Geography 291: Geospatial Analysis with Desktop GIS

Chapter 4 talked about map density and its variables and when it is important to use it. I found it helpful the way it broke down what to map using density, the two ways of mapping density, mapping density concerning defined areas, and creating a density surface. The book talks about how density maps are useful when looking at patterns rather than locations of individual features and gives you a measurement of density per area, so comparing areas is done more accurately. Deciding what to map can be tricky though because density maps may not be useful in certain situations. I liked how the reading brought up that you should think about the features you are mapping and the information you need from the map before making the map itself. A concept I thought was interesting was the difference between map features and feature values. A map feature could be an example of locations of businesses where feature values could be the number of employees at each business. This distinction was helpful when thinking about the purpose of the map you are making. Mapping density by area is useful when you have data or lines or points that can be summarized by area resulting in a shaded fill map or dot density map. This is an easy process but is not as precise especially for large areas. Creating a density surface is useful when you have individual locations, sample points, or lines resulting in a shaded density surface or a contour map. This requires more data processing but can give a more accurate view of the centers of density. It was interesting to see how GIS plays a role in creating a density surface to make a running average of features per area resulting in a smoothed surface.

Chapter 5 discussed mapping what is inside an area to see what is happening there compared to other areas in order to see where there is more or less of something. The book goes into explaining the three ways of finding data for the inside of an area; drawing areas and features, selecting the features inside an area, and overlaying areas and features. Drawing areas and features create maps showing boundaries that can be used to see which features are inside and outside a specific area. This approach can show and use locations, lines, areas, and surfaces. Another way to find data is by selecting the features inside that area to get a list or summary of features inside an area or within a given distance of a feature. This approach shows locations, lines, and areas to get information about what is inside a single area rather than information about what is in each of several areas. The last way of finding data for the inside of an area is overlaying the areas and features to find out which features are in which areas, to give a summary of how many by area. Areas and features are combined through GIS to create a new layer showing attributes of both where they can be compared to calculate summary statistics for each area. This approach uses locations, lines, areas, and surfaces making this way good for displaying what is in each of the areas, but it does require more processing. 

Chapter 6 discusses mapping data within a set distance to identify the area and features inside that area that are affected by an event or activity. This approach is effective in finding what is within a set distance to monitor activity in the area. Throughout the reading of this book, I have noticed how helpful the examples are that it gives. One example was a state forester monitoring logging that could use this method to make sure logging does not occur within a 100-meter distance from streams. This chapter also goes into detail about how to define your analysis, the three approaches to this method, using a straight-line distance, measuring distance or cost over a network, and calculating cost over a geographic area. To define your analysis there are three ways to get an accurate measure of what is nearby. This includes using straight-line distance to create a boundary or selecting features within the distance around a source. This is a pretty quick and easy approach but it can only give a rough estimate of travel distance. Measuring travel distance or cost of a location over a fixed infrastructure is achieved through GIS finding segments of the network that are within the distance or cost. This approach gives a more precise measurement over a network but requires an accurate network layer. Looking at costs over a surface is another method that can measure overland travel and calculate how much is within the travel distance. This allows for combining several layers to measure over-land travel costs but requires more data preparation to build the cost surface. 

Chapter 4-

Chapter 4 discusses mapping the density of features, why to do it, and how to do it, so you can more accurately compare areas and know if certain areas fit your criteria. The first subsection, “why map density,” describes how it shows you where the highest concentration of features is and how it’s good for looking at patterns in features. If you have multiple features on a map, or when you’re mapping areas, mapping density can help to differentiate easier. “Deciding what to map” asks you to consider what kind of data you have, if you want to map features or feature values- feature values being the number of employees at a business vs. the location of businesses, for example, since the two can create different patterns. “Two ways of mapping density” describes mapping density by defined area- by mapping it graphically, using a dot map (which doesn’t actually show exact locations just the density of features in an area), or by calculating a density value for each area, and by creating a density surface- each cell in the raster layer gets a density value, typically if you have individual locations, sample points, or lines. The next two subsections go into extreme depth on how each method works, how to do it, and what the GIS does. 

