Geography 291: Geospatial Analysis with Desktop GIS

Chapter 4

• Mapping the density of features lets you see the patterns of where things are concentrated.
• Density maps are mostly used to look at patterns instead of the usual locations of features.
  • Mapping density is especially useful when mapping areas like counties.
• GIS can be used to map the density of points or lines.
  • You can map the density of features 
• There are two ways of mapping density, by defined area and by density surface 
  • Defined area is density mapped graphically by using a dot map or calculating a density value for each area 
  • Density surface is created in the GIS as a raster layer 
• Density is calculated based on the areal extent of each polygon
• Some GISsoftware allows you to calculate density instantaneously
  • When creating the map you specify the value you’re mapping density for and the attribute containing the area
• A dot density map is a method where you map each area based on a total count or amount and specify how much each dot represents
  • Dot maps gives readers a quick sense of density in a place
  • A dot map simply represents density graphically 
• GIS can be used to summarize features or feature values for each polygon 
• There are many parameters that you specify affect how the gis calculates density surface like cell size, search radius, calculation method, and units.
  • Cell size determines how coarse or fine the patterns will appear. 

 

Chapter 5 

• Mapping inside an area allows you to monitor what’s occurring inside it, or to compare several areas based on what’s inside each.
  • To find what’s inside you draw an area boundary on top of the features.
• Finding what’s inside a single area lets you monitor activity or summarize information about the area.
  • Finding how much of something is inside each of the areas lets you compare the areas.
• Discrete features are identifiable and unique.
  • Listing them or a numeric attribute with them would allow easier comparisons.
• Continuous features represent seamless geographic phenomena.
• Continuous values: are numeric values that can vary continuously across a surface.
• GIS can be used to find out whether an individual feature is inside an area.
• Linear Features and discrete areas might lie partially inside and outside an area.
• Three ways of finding what’s inside 
  • Drawing areas: you create a map showing the boundary of the area and the features.
  • Selecting the features inside the area: you can specify the area and the layer containing the features, and the GIS selects a subset of the features inside the area.
  • Overlaying the areas and features: the GIS combines the area and the features to create a new layer with the attribute of both or compares the two layers to calculate summary statistics for each area.
• Overlaying areas and features: this method lets you find which discrete features are inside which areas and summarize them.

 

Chapter 6 

• Finding what’s nearby 
  • Lets you see what’s within a set distance or travel range of a feature.
  • To find what’s nearby, you can measure straight line distance, measure distance or cost over a network, or over a surface.
• Distance is one way of defining and measuring how close something is.
  • If you are mapping what’s nearby based on travel, you can use distance or cost.
• You can specify a single range or several ranges
  • If specifying more than one range, you can create either inclusive rings or distinct brands
• Inclusive rings are useful for finding out how the total amount increases as the distance increases. 
  • Bands are useful if you want to compare distance to other characteristics.
• Three ways of finding what’s nearby:
  • Straight-line distance: you can specify the source feature and the distance, and the GIS finds the area or the surrounding features within the distance.
  • Distance or cost over a network: You can specify the source locations and a distance or travel cost along each linear feature. 
  • Cost over a surface: You can specify the location of the source features and a travel cost. 
• To create a buffer, you specify the source feature and the buffer distance.
  • Once you’ve created the buffer, you can display it to see what’s within the distance of the source, or you can use the buffer to select the features that fall within it.

Chapter 4

The main focus of chapter four is about ‘density’, and how to map the density of features. Other questions looked at are why map density is important, deciding what to map, different ways of mapping density, mapping density in a defined area, and creating a ‘defined’ surface. The higher the density of something, the higher the values are. For example, the correlation between density and high values can show areas of business, population centers, and areas of crime. The chapter also asks if you want to map explicitly features, or the values of said features, with the chapter using businesses in a given area vs employees in a given area, both on the same map. The chapter also lists two primary ways to map density. The first way is by ‘defined area’ or a dot map. Each dot on said map represents a specified number of features, and the closer the dots are together, the higher the density of features in that area. Then there is mapping by density surface, which is referred to as a ‘raster layer’ though what a raster is is not explained. In a density surface map, each cell gets a density value based on the number of features within the cell. As opposed to defined areas, density surface maps provide the most detailed information but also require the most effort to create. The chapter also details how to calculate the density values in defined areas depending on the type of map. Calculations can also show the features closest to the center of the cell. Chapter 4 also emphasizes the importance of the units used depending on the map type and what is measured.

