Category: Course Student Work

Chapter 4).

Mapping density is crucial for identifying patterns relative to where features are concentrated. Concentrated areas of crime for example will need action by law enforcement. Mapping density is useful for mapping areas (census tracts or counties) of different sizes and showing patterns rather than details about individual features. In order to map density, we can either shade defined areas based on a density value or create a density surface. Generally features of GIS are mapped using a density surface. The other thing we can do is map already summarized data by defined areas like administrative boundaries. We can either map density features or feature values that we talked about last week. A feature value goes beyond just the feature location like the number of employees at each business. Density by defined summarized area does not show actual feature locations but rather represents a specific number of features. Density = # of features / area of polygon. We may need to use a conversion factor to keep units consistent. On the other hand, the GIS creates a density surface as a raster layer and can be locations or linear features like roads. Map density surface if you have individual features or sample points. Density by defined area seems simpler but density surface mapping looks better but is more complex to do. ArcGIS imposes density by defined area on the maps by shading. For a dot density map, we map each area or dot based on a total count or amount. Two different size census tracts with the same population would be the same color on a shaded map but a dot density map shows that the smaller tract has a higher density with the same number of dots in a smaller space. Dot maps are not calculated density values but the actual total numbers or values for each area. The four parameters of cell size, search radius, calculation method, and units are important considerations for calculating density values. I’m not too comfortable with calculating cell size and density converse and so I’ll definitely have to refer back to the book if we have to do this. A tip to remember is to use a value for units that reflect what features we are mapping Square meters for plants or trees and square miles for businesses. Another cool thing is that we can create a density surface using center points from data summarized by defined areas. When displaying a density surface, we employ graduated colors by creating custom class ranges or allow the GIS to do this through a standard classification scheme. Overall, the patterns of the map depend on the creation of the density surface and its parameters. 

Chapter 5).

Finding what’s inside allows us to evaluate if something occurs within an area or identify comparable information for different/multiple areas. Comparison here is important because it can be crucial in some cases to know what surrounding areas have within them or not. In order to find what’s inside we can either draw or utilize area boundaries. The number of areas and the types of features in those areas are fundamental. A grouping of zipcodes would be several areas combined. Identify each area with a name like the name of the watershed for example. We can use the GIS to get a list, count, or summary of the features within an area. We can include features that fall completely inside (for amounts), partially inside (for lists and counts), or the portion of each feature inside the area. The overlaying the areas and features approach seems good by showing what features are inside and summary details but takes longer to process. If you’re overlaying an area on data that’s summarized by area, we should make sure the summarized areas fall completely inside. This is good to do with multiple areas or single areas that need summaries of continuous data, or discrete features including only the portion inside the area. To distinguish areas when actually making the map, label them and or draw in a different shade. When selecting features inside an area and using the results it is good to know what a frequency is. A frequency is the number of features with a given value or range of values. A bar chart can be shown for numbers and a pier chart for proportions of a whole or percentages. The summary of a numeric attribute of a feature can be a sum, average, median, or standard deviation. A sidenote is that we can show what is inside the area only but it is good to show the features outside of the area as well for contextual information. I like the look of showing features inside the area with a darker color and features outside with a lighter shade of that same color. When overlaying areas with continuous categories or classes the GIS will generally select the modeling whether it be vector or raster methods based on the data we have.  Pay attention to slivers which are very small areas that are there or emerge after overlay. Remove them at first or have the GIS remove after mapping. Sometimes Raster overlay is the default or the GIS converts it to raster because it is simpler. The GIS also creates a table to analyze the results of the overlay for the raster method. Geez vector overlay seems much more difficult.  

Chapter 6).

Finding what’s nearby is super good for considering events in an area, finding the area served by something, or the features affected by something (homes impacted by flooding). What occurs within set distance or traveling ranges is critical for many uses of GIS. In order to find and evaluate what’s nearby, we can measure straight line distance, measure distance or cost over a network, or measure cost over a surface. In cases where no movement between the source and surrounding features, measure using straight-line distance. If there is movement, travel can be measured over a geometric network like a street or over land. Finding what’s nearby can also be done by measuring costs which include time, money and or effort. This relevance of the curvature of the Earth comes into play here again in that calculating distance under the conditions of a flat Earth uses the planar model while doing this under the conditions of a spherical Earth uses the geodesic model. This distortion only occurs again when the area is large but for small areas of interest it doesn’t apply and planar modeling can be done. It is important to consider whether we will need a list, count or summary, and how many distance or cost ranges are needed. If we want to know how many streets are within 1, 2, and 3 miles of a fire station, we can use inclusive rings or distinct bands. 