Chapter 5- 

Chapter 5, “Finding What’s Inside,” describes why you should map what’s inside, defining your analysis, ways of finding what’s inside, drawing areas and features, selecting features inside an area, and overlaying areas and features. The first subsection, “why map what’s inside,” states that you can look at what’s happening inside an area, or compare what’s happening in several areas based on what’s inside. You can know whether to take action by observing one. “Defining your analysis” describes how depending on your data, you can either draw an area boundary on top of the features, use an area boundary to select the features inside and list or summarize them, or combine the area boundary and features to create summarized data. The subsection goes in depth on what you need in order to make a decision and why. “Three ways of finding what’s inside” describes drawing areas and features as a way to find what’s inside- creating a boundary of an area and features to see what’s inside and out, selecting the features inside the area, and overlaying the areas and features- the GIS combines the area and the features into a new layer or compares two layers, and the subsection also compares each method and what features best suited for them. “Drawing areas and features” describes the actual process of finding what’s inside, by making a map to see what features are inside the area either using locations and lines, discrete areas, or continuous features. “Selecting features inside an area” is a method where you specify the features and the area, then highlighting selected features on a map and putting them into a data table, or can summarize an attribute associated with the features. “Overlaying areas and features” is a method for discrete features or continuous ones.

Chapter 6-

“Finding What’s Nearby,” talks about how this lets you see what’s in a set distance or travel range of a feature to monitor events in an area or find an area served by a facility or the features affected by an activity. The first subsection, “why map what’s nearby,” talks about how finding what’s in a set distance identifies an area and the features inside an idea affected by an event or activity. “Defining your analysis” describes how in order to find what’s nearby, you can measure straight line distance, measure distance or cost over a network, or measure cost over a surface, and how the information you need from the analysis will help to choose the best method. “Three ways of finding what’s nearby” goes more in depth about the previously mentioned methods, what each is good for and what you need, and how to choose what method works best for you. “Using straight-line distance” is the simplest way of finding what’s nearby, by either creating a buffer to defined a boundary and find what’s inside it, select features to find others within a given distance, calculate feature to feature distance to find and assign distance to locations near a source, or create a surface to calculate continuous distance, and each method is discussed in depth. “Measuring distance or cost over a network” is a method where the GIS identifies all lines within a given distance, time, or cost of a source location, by specifying the network layer, what the GIS does, assigning street segments to center, setting travel parameters, specifying more than one center, and selecting the surrounding features to make the map. “Calculating the cost over a geographic surface” lets you find what’s nearby when traveling overland by creating a raster layer with the value of each cell being the total travel cost from the nearest source cell, and how and why to do this.

Charlie Hornacek

Chapter 4:

In Chapter 4, the focus is on mapping density and the various methods to achieve this. Density mapping is crucial for identifying patterns and groups within a given space, rather than analyzing individual data points. One approach discussed is mapping by defined areas, using dots to represent features. However, to avoid clutter, dots can be redistributed within specific areas, offering insights into which areas are more densely packed. Alternatively, density surface maps, utilizing raster cells, measure the number of features within a certain radius, assigning values and colors based on the concentration. The chapter also emphasizes the importance of choosing appropriate class ranges for natural breaks and quantile methods, which may seem exponential or arbitrary.

Chapter 5:

Chapter 5 delves into mapping areas, aiming to determine the best locations for specific purposes or understand the proximity of one element to another. Two main types of values, discrete and continuous, are assigned to features. Discrete features are clearly separated, while continuous features form a continuous path. The chapter explores methods to find what is within an area, such as drawing areas/features, selecting certain features, or overlaying areas/features. Each method has its applications, whether for firefighting strategies or legal considerations like property lines. The chapter highlights the versatility of mapping based on what’s happening inside an area, providing valuable insights for various applications.