Chapter 5

The main focus of the fifth chapter of Mitchell details what is on the inside of certain areas of map. The layout is the same as other chapters and like chapter three it seems to go on for a while, repeating a lot of information. Chapter 5 also focuses on defining the analysis of a map, different ways of finding what’s inside the map, how to draw areas and features, selecting features within a given area, and the overlaying of areas and features. One reason Mitchell gives to map inside is to know whether to ‘take action’ or not, giving examples of a district attorney monitoring drug related arrests in proximity to a school. The chapter also talks again about discrete and continuous features which I will admit I had forgotten existed until reading this part in the chapter. Mitchell details the information needed from an analysis, be it a list, count, or summary. In addition to the information needed, the chapter also goes over if you should include or exclude areas which are only partially included or excluded in the map. Key in the chapter are the three ways of “finding what’s inside”. By drawing areas and features you can see which features are in and outside of the area, and all that is needed is a dataset containing the boundary of the area and another dataset containing the features of the area. The second method is selecting key features in the area in order to obtain a summary or list of features in an area or group of areas, or for finding things within a certain distance of features. The final method is to overlay both the areas and features, which can be used to find which features are in different areas or finding out how much of said feature is in one or more areas.

Chapter 6

The main focus of the sixth chapter is “finding what’s nearby”, or as explained, letting you see what is within a set distance of a feature, allowing you to monitor events in an area. The chapter also focuses on reasons for mapping what’s nearby, using straight-line distance measuring, measuring distance over a network, and calculating costs over geographic surfaces. This is again where the book starts to lose me with mentions and examples of calculations given that I am not good with numbers in the slightest, but I digress. One reason Mitchell gives for mapping what’s nearby is for emergency situations, specifically using an example of a fire chief knowing the distance of streets within a three minute distance of a fire station. Mitchell also asks if you’re measuring what is nearby as distance or cost, which is another confusing aspect. Despite reading the section over again, it still doesn’t make sense how you can map cost over a geographical area. Another question of measuring is if you are measuring a flat plane using the ‘planar’ method  or are you taking the curvature of the earth into account. The second method is substantially more difficult given that the curvature of the earth is not only uneven, but distorts maps and how they are viewed. For example, looking at the sizes of countries on a globe compared to their actual size on a flat plane. Measuring “what’s nearby” is outlined in three different ways, those being straight line distance which is exactly what it sounds like and is good for creating boundaries. The second method is distance over a network which is good for finding things within travel distance. The third method is cost over a surface, which I again don’t fully understand so I won’t try to explain or summarize it. Overall while parts of the reading are still interesting, I feel it becomes repetitive and tends to drag on much longer than it needs to.

Chapter 4

The fourth chapter of Mitchell was about mapping the density of features. I found this chapter of Mitchell particularly intriguing because I have an interest in density maps. I find these types of maps interesting because they are typically each to read and the reader is able to get a lot of information at a glance. According to Mitchell, a density map “shows you where the highest concentration of features is.” The chapter describes two ways that density is able to be mapped, defined area and density surface. When creating a density map by defined area, a dot map is easily used. With a dot map, dots are able to represent the density of a thing within a location summarized by defined areas. These maps lean more towards showing the data graphically instead of density features. When creating a density map by density surface, a GIS raster layer is typically used. Each of the cells within the layer is assigned a density value. When using this method, the result is usually a density surface or a contour map. This method is typically a lot more labor and time-intensive. When comparing the two methods, it is easy to point out when one method should be used over the other. A density map should be created by a defined area when the data is already summarized by area or can be summarized. A density map should be created by density surface if the data consists of individual locations, sample points, or lines. This type of mapping is best used if the mapper is trying to see the concentration of a point. One comment I have for this chapter is that Mitchell introduces the idea of a raster layer while describing creating a density map by density surface, however, he doesn’t explain what a raster layer is until later in the chapter. I feel like not knowing what a raster layer was until pages later caused me to struggle with the concept of density surface at first.

