in numeric value but in adjacent quadrants can look the same when they are not, especially if you are using a 2-color scale to distinguish all of the categories. Using the full range of colors in a small area of boundaries, I have also learned, can be less advantageous to the reader, as it may require more looks at the legend to distinguish the different categories as opposed to a 2-3 color scale.

Chapter 3:

The start of the chapter brought up an interesting point about how maps are made with different purposes. For example, if you are making a map to explore relationships between two things, you would limit the use of information that is not relevant and try to display the data in multiple different ways to show how deep the relationship is. On the other hand, if you are making a map to explore the results of a finding, utilizing all of the data in the result is most likely the best approach to show the full extent of what was tested and what was found. It talks later in the chapter about the different methods of splitting up or classifying categories via natural breaks, equal interval, and standard deviation. The first two I have heard about and used but I was unfamiliar with standard deviation being used in this way, as “each class is defined by its distance from the mean value of all the features”. Displaying data based on its distance from the mean seems very specialized, as I cannot recall any times where I have seen this done in graphic form. When in the making maps portion, they mentioned the use of graduated symbols when measuring volumes or numeric values in area. I always thought that graduated symbols were a strange choice when expressing the size of numeric values, since the size of a specific shape can be hard to quantify in my opinion. While having to constantly check a legend or key to determine what size relates to what, it can be hard to determine such size when there are too many categories of size, especially if the area in question has a smaller scale.

Chapter 4:

One of my favorite techniques used in density maps are the contour lines. I think that showing the rate of change across a surface of the highest densities is a really cool approach and one that is unique to many of the other methods that they mentioned like dot diagrams, color gradients, etc. A use for them that I am aware of is with isobars in determining the rate of change in pressure across a weather map. In this scenario, determining the rate of change is very important as high rates of change in pressure can allow storms and bad weather to permeate in these areas, making it very crucial to be able to map and identify these areas. Additionally with the methods of displaying density information, I think dot density maps are quite neat in its simplicity and straightforward idea in showing what places has higher density values, but I do think they can make a map a fair bit cluttered at times. The book mentions that you can try to avoid this by making the size of the dot small enough so that it obstructs as little of the boundary lines as possible, but  I still feel that even if the dots are small, they can still make the boundary lines confusing to follow, especially in spaces where the scale is small or if there are small areas of high dense areas near each other, like in a density map of a U.S. state’s counties. Counties with very high density will have a hard time being distinguished from one another from an eye that is not familiar with their placement on a map. Also, I think that density surfaces are really great tools to show density while preserving boundary line integrity, but the type of very precise locational data that would be needed to accomplish this makes the actual creation of such maps really specialized for very exact data. Map density area is a lot more generalized and can be done with more simple data, but it requires much less data processing, and it is gives decent ideas of where densities are located in a larger area of land, which might just be what a person is looking for as opposed to the exact regions of density increase within boundary lines.

Chapter 1:

The first chapter acted as an introduction to the book. The process of analysis was given in a detailed manner. I liked how the chapter said framing questions was the first way to start analyzing data. Understanding data, choosing a method, processing the data, and looking at the results were explained briefly as a part of the process. I liked the different types of maps under the Geographic Features Category to show maps summarized by area, discrete or continuous phenomena.  I thought the maps co-relating businesses with areas/zip codes were interesting because I have always associated GIS maps with disaster management or weather, so this felt new. I knew that Geographic features could be represented using vectors, but this was my first time coming across the “raster” method, which is the representation of a matrix of cells in continuous space. Most of the analysis in this method occurs by combining layers to create new layers with new cell values. The book also included important tips like using the perfect-sized cell instead of too large or too small of a size for a more precise map. I will keep this information in mind when I start making actual maps on the software. Geographic attributes were divided into multiple things like categories, ranks, counts, amounts, ratios, etc and even working with the data tables seemed very math-oriented and statistical than something more social sciencey than I previously assumed. There was a lot of calculation and selection used to summarize data. Overall, different concepts for different types of analysis’ were mentioned, and I found them useful because understanding them will help me get a better idea of what kind of analysis I would like to do. Also, I’ve been trying to find an intersection between technical and social sciences, and I’m trying to see what kind of doors GIS opens up for me there. 

 

Chapter 2: 

The second chapter focused more on the concept of mapping. It talked about how maps are prepared and bought into this world.  I’ve never had the chance to map stuff before, except for one data visualization project where I visualized the crime rates in each state in India. I like how the entire process is laid out and explained in a well-detailed manner. I feel like for someone with zero to little experience with mapping, this chapter can be helpful since it starts with understanding the location and what exactly we want to map and then goes on to prepare our data and how we can map single or multiple types or by category. Some sections specified how GIS can be used to make these maps more efficient. It was interesting to see the use of maps to quantify thefts, burglaries, and crime in specific locations. It also made me think about other places where we can use maps to resolve nationwide issues like this. Maps give you information that will help analyze further to find solutions.  A few things that my dorky self would enjoy doing while mapping is choosing symbols and colors(Also, the chapter makes use of pastel colors  for maps, so I find it very cute.) 

Mapping is usually looked at as something simple, however, the chapter mentions things like the usage of maps or maps that use eighteen zoning categories. The chapter also describes how ArcGIS provides base maps, which can be used as reference features for mapping. This will help me when I start working on the software. 

 

Chapter 3: 

The third chapter takes mapping into detail. Looking at the title — Mapping the Most and Least, makes me think that chapter will talk more about quantifiable skills required to make maps. I liked the business analogy used at the beginning of the chapter to explain why we need to map the most and least quantities. This chapter, just like the previous two chapters, had detailed instructions on specific map-making processes. It mentioned things like displaying areas using graduated colors while surfaces are displayed using contours or 3D view. The next page also included a splotchy green map that looked really cool. The chapter also included things that could potentially sidetrack us from the main task, like exploring data or presenting a map and how to explore data in a way to see emerging patterns and questions. Economic and statistical terms were used throughout, like counts, amounts, ratios, ranks, proportions, etc. All the terms were clearly defined, which was helpful for someone like me who has never been in an ECON class before. The chapter made use of multiple formulae to make sure that the data was accurate and precise.

The chapter noted that similar quantities should be grouped in one class together to make it easier for the student to make the map. Mitchell mentions various classification plans, namely standard deviation, quantile, and natural breaks, and their advantages and disadvantages. As I suspected before, the chapter’s primary focus was to explain how stats and math are used to create maps. 

 

Chapter 4: 

The fourth chapter focuses on mapping according to density, and similar to chapter three, it consists of various economic and statistical terms. It starts with explaining why map density is essential and can be used in multiple areas with a specific type of data. Density maps can be helpful when looking at patterns. It helps with areas with a higher concentration, so I’m assuming that people with no knowledge will also be able to decipher the maps. The author also mentions that its important to decide what to map and what kind of data will be used so that it is compatible with the style. The book mentioned two ways of mapping according to density — By defined area, where you calculate a density value for each area using dot maps, and by density surface, which uses the raster layer mentioned in the first chapter.  Each cell in the layer gets a density value based on the number of features within a radius of the cell. Different comparing methods and ways to choose them were mentioned in the book to make it easier for students when they start mapping. 

Like chapter three, this chapter also included specific class ranges and colors for ratios for shaded maps. The book instructs on creating different types of dot density maps on different scales of data. It goes further on how to calculate density values by converting density units to cell units, searching for radius, and using different calculation methods and contours.