Chapter 6:

Chapter 6 focuses on mapping things within a certain distance or time of a location, taking into account the complexity of factors like transportation infrastructure and terrain. Straight-line distance, buffer techniques, and the consideration of Earth’s curvature are discussed. The chapter introduces the concept of buffers around lines or shapes, offering flexibility for different classes of points/lines/shapes. The ability to determine distances across networks and analyze travel costs, especially for roads, adds a practical dimension to spatial analysis. The chapter also touches upon the simplicity of the algorithm for determining distance across networks, emphasizing the importance of accounting for real-world factors in mapping.

Chapter 4.

 

This chapter covers mapping density and the process of deciding how to do so. The primary use of density mapping is to determine patterns and groups, rather than analyze individual data points. Density is mapped by finding the amount of something within a consistent unit of space. It could be features or feature values, which will often present different results and patterns. 

There’s a few different methods to mapping density.

One of the ways of mapping density is mapping by defined areas. Typically, you could map features on a surface using dots, where each dot represents 1 feature. In certain scenarios, however, this can become too cluttered to discern some important patterns. Instead, the dots could be defined by certain areas (legal borders, zip codes, etc.) and then randomly redistributed throughout their area, which gives a good sense of which areas are more densely packed with this feature. This can also be done by adding each feature in an area and assigning ranges of number of features to a colour, then give each area their respective colour based on this range. 

Another way is density surface maps. This is a method using raster cells instead of other defined areas like what would be with vector boundaries. Density surface takes each raster and measures how many features fall within a certain radius of that raster, then assign a value (and typically colour) to it based on the amount. That radius is called the “Search Radius.” Often, the search radius is weighted so that closer points to the cell have a higher value than further ones. I’m assuming that it uses a Gaussian function for the weighting, or at least an approximation of a Gaussian function. This is inherently similar to the Kuwahara filter, which is a noise-reduction filter. It’s used to discern patterns out of impossible-to-read, noisy scannings of people’s heart muscles by dividing an image into cells and giving each cell a weighted search radius.

This chapter further expands on the ideas surrounding cell size in order to properly show patterns without generalizing to becoming choppy, while still not taking much storage space. 

I’m not entirely sure why the numbers for the class ranges are chosen for the natural breaks and quantile methods. It seems exponential, but also partly just random and I don’t fully understand the choices.

 

Chapter 5

 

 Chapter 5 is all about mapping areas. This can be used to determine where is the best place to place something, or to see what is possibly close enough to something to affect it. These can be in a radius around a point, in a radius surrounding a line, in a manually created bordered area (such as property line/zip code).

There are two main types of values to assign to features: Discrete and Continuous. Discrete are things that are unique and separated clearly by a point or border. Continuous are features that are not separated like this, but instead have a continuous path from one data point to another in all places. This is things like density or elevation maps. Knowing what features are all within a certain area, such as other areas or single points, creates a better understanding of the area and allows determining how the features may affect the area. 

When dealing with features that have a distance or area that are within an area, mappers can choose to only select features that are fully inside the area, partially inside, or just only consider the parts of the features inside the area. There are different applications for each, I would assume, such as streams in the area of dangerous chemical spill. It would be useful to map teh entirety of streams that fall at all within the area of the spill, because likely they would be affected downstream since the water may carry the contaminants. The overlay method would be very useful for legal things like property lines, since its not important to know the rest of the are, just where it overlaps. 

You are also able to find the features of features/areas within marked areas, and find values, frequencies, densities, averages, or summaries.

I feel as if the shaded areas outside the highlighted areas would be especially difficult to see, and I have a hard time discerning which is which colour.

I feel as though there would not be many uses for taking the average elevation of watersheds in a scenario like the one shown where they overlay a continuous elevation graph over watershed boundaries. There seems to be greatly varied elevation within the watershed boundaries, with lower land on one side and very high land on the other. I suppose that over a very large map that contains many many watersheds could be more useful as to generalize elevation. 

 

Chapter 6

 

This chapter covers how to find and analyze things within a certain distance or time of a location. Determining time or distance is considerably more complex when it’s regarding how something like a person or animal would actually get to that location. People can only drive on roads, and there aren’t always direct roads to a location. Additionally, stops and traffic lights could influence how long it takes to get to somewhere. Steep elevation or dense forest could influence how deer may travel across land, and direct paths may not be short or possible.