Chapter 5

The fifth chapter of Mitchell was about finding what is inside of a dedicated area of a map. Mitchell states that mapping the inside “let(s) you see whether an activity occurs inside an area or summarize information for each of several areas so you can compare them.” He then gives two reasons for why someone might want to do this: to show whether or not to take action on something and to see if there is more or less of something. Personally, I like how this chapter was laid out. The format of this chapter was like chapter three with headings appearing as questions to help the reader. The chapter focuses on the three main methods to map what’s inside of a dedicated area. In the beginning, it tells the reader what things to consider in order to find the best method for them. The things listed to consider are as follows, the data you want to collect, whether you want to map a single area or multiple areas, whether your features are discrete or continuous, the information you want to find out from mapping, and if you are using features inside the area or both inside and partially outside the area. Next, the chapter then gives a brief description of the three main types of methods for mapping inside. First, there is
drawing areas and features, where the person creating the map will make the map to have it show the boundary of the area and the features inside of it. Next, there is selecting the features inside the area. The person creating the map will dedicate an area and the layer containing the features, and then GIS will select a subset of the features within the area. The final method is overlaying the areas and features. The person creating the map will combine the area and features in a new layer along with attributes for both or they will create two layers in order to calculate summary stats. After the brief description of the methods, the chapter then dives into greater detail by comparing the methods and walking the reader through how to create them.

Chapter 6

The sixth chapter of Mitchell is about finding what is nearby. Mitchell states that “finding what’s nearby lets you see what’s within a set distance or travel range of a feature. This lets you monitor events in an area, or find the area served by a facility or the features affected by an activity.” One thing I found interesting in this chapter is the concept of costs. Cost is a way that you are able to measure distance while mapping. Measuring cost doesn’t necessarily mean that it costs a certain amount of money to get there, which is what I originally thought when the concept was introduced. A cost is sort of like a trade off. While a cost can be the expense it will take to get to a certain point, it also can have other meanings. For instance, according to Mitchell, a cost is time and effort expended. These types of costs are called travel costs. When time is a cost, it means that it will take you an increased amount of time to get somewhere by taking a certain route. According to Mitchell, an example of time being a travel cost is “it takes longer … for customers to get to a store through heavy traffic.” When effort expended is a cost, it is the wage of difficulty taken to get somewhere. An example given by Mitchell of effort expended is “a deer walking through thick underbrush versus open forest to reach a stream.” The concept of costs is so interesting to me because I never would have considered that these types of ideas would be used when mapping. I think that it is cool that as a mapper, you have to think about the different trade offs people will have to make while traveling a specific route.

Chapter 4- 

Mapping density is a good way to create and generate maps. This type of map lets you use different features to clearly see the data the map is trying to portray. Every map at the beginning of this chapter was showing how density maps can be created. They are all showing density, but in different ways. There are two different ways to map density, by defined area or by density surface. But making this type of map also has its drawbacks. Dots being too big on a map may crowd the map so you cant see certain areas or important lines. 

Different shades of the same color is the easiest way for me to see density patterns. Using different colors for population density is a great way to see where the majority of the population is located on the map. This section was full of different types of maps all geared around density. The most important thing to remember when using color is to use the same shade. With the same shade, people can easily decipher what areas are more dense than others, using the shades. If you just use random colors to represent the different densities, people will have to keep looking at the key to try and figure out what density relates to the color. 

It’s interesting to see how each map is so similar, yet different in its own way. This chapter really helped me understand how to demonstrate density in a map. There is no one right way to do it. Each data set needs a different way to construct the map to fit with the data. There were a lot of different ideas coming together in this chapter. 

Chapter 5- 

There are so many different ways of mapping inside of an area. The forest few pages of this chapter kind of go over some examples and how they might look. The second example that the book gives is a great way to look at streams and the environment and try to figure out how water affects certain plant species. The majority of the steam is surrounded by forests. The urban areas are mostly surrounded by agricultural land. This tells the person looking at the map that agricultural land is usually around people’s houses, like urban areas. 