The straight line distance system seems like it works fine for many situations, especially ones where short time/distance is not immediately important.

The “buffer” for straight line distances can be placed around lines or shapes in addition to just points. Additionally, you can have multiple lengths of buffer lines for different classes of points/lines/shapes, and they can be combined where they overlap.

Earth’s curvature causes maps to become distorted at large scales, and so this is something that has to be taken into account when working with large maps and distances.

It’s also possible to determine the exact distance between two features (usually a feature and a source) within a selected range. With multiple sources, one can find whichever source is the closest to the point you want to determine, and then finding the distance to that and classifying it based on that one. The distance from the further ones will not affect it’s distance to one.

The algorithm used to determine distance across networks was considerably more simple than I thought it would be. 

Using cost layer, you can determine the cost to travel or expand to that location, for things like roads.

Chapter 4-

This chapter starts by explaining the difference between mapping features and feature values as densities. Mapping a feature would show the density of a business in a particular area, whereas mapping a feature value might show the density of workers at the business. It’s interesting how different these two maps look, even though the data seems fairly similar. The density maps are a little confusing right now, but I think it will make more sense when we’re creating them in the lab ourselves. The book does mention not to make dots too big when graphing density, otherwise, it is hard to pick out the patterns since they all mesh together. Also, this chapter mentions not to use too many classes when graphing density surfaces, otherwise the colors are hard to distinguish. I think it’s an interesting idea to make a map using light colors for high density because it’s usually the other way around. Although, the book mentions that the reader’s eye is drawn to the light color, and I think this is true. This chapter taught me that density maps are useful because they display patterns rather than features, which is very beneficial for real-world applications. The book mentions that crime analysts, transportation planners, and urban planners can all use density maps for their jobs. This chapter also emphasizes the idea that it’s important to decide what kind of data you have before choosing what kind of map to make and how to map it. The chapter presents many different ways to map densities, such as dots, graduated colors, or contours. There are many useful images that show common mistakes people make when mapping densities and how to fix them in order to create an effective map. 

Chapter 5-

Chapter 5 is about mapping what’s happening inside a certain area. When a map is made based on data occurring inside the area, trends can be tracked and policies or courses of action can be made based on the data. The book mentions that firefighters could use this method when there are toxic plumes so they know what areas are being affected. Also, mapping data inside an area can be done with one specific area or multiple areas. When mapping multiple areas, this would be used to compare certain trends or patterns. One thing I find interesting about all these methods is how much you can manipulate the map to display a very specific type of data in a way that is easy to understand. This chapter goes on to explain the three different ways of finding out what is inside an area: drawing areas/features, selecting certain features, or overlaying the area/features. These all have instances when they are most beneficial, so I think that you would just have to decide what kind of map you want to portray. This chapter has another chart comparing all of these methods that has pros and cons, which I think I’ll look back on later! One thing I like about this chapter, and the others before, is how it builds on material from the other chapters. It incorporates terms and ideas that were introduced earlier, like discrete or continuous features, and almost forces you to learn what they mean. I think building the information up like this is a very effective way of teaching this subject. I think maps based on what’s happening in an area have many diverse applications and it will be interesting to see how these are made in practice. 

Chapter 6-

Chapter 6 seems similar to 5, but it explains how to map what is nearby rather than inside an area. These maps are useful because you can specify a distance and analyze data within that set amount, or you can even use them to calculate travel costs and mileage. I think it’s interesting how this method can be measured using either a set distance or a set cost. If you have a budget, you can determine how far you can travel based on that budget. You can also take into account the time it takes to travel somewhere based on heavy or light traffic. Like the last chapter, this chapter explains the three different methods of mapping what’s nearby- straight-line distance, distance/cost over a network, and cost over a surface. These methods all vary in precision and uses, and it also depends on what type of data you have available to input. I think that mapping distance may seem like a fairly simple task or something that is just intuitive when looking at a map, but it’s interesting to see all the work that goes into creating maps like this. Also, the work that gets put in to make these maps means that people can look at them and read them easily. I like how each of the chapters goes into detail about what the GIS does when you’re making a map. It’s interesting to know what is happening “behind the scenes”. It’s nice how this book talks about things that you can do to make maps and show data, while also explaining the way the computer helps you out. I think it explains these concepts in a way that isn’t overwhelming and gives you just enough information to understand the process.

Chapter 4: 

The beginning of chapter four talks about map density and how map densities are specifically used for finding patterns within the mapping; it also goes into depth about deciding what to map based on the data that you have. There are two ways of mapping density which are by a defined area, and by density surface. The chapter then goes into more depth about mapping density for defined areas which requires calculating a density value for these to find areas. The equation used for this is: population density = total population /(area/2787840). Further into the density for defined areas it talks about the dot density map And continues about the individual features that map density has for those to find areas. Next to the chapter talks about creating a density surface it goes into explaining the idea behind what the GIS does with the surface. In this portion there are a lot of calculations that need to be done such as cell size. For these calculations there are three different steps that need to be calculated in order to get that information. The next part of the chapter goes into displaying a density surface which pinpoints colors used for the maps. It suggests that because of the surface layering that there should be graduated colors to show the variation in the units that you are describing. it also goes into the ideas of Contours which are connection points of equal density that show the rate of change across surfaces. Lastly this part of the chapter talks about looking at the results and how you can understand and analyze the data that is being presented.

I really thought this chapter was very thorough. I am interested to see how we apply the calculations in this class because at first glance these calculations seemed a bit difficult to understand without knowing or seeing multiple examples of how those calculations are supposed to be used. 

Chapter 5: 

Chapter five starts off with why map what’s inside, it goes to the idea of being particular about what you’re deciding to bring to the data set. It talks about crimes that you can see in a certain area as well as toxic plumes. Understanding why someone would want to have this data set for future reference. Next it goes further into defining your analysis so going more into depth about what you can see and pull out from the data set especially if you’re looking at different areas in the book there’s single areas as well as multiple areas that are being discussed. therefore depending on what area you’re looking at it can determine what patterns or information you need to pull from it. After looking at the single and multiple areas it goes into the idea about are the features inside discrete or continuous. This just goes into the further investigation of the area to see if there is a big impact or less impact to the surrounding area. Following that explanation it goes into what information you will actually need to pull out from the data set starting off with the idea about needing a list count or summary. then going into more of the Strategic analysis of do you need to see these features that are completely or partially inside the area. This goes into the idea of the borders around that area and if something’s on that borderline do you count it or do you not count it. It was really interesting to see the comparing methods on page 147. This was really helpful in kind of the breakdown of what can be pulled from these maps and how they can aid in data analysis. The rest of this chapter just goes more in-depth about what can be found inside certain areas and features based on the data set and what information can be pulled based on the information that is present.  

Chapter 6: 

Chapter six starts off with talking about why map what’s nearby. meaning why expand the area that you’re looking at but then only focus on the smaller aspect. For instance if you are looking at an analyzing a small  neighborhood but you also have the outside roadways to see the traveling range of certain areas. then the book goes into how you’re measuring these areas and what measurements you should be using. They’re also different distances or cost ranges that you might need; these are inclusive rings and distinct bands. both of these pinpoint areas that you want your perspective audience to look at to grasp the data set that you are pulling from. In this chapter there was also discussion about creating a buffer within your map to make it more clear about where the information is coming from. There was also discussion about layering of information colors and more. especially when it came to creating distance ranges in various color layers. 

It was interesting to see on page 217 how you can have a bigger map but then designate two different areas of that map to have data point sets therefore you can kind of do a comparison about seeing certain data. On page 229 it was interesting to learn about the calculating cost over a geographic surface. I didn’t really know what this was and so it is interesting to learn that this is as stated from the book “Calculating cost distance over surface lets you find out what’s nearby when traveling overland.” I thought this chapter was really informative and gave really clear information about GIS mapping and the various maps that you can create and what data you can pull from those maps.