Discrete features of a map are unique and identifiable. They are very easy to list or count. Some of these features are addresses, streams, pipelines, or parcels. These features give clear representation of an area. They are well defined on a map and can be easily spotted and made. Continuous features extend over a continuous area. They are not individual points, but areas. Some examples of continuous features are elevation, temperature, vegetation, or population density. Both of these two types of features are important to determine different types of maps and map needs. 

The comparing methods chart on page 147 of the book was very helpful because it summarized all of the different types of methods in one spot. It’s easy to see the three different methods, and which one to use for a certain type of map. Drawing areas and features is easy, but you can’t get the information from inside. Selecting the features is good for getting information inside an area. Overlaying the areas is good for finding displays within several areas. This chapter gave a different perspective on maps with all of these different features and looking inside. 

Chapter 6- 

Mapping what’s nearby offers many advantages to make the mapping process go easier, as well as looking at the map. Mapping nearby areas adds a separate layer to the map, meaning more information and knowledge can be obtained from looking at the map. The map on page 183 truly needs the streets to be added to the map to determine more information from the map. This map shows a fire station and the nearby streets surrounding the building. Its important to add more streets away from the fire station to determine the best route for a fire truck to get to a certain house, or to see how many streets and houses a certain fire station has to look after. Straight line distance is a good approach for creating a boundary around a certain area. All you need to create this is a layer containing the source feature and a layer containing the surrounding features. This process is pretty easy and quick, but it only gives a rough estimate of travel distance. 

This chapter was helpful in digging down into the details of how to create a perfect map using GIS. Every map is different, so there are different tools to use in order to get your map looking the way you want. Different features and tools do different things, so it’s important to familiarize yourself with the basics before creating a map.

Chapter 4: Chapter four discusses mapping density, which is useful for displaying where the data is most concentrated. Displaying the density can help identify specific areas with the highest values, such as population, businesses, or crimes within square miles. You can map features which are the number of businesses or people in an area or you can map feature values which refer to the quantity of something for each feature such as the number of workers at each business. One way to display density is by using dot maps where dots represent a specific number of a feature and how close the dots are together represents a higher density and dots that are distributed further apart represent lower density areas. Surface density can be shown using a raster layer where lower-density areas are shaded in a lighter color and higher-density areas are shaded in a darker color. You should only map using surface density if the data is specific locations, sample points, or lines. However, only map density should be used if the data is summarized by area. ArcGIS allows you to map density without needing to do prior calculations, which is very useful and efficient. ArcGIS also makes it easy to make a dot density map by automatically adjusting the number of dots when the amount each dot represents is defined. It’s important to pay attention to cell size, search radius, calculation method, and units. Cell size determines how smooth the appearance of the pattern is. Smaller cell size allows for smoother appearances but can lead to longer processing times and take up storage space. A cell size between 10 and 100 cells/ density unit is best. Search radius shows broader patterns when it is larger and more localized patterns when smaller. Calculation method is how the cell values are calculated. Simple calculation includes features in the search radius of each cell. Weighted calculation shows features closest to the center of the cell. Units are important because the appropriate unit should be chosen based on what is being mapped. Using larger units is better for showing features further away while smaller units are better for more localized features. 

Chapter 5: Chapter 5 explains how to tell if certain features or activities occur within a certain area or not. The reasoning behind this was fascinating. Mapping what is happening within an area can help understand what issues certain areas may struggle with and potential reasons that certain areas may have these issues. I’m still a little confused about what continuous features are referring to but based on the explanation in Chapter 5 I think it refers to features that can change over time such as elevation and vegetation type. Discrete features are countable and unchanging over time such as locations of crimes or streams and roads. To find out what is inside a certain area or boundary, you can use three different methods. One option is drawing the boundary and identifying what features are within those boundaries. Another option is making a boundary and then selecting a layer that has specific features, which GIS can use to find subsets of those features in that specific area. This is most useful when you want to summarize the features inside an area. The last option is a little confusing to me. I interpreted this method as GIS using the area and specified features to make a new layer that displays only the features in that area. I think that is how it works, but without doing it in GIS I’m not completely sure that is how it works. It seems that using GIS to make a new layer allows you to find features within an area and information about the features. Drawing and counting the features tells the number of features but doesn’t give additional information about the features. Choosing the features within the area gives a summary of what’s inside the area but doesn’t provide specific details about what’s inside the area. However, making a new layer with GIS is best for multiple areas while the other options are best for when you are analyzing only one area. GIS allows you to get a report on certain features which you can use to make a statistical summary that can be used to compare features within areas. 