Chapter 4

• Mapping the density of features helps you see the patterns of where certain things are concentrated
• Density shows you where the highest concentration of features is in your map. Good for looking at patterns rather than individual features.
  • This is useful for analyzing things such as census population or number of burglaries within an area.
• Can be used both for features (locations) and feature values (eg. Number of employees at a business).
  • This makes density maps more versatile and able to be used by a much wider audience for a more varied amount of analysis needs.
• You can use either dot mapping or cell layers to form a density map.
  • Density surface (cells) shows more information, but requires more effort to make.
• Density surface can be used for individual locations or linear features (roads, rivers, etc.)
• You should map by defined area if you already have the data you need summarized, or if you want to compare areas with defined borders. A density surface map is needed if you want to see the concentration of points or line features.
• There are also two different ways to display density maps; you can choose to use either gradual colors or a contoured map.
• Contour maps are good for showing the rate of change across a surface of the map, with closer lines indicating a faster rate of change.
• Gradual color maps are more cell-like with layers of color to display the data. For example, you can use a light color over a dark background to shower higher density, or vice versa. 

 

Chapter 5

• People map a specific area to monitor what’s going on inside of it, which can be used to compare what’s going on inside several different areas
  • This helps them know whether or not they might need to take action regarding the problem they are trying to monitor / analyze.
  • This can be used for policy changes, deciding specific penalties, etc.

• For your data, you need to consider how many areas you have, and what types of features are within the area.
• With GIS, you can find what’s within just one area, or several.
• Discrete features are unique, identifiable features that can be listed, counted, or summarized. They can be things like student addresses, crimes, or linear features such as rivers and pipelines.
• Continuous features are seamless geographic phenomena, such as the soil types within an area, or the number of inches of rain per year. 
• Continuous values are numeric values that vary continuously across a surface, such as temperature or elevation. 
• The GIS can help you see whether or not an individual feature is inside of an area. 
• There are three ways to find what’s inside the map
  • Drawing areas and features for a visual approach. This is done by collecting the data set containing the boundary areas, and a dataset containing the features.
  • Select the features inside of an area to get a list or summary of the features within an area.
  • The GIS combines multiple layers of maps to overlay the areas and features. This is useful for finding which features are in each of several areas or finding out how much of something is in one or more areas.

 

Chapter 6

• Mapping what is nearby allows you to see what is within a set distance or travel range of a specific feature. This helps with monitoring events within an area, or finding the features affected by a particular activity.
• Traveling range is measured using distance, time, or cost. Finding out what is within the traveling range of a feature allows you to define the area defined by a facility.
• To find what’s nearby, you can measure straight-line distance, measure distance or cost over a network, or measure cost over a surface
• Distance does not always equal nearness. You can also measure using cost, of which time, effort, and money are the most common. 
• You have the option of calculating based on the assumption that the earth is a flat surface (planar method), or you can account for the curvature of the earth (geodesic method).
  • The planar method is useful if the area of interest is relatively small, such as a city, county, or state.
  • Geodesic method is good for when your area of interest is much larger, encompassing an area such as a region, continent, or the entire earth.
• Using a straight-line distance to find what is nearby is useful for when you are trying to create a boundary or selecting features within an area. This method involves specifying the source feature, and then having the GIS find the area or surrounding features within the distance. 
• You can also use the GIS to find  which segments of the network are within the distance or cost of the source locations.
• This can also be done using the associated travel costs.
  • Use straight-line distance if you’re defining an area of influence or want a quick estimate of travel range.
  •  Use cost or distance over a network if you’re measuring travel over a fixed infrastructure to or from a source.
  •  Use cost over a surface if you’re measuring overland travel.

Ch. 4

Chapter 4 covered the concept of density. Density is an important variable because it can convey to the audience the concentration of features on a map. This is useful for analyzing patterns. Density allows us to show accurate data in proportion to other locations on the map. We can do this by plotting something by square unit of distance. 

Features can be mapped either by the value of that feature or of the feature itself. These two ways of mapping density can produce very different results. Feature values will likely deal with a lot larger numbers then only features will. 