Chapter 6: Chapter 6 explores how to map what is nearby and why this might be useful. Mapping certain things near a certain feature can be useful, especially for gaining info and preparation. For example, knowing how many families are within 20 minutes of the hospital allows the hospital to prepare by knowing how many employees should be staffed to help the nearby population. You can measure what is nearby based on distance, such as what is within a 50-mile radius, or by cost, such as time or gas money per mile. Cost is more useful when basing what is nearby on travel, which makes sense because one house may be a mile from the hospital but can get there within 4 minutes while a house that is ¾ of a mile is 6 minutes from the hospital due to traffic and roads. You can use different ranges to see what is nearby in different distances or costs from the feature. Inclusive rings can be used to see how an amount of something nearby changes as the distance increases. Distinct bands on the other hand compare how the range closest to the feature, 500-1000ft compares to the range furthest from the feature, 1000-2000 ft. This could give information about if the location of the feature is in the best location based on what is nearby. For example, more crimes may occur in the further range than the closer range, which would mean that it would take longer for the police to get to the scene. This could help the police prepare by sending more patrol cars into the further range to reach the scene faster. Different methods to use to measure what is nearby are straight line distance, distance or cost over a network, and cost over a surface. Straight line distance makes a boundary a certain distance from the feature and IDs what is near the feature within the boundary. Distance or cost over a network uses a certain distance or cost, like time, from the feature to see what is nearby the feature in that range. I don’t understand what cost over a surface is referring to, however. I think it might be referring to the amount of time it takes to get to a feature based on the surface, such as hills or flat surfaces that could affect how long it takes to get to the feature. 

Charlie Hornacek

C1

The initial exposure to GIS in Chapter 1 provides a foundational understanding of its processes. The step-by-step breakdown of GIS, akin to the scientific method, introduces you to the generic process involved. The distinction between discrete and continuous features on GIS maps is explained, along with their representation using vector and raster models. along with the concept of attribute values, categorized into five types, adds depth to the understanding. The chapter concludes with a discussion on data tables, emphasizing the practical aspect for better comprehension.

C2

Chapter 2 talks about the significance of mapping within GIS analysis. The chapter emphasizes that maps can be powerful tools for recognizing patterns and addressing specific questions. Different mapping methods, such as mapping with a single type of method or mapping by category, are explored. The chapter provides insights into the importance of understanding the audience when creating maps and the challenges associated with choosing symbols and determining map size. Overall, it underscores the practical aspects of mapping within the GIS framework.

C3

Chapter 3 builds on the mapping concepts introduced earlier, focusing on mapping quantities and classifications. It revisits the notions of discrete and continuous mapping, along with a detailed exploration of attribute values like counts, ratios, amounts, and ranks. The introduction of standard classification schemes, such as natural breaks and standard deviation, adds complexity. The chapter also talks about the trade-off between accurate representation and generalization for pattern recognition, emphasizing the importance of dealing with outliers in the mapping process.

Chapter 1

Introducing GIS Analysis

This chapter is informative when it comes to understanding GIS analysis, along with geographic features and attributes. It described the process of GIS analysis as looking at geographic patterns in data and the relationships between features. There are various methods to this which can look simple or more complex. I like how the reading broke up the different parts of the analysis process including; framing the question, understanding your data, choosing a method, processing the data, and then looking at the results. It was also interesting how the book pointed out that when it comes to geographic features, it is important to note that the type of feature you are working with will affect all the steps of the analysis process previously mentioned. These types of features can look like discrete features, continuous phenomena, or even features summarized by area. These are important to break down because I can see how foundational these features are to GIS analysis in enabling understanding and supporting applications. Finally, geographic attributes identify what the feature is and either describe or represent some magnitude associated with it. Some attribute values can look like categories, ranks, counts, amounts, and ratios, and it is crucial to know which one you are working with because this changes the type of analysis you are doing with GIS. 