There are two ways of mapping density: by defined area and by density surface. Mapping by defined area uses dots to represent the density of individual areas. These maps are easy to read. Mapping by density surface uses a raster layer in GIS. This creates a map with shaded regions that provide a lot of detail. Something to note with density for defined areas is that locations within the area could have different densities than the overall value. With a dot density map, each dot does not represent the exact location of a value, but rather the number of features that can be found anywhere in that polygon.  

This chapter also outlined cell size (which I think of as pixel size) and how to decide what to set your cell size at. This is actually a very important aspect to consider. Using an inappropriate cell size could present your data inaccurately. 

Contour lines were also discussed. They show the rate of change across a surface based on how close the lines are together. It is important to make sure the contour interval isn’t too big or too small. Oftentimes, contour lines are paired with shaded density to present more information on the map. 

Ch. 5

Chapter 5 opened with information about finding information on a single area and well as several areas. Discrete or continuous values can be used for this. The information that you are seeking out can help you decide what to use. Said information can be a list, count, or summary. 

Next, this chapter addressed ways of finding what’s inside of a boundary. One way is to draw the areas and features. This is just creating a map with the boundary and features on it and observing which features fall inside the boundary. The next method is selecting the features inside the area. To do this, you would specify the area and the GIS will select a subset of the features that fall within the area. The last method is to overlay the areas and features. With this, the area and feature layers are combined to create a new layer using GIS. 

The writing then went in depth about how to draw areas and features, outlining different types of features and how they can be used. This included discrete areas and continuous features. Discrete areas had multiple choice on how to display them including shading, labeling, outlining, and more. Continuous features didn’t have as much wiggle room. To use continuous features, you draw the boundary lines and then the continuous data with a dark outline to make the map easier to read. The use of shading as well as boundary lines helps to create a clear map.

Selecting features inside an area is another method of mapping. This method allows you to use GIS to see what features are included in your boundary. It flags the features on the map as well as highlighting them in your data set. 

In terms of numeric values, there are a few common summaries. These are: sum, to show total; mean, to show averages; median, to show the middle value; and standard deviation, to show extent/broadness of data.

Ch. 6

The first section of chapter 6 went over how to define your analysis of what’s nearby. Is first acknowledged that there are several ways of measuring what is considered “near.” Travel can also be measured in different ways, depending on your mode of transportation. I never thought of measuring nearness by anything other than distance, but this chapter introduced some new variables. Nearness can be measured using time, cost, effort/difficulty of transportation. It was interesting to see how the example map changed when mapping streets within three-fourths of a mile of a fire station to streets within three minutes of a fire station. It shows just how important choosing the correct feature to map is.

The next thing that was introduced was the planar and geodesic methods: methods to use that consider the curvature of the earth. The planar mapping method is used when the area of interest is small, like a city or state. The geodesic method is used when the curvature of the earth will have a larger effect, like when considering a continent. 

Distinct bands is a feature used to show the distance from one characteristic to another. It uses multiple rings of increasing size on top of each other with a common center. 

There are a few ways of finding what’s nearby. The first is straight line distance. This measures a distance in every direction from a center point (to create a circle). This is useful when creating a boundary. The next one is distance or cost over a network. This one uses distance or travel cost to create the map. It is useful when finding what is within a travel distance/cost from somewhere. The next one is cost over a surface. This method creates a layer on the map to show travel cost from each feature. It creates a shaded map.

Chapter 4

• Mapping density shows you where the highest concentration of features are
  • Useful for looking at patterns rather than locations of individual features and for mapping areas of different sizes
  • Lets you map an area using a uniformal unit to clearly see the distribution-
• Can shade defined areas based on density value or create density surface
• Can use GIS to map the density of points or lines
  • Usually these features are mapped using a density surface
• Can map the density of the features or feature values
  • Will give you very different results
• Although can map feature locations to see where they’re concentrated, creating a density map gives a measurement of density per area, 
  • Can more accurately compare areas or know whether certain areas meet your criteria
• Can map density graphically, using a dot map, or calculate the density value for each area
• A density surface is usually created in the GIS as a raster layer
• Calculating a density value for defined areas
  • Calculate density based on the areal extent of each polygon
• Some GIS software such as ArcGIS lets you calculate density on the fly
• Creating a dot density map
  • Map each area based on a total count or amount and specify how much each dot represents
• When creating dot density map, specify how many features each dot represents and how big the dots are
  • Important to be proper size in order to show patterns correctly
• Can use GIS to summary features or feature values for each polygon
• To create density surface, GIS defines a neighborhood around each cell center
• Need to set several parameters to affect how GIS calculates density surface and what the patterns look like
• GIS uses one of two methods for calculating cell values
  • Simple method counts only those features within the search radius of each cell
  • Weighted method uses mathematical function to give more importance to features closer to the center of the cell
• GIS lets you specify areal units in which you want the density values calculated

 

Chapter 5

• People map what’s inside an area to monitor what’s going on inside it or to compare several areas based on what’s inside each
  • By monitoring what’s going on in an area, people know whether to take action
• To find what’s inside can draw an area boundary on top of the features  and use an area boundary to select the features inside and list or summarize them or combine the area boundary and features to create summary data
• Need to consider how many areas you have and what type of features are inside the areas
• Can use single area or multiple areas
• Linear features and discrete areas might lie partially inside and outside an area
• Can choose to include only features that fall completely inside
  • Features that fall inside but extend beyond the boundary or include only the portion of the features that falls inside the area boundary
• Drawing areas on top of features is a quick and easy way to see what’s inside
  • However can find out what’s inside in other ways that give you additional information i.e. list of the features or summary statistics
• Sometimes making a map and looking at it is all the analysis needed
  • Using GIS to draw the area or areas on top of the features, you can see which discrete features are inside or outside an area or get a sense of the range of continuous values in the area
• GIS checks the location of each feature to see if it’s inside the area and flags the ones that are
  • The highlights selected features on the map and selects corresponding rows i the feature set’s data table
• Can use GIS to create a report on the selected features
• GIS tags each feature with a code for the area it falls within and assigns the area’s attributes to each feature
• If you have a single area, mapping individual locations is similar to mapping locations using geographic selection
  • If mapping lines or areas with a single area, can draw just the portion of each feature inside the containing area
• GIS summarizes the amount of each category or class features falling inside one or more areas
  • Can get a map, table, or chart of the results

 

Chapter 6

• Using GIS can find out what’s occurring in a set distance of a feature
  • Can also find what’s within traveling range
  • Traveling distance measured by distance, time, or cost
• To find what’s nearby, can use straight-line distance, measure distance or cost over network or measure cost over distance
  • Deciding how to measure “nearness” and what info you need to form analysis will help you decide what method to use
• What’s nearby can be based on a set distance you specify, or on travel to or from a feature
  • If travel is involved can measure nearness using distance or travel cost
• Knowing the information you need will help you choose the best method for your analysis
  • List, count, or summary?
• Three ways of finding what’s nearby
  • Simple way of finding what’s nearby is to use straight-line distance
    • However measuring distance or cost over a network, or cost over a surface, can give you a more accurate measure of what’s nearby
• Using selection to find what’s nearby is like creating a buffer
  • Specify the distance from the source and the GIS selects the surrounding features within the distance
  • GIS does not create a boundary around the source features
    • It calculates the distance and selects the the features in one step so you don’t have have to use a buffer to select the features surrounding the source
• If you’re finding individual locations near a source feature, you can have the GIS calculate the actual distance between each location and the closet source
  • Useful if need to know exactly how far each location is from the source rather than whether it’s within a given distance
• Spider diagram: GIS can draw a line between each location and is nearest source
• Creating a distance surface
  • Create a raster layer of continuous distance from the source
• Measuring distance or cost over a network
  • GIS identifies all the line in a network(i.e. streets or pipelines) within a given distance, time, or cost of a source location
    • Source locations in networks are often termed centers because they usually represent centers that people, goods, or services travel to or from
• Geometric network composed of edges/lines, junctions, and turns
• Calculating cost distance over a surface lets you find out what’s nearby when traveling overland

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.