 

Chapter 2

Mapping Where Things Are

This chapter was helpful in understanding the purpose of mapping where things are, deciding what to map, how to prepare your data, how to make the map, and analyzing geographic patterns. It was unique to me that the reading specifically pointed out the purpose of mapping where things are. You do not typically think about this broad of an idea but it makes sense now why it would be important to remember why people use maps so you can explore causes for the patterns you see. Deciding what features to display and how to display them can be done by reflecting on the information you need and what the map will be used for. It is interesting how the level of detail needed to be displayed can change depending on the purpose of the map. Preparing the data for the map can be done by assigning geographic coordinates and category values. One thing I noticed is how tedious it must be if your data is not already in the GIS database. Entering it by hand and giving location information like street addresses, or latitude-longitude values would take up a lot of time. When the reading discussed how to make the map itself and all the types that can be used, I appreciated all of the examples and pictures that were included. It helped me gain a better understanding of what the results might and probably should look like when using GIS. Finally, analyzing the geographic patterns that are presented is allowed by distinctly given information. 

 

Chapter 3

Mapping the Most and Least

Chapter 3 talks about the use of mapping the “most and the least” and why you should do this. It gives readers a better understanding of what you need to map, quantities, how to create classes, and how to make a map while looking at the patterns it displays. This chapter went into more detail about things previously mentioned and learned in the first two chapters which I appreciated. Mapping the most and the least was a concept I had never heard of before. From the text, I understand this as the process of mapping features based on quantities which is described as adding an additional level of information more than just mapping location and features. Again, the features you are mapping are important as well as understanding the quantities you are mapping. The reading says quantities can be counts or amounts, ratios, or ranks, these reminded me of the attribute values explained in the first chapter. This helps you decide on the best way to present your data. Creating classes was the next section that stood out to me, deciding whether to assign each specific value its own symbol or to group the values into classes. Finally, the author’s explanation of making a map was again supported by a good amount of example maps that presented various ideas and approaches and this was helpful for me. It was really cool to see the 3D maps and all the factors to consider such as viewer location, z-factor, and the light source. Overall, I felt like this chapter covered a lot of things that were already discussed in the first two chapters, but in some ways, it was a good overview and in other ways, it was helpful to see the topic or idea explained more in-depth. 

Chapter 1

• Because GIS has been around for such a long time the tools and technology that use it have evolved significantly. The number of people that are familiar with GIS has also increased along with the usage.
• The most common uses of GIS seem like they could be used very broadly for a wide variety of fields. I would be interested in seeing an example of each of these uses, particularly the ‘finding what’s inside’ point because I am have a little difficulty imagining what this could be applied for. Maybe what species is inside a geographical region?
• GIS is described as being a process for observing patterns and relationships in features. It does so through the construction of maps or models.
• The way working with GIS is described sound very similar to the way conducting a scientific experiment is; Start with a question, choose methods, gather information, and observe and analyze the results.
• As I was reading I did have a question of the definition of a ‘parcel’ because it was brought up many times and used in a way that I was not familiar with. After a quick search I found that it was simply an area of land with clear boundaries, often split off from a larger chunk. This made the word make much more sense in the context of the book.
• I think the idea of continuous data/ phenomena showing similarities between areas rather than exact information is interesting. It’s seeing more of a relationship between areas that you may not be able to observe as easily without the visual, such as simply using a table.
• Summarizing data and mapping discrete features should use the vector model, and continuous numerical values should use the rester model.
• Categories and ranks are not continuous values because they are assigned one set, whole number. Contrarily, counts, amounts, and ratios are continuous values because they are not assigned a set number and can be anywhere within a range.
• The process to select features seemed a little technical at first, but this section of the chapter seemed to make it make sense and acted as a helpful guide.

Chapter 2

• The first few pages of chapter 2 seemed a little redundant. It established that mapping is important and locational information has many uses across a variety of fields, which is something that the reading we did for last week also elaborated on.
• It’s important to remember that when you’re making maps you should assign geographical coordinates to features and possibly category types as well.
• Mapping by subsets or mapping by whole features/categories can be beneficial in identifying patterns that may not have been observable using the opposite method (they both have valid uses).
• The connection between recommending a maximum of seven categories and the human ability to easily identify seven colors is pretty neat. Having a cut off to ensure clarity also seems like it could prove useful keep in mind for future projects (keeping in mind there seems to be a sweet spot in between having not enough categories and leaving out information and having too many that it gets confusing).
• You can group categories by either providing each category a detailed code and a general code or by creating a table with a detailed code and general code which can then be combined with the feature database table to be displayed using the general code. The second method make it easier to adjust the category groupings. The third method is to use a symbol for each general category, which can be reused if needed later.
• The issue with using symbols is that they are harder to separate than points using color, especially if the shapes are small. I would imagine that combing shapes and color variations may be an even more effective way of distinguishing features.
• ArcGIS provides basemaps that you can use that contains grayed-out reference buildings and landmarks for you to overlay your information on top of.

Chapter 3

• One of the first things I noted was how many examples there were in this chapter. I think it will be helpful to see all the different methods of mapping quantity – through contours, summaries of areas, and gradating colors, for example- that you can use choose from to most accurately and legibly display your information.
• If the areas you are summarizing vary in size you should use ratios (averages, proportions, or densities) rather than counts to be able to accurately observe patterns. This seems like important information, especially since skewed data can become a major problem and fuel misunderstanding of an issue or piece of information (can do more harm than good, despite the intentions).
• The concept of ranking seems intriguing to me, especially when it comes to things that are more subjective like the provided example of the scenic value of a river. What factors are used to determine the ranking? Though this may be helpful to some, what’s the determining factor of the rankings that makes it widely accepted as a ‘correct’ ranking?
• A lot of sections in this chapter appear to be ones taken almost directly from other chapters (ex. river ranking example, business example, and even several paragraphs explaining the relativity of ranks) so it was a little redundant at times.
• Natural breaks (classes are based on natural groupings of values), Quantile (Each class contains an equal number of features), Equal Interval (high and low values of each class have the same difference between them), and Standard Deviation (classes are based on their variation from the mean) are all ways to classify information. They each have their own strengths, weaknesses, and uses. This section of the book appears to be very helpful in determining which scheme to use based on a chart your data produces.
• Graduated symbols, graduated colors, charts, contours, and 3D perspective views are all map formats that you can choose from to effectively present your data. Similarly to the classifications, each map style has its own best uses, advantages, and disadvantages, but it mostly varies based on which type of information you would like to present.

Shaw Week 

Chapter 1

 

• GIS is an acronym for Geographic information systems
• GIS has grown immensely since the creation of it, spatial scientists realized its potential and now helps analyze most world issues 
• While spatial analysis has made great strides in advancement and accessibility learning the basics is still required to get a grasp on how to use tools
• GIS analysis is a way of looking at data and geographical patterns and finding relationships between them. 
  • Starting each analysis by doing something as simple as forming a question and finding an area where you want to explore.
• Types of features in GIS
  • Discrete Features: locations and lines, the actual location can be pinpointed 
  • Continuous phenomena: entire area between boundaries, no differences in soil, land,vegetation.
• Geographic features can be represented in GIS using two models of the world vector and raster
  • Vector: Each feature is a row in table, and feature shapes defined by x, and y locations in space.
  • Raster : features are represented as a matrix of cells in continuous space, each layer represents one attribute.

 

• Map projections and coordinate systems are all the data layers being used should be the same in map projection and coordinate systems. 

 

Chapter 2 

• Mapping is used to see what, or where an individual feature is.
  • This can help show an individual where they need to take action/ what areas meet your criteria you are looking for
• • This map allows wildlife officers to track the behavior of bears and assign officers to spots of need.
• There are many features for different layers.
  • Each feature on the map needs a location in geographic coordinates 
  • The GIS stores the coordinates that are saved and draws the features.
• Using a subset of features allows you or the user to narrow down the the category value to something more specific or even make the range more broad
• Mapping features by category can provide understanding on how a place functions
• When showing categories on a map you want to only go up to 7 because most people can distinguish up to 7 categories on a map. 
• In smaller areas that are being mapped, individual features are easier to distinguish, so more categories will also be easier to distinguish

Chapter 3 

• People map where the most and least are to find places that meet their criteria and take action, or to see the relationships between places. 
• To map the most and least you map features based on a quantity associated with each
  • Adds an additional level of info beyond mapping the locations of features
• To map the most and least you assign symbols to features based on an attribute that contains a quantity.
• Ratios show you the relationships between two quantities, and are created by dividing one quantity by another, for each feature. 
• Proportions show you what part of a whole each quantity represents. 
  • To calculate a proportion, you divide quantities that use the same measure. 
• Densities show you where features are concentrated.
  • To calculate density, you divide a value by the area 
• Ranks put features in order, from high to low. 
  • Ranks are useful when direct measures are difficult or if the quantity represents a combination of factors

Chapter 1:

Overall, it is quite interesting to view GIS from an introductory standpoint. Since I know very little about what GIS actually is, it is quite nice to grasp the basic background behind what GIS is. The chapter first starts off with the generic process of what GIS entails. The simplistic steps behind GIS remind me of the steps found within the scientific method. The chapter then goes into the types of geographic features found within the GIS maps. Discrete features are the features on the maps that can actually be defined, which are generally represented as dots or lines. Continuous features are a little more complex to me, but they seem to be features that can be measured pretty much anywhere. There can also be features that can be summarized by area, which is a more density based data. The chapter then goes on to explain how geographic features can be represented. The first way is the vector model, which seems to be a more discrete method, which seems to pinpoint exact points and areas by using coordinates for instance. The raster model seems to be a more continuous representation, where there are layers representing the entire region of the given map. Overall, the differences between vector and raster models seem to have some overlap between them and therefore can be quite confusing. The chapter then talks about attribute values, which relate to geographic features. The five attributes (categories, ranks, counts, amounts, ratios) all make sense to me. The chapter then closes off with understanding the use of data tables. The three features that you use for the data tables are selecting, calculating, and summarizing. Overall, this part seems quite complicated, and I think that actually practicing it will make it easier to understand. 

Chapter 2:

This chapter talks about the importance of mapping, and the process of how to undergo mapping through the GIS software. Personally, I find maps interesting, which is one of the reasons why I took GIS. From what I know about maps, they tell you where places are and what unique features are present in different locations. However, I find it interesting that GIS can use maps to help pinpoint certain areas that need particular attention. The chapter talks about the process of mapping. The questions that it asks seem similar to the questions found in chapter 1, which takes the process as a step by step methodology. With using GIS, there are many ways that one can map their data. Mapping with a single type method can show simplistic and universal features, which helps those find a distinct pattern. Another mapping process is through mapping by category. This adds a key to help distinguish different areas found on a map, which helps to create an idea of where different regions are located. Also when it comes to categories, you want to make sure that you don’t have too many,or else it becomes complicated for the reader. If you need to have a large amount of categories, then you might just want to generalize the categories to make things more simplistic. It is also important to know what symbols to use for defining each category in your key. Overall, the purpose of mapping with GIS is to help one analyze certain patterns going on with their data. It can be as simple as zooming in or out or removing certain features on your map that will help you pinpoint certain patterns. 

Chapter 3:

This chapter talks about mapping the most and the least, which I honestly had no idea what that meant prior to reading this chapter. However, I have learned that it is a process of mapping that helps researchers correlate patterns or find areas that need to take action. Basically, it is diving deeper into the general ideas of mapping that were discussed in Chapter 2. It also takes in certain ideas from chapter one, as the beginning of the chapter talks about discrete and continuous mapping, along with ideas from the five attributes. Although this information was a little on the repetitive side, it was still good to relearn the information, along with understanding the importance of it to the overall idea of the chapter. After the review session in the beginning of the chapter, it talks about how to properly represent the data on a map. Using counts, ratios, and amounts would generally yield maps that show different classifications. The overall idea of using classes for mapping made sense to me. However, what was a completely new concept was the use of standard classification schemes. There are four of these schemes, which consists of natural breaks, quantile, equal interval, and standard deviation. I have only heard of one of those, and the other three seem a little confusing for me to fully understand what they mean. However, it was easier to understand the overall methods in choosing what classification schemes to use depending on what data you have. The end of the chapter discussed other important aspects, such as determining how many classes you need, and how to deal with outliers.