Chapter 4

The first section asked the question: why map density? Mapping density will show the concentration of features on a map. It is helpful when searching for a pattern rather than specific locations of features. Density maps use areal units that will clearly show the distribution.  The next section is on deciding what to map. You need to think about the features you’re mapping and the information you need from the map. If you want to map the density of points or lines you will typically use a density surface. If you have data that has already been summarized then you map it using defined areas.You also need to decide if you want to map features or the feature values because it can affect the patterns in the data. Section 3 focuses on the two ways of mapping density: based on features summarized by a defined area or by creating a density surface. When mapping by a defined area you can map density graphically, using a dot map, or by calculating a density value for each area. A density surface is created as a raster layer and each cell in the layer gets a density value. It then focuses on mapping density for defined areas. You can calculate a density value for defined areas based on the areal extent of each polygon or you can create a dot density map based on the total count or amount and then specify how much each dot represents. The last section is about creating a density surface. You will specify call size, search radius, calculation method, and units, all which affect how the GIS calculates the density. The cell size determines how coarse or fine the patterns appear and the search radius will determine how generalized the patterns will be, there are two calculation methods, and you can specify what kind of areal units you want the density to be calculated in. You can also display a density surface using either graduated colors or contours. 

Chapter 5

Chapter 5 was about finding what’s inside.  It is useful to map what’s inside an area to see what is happening there or to compare it to other insides of areas. You first need to determine if you are finding what’s inside a single area or each of many areas, if the features are continuous or discrete, what kind of information you need from the analysis, and if you need to see features that are completely or partially inside. What I have noticed is that there are always a lot of beginning steps and decisions when it comes to deciding how to map and analyze. You can find what’s inside by drawing areas and features, selecting the features inside the area, or overlaying the areas and features. By drawing areas and features you can simply look at what features are inside or outside the area. You can see which discrete and continuous features are inside the areas depending on what data you have. When you select features inside the area the GIS checks if each feature is inside the area and then flags the ones that are. Overlaying areas and features is more complex and finds which discrete features are inside certain areas and summarizes them, calculates the amount of each continuous category or class inside one or more areas, or summarizes continuous values inside one or more areas. Reading about all of these methods feels confusing and I think I would need to do it in order to understand it more. I am ready to actually use the software and see some of these processes actually happen. 

 

Chapter 6

Chapter 6 is about mapping what’s nearby. By mapping what’s nearby, you can find out how and event or activity affects an area and features inside of it. There are yet again a million different questions you need to answer in order to determine how you map and analyze your data. To identify what is nearby you can use: straight line distance(Defining an area of influence around a feature, and creating a boundary or selecting features within the distance) , distance or cost over a network(Measuring travel over a fixed infrastructure) , or cost over a surface(Measuring overland travel and calculating how much area is within the travel range). You can use straight line distance by creating a buffer to define a boundary and what is inside it, select features to find features within a given distance, calculate feature-to-feature distance to find and assign distance to locations near a source, or create a distance surface to calculate continuous distance from a source. When measuring distance or cost over a network, GIS identifies all the lines within a network and you can then find features around the area. When calculating cost over a geographic surface, GIS creates a raster layer where the value of each cell is the total travel cost from the nearest source cell. Again, I read all of this information and it feels like a lot but I am excited to see what I can do and learn from using the software next week. 

Chapter 1- 

• I logged into ArcGIS, downloaded the tutorials, and created a new project. I also learned how to save my projects.
• I learned how to add and remove basemaps, like a street basemap, for example, and I learned what layers are and how to add and remove them (located in the contents pane).
• I learned how to share and export files/maps and I familiarized myself with creating and removing pop ups, as well as zooming in and out.
• I practiced making bookmarks.
• Every vector feature class has an attribute table, and each feature (point, line, or polygon) of a feature class has a record or row of data. You right click on a feature class and select “attribute table.” In the map tab, choose “select by attribute.” On the attribute table, click “show selected records.”
• Right clicking on feature classes, attributes, etc. gives you lots of options to choose. You can sort data in different ways (like ascending and descending), deleting data, etc.. 
• Analysis tab -> tools button -> geoprocessing plane -> toolboxes -> expand analysis tools -> statistics -> summary statistics
• Symbolize features classes by right clicking on one and selecting symbology. Then choose the desired symbol. 
• You can label feature classes on a map by choosing a feature class and clicking on the labeling tab at the top of the screen. 
• In the Catalog pane, expand Maps, double-click the desired 3-D feature. Use the right and left buttons to navigate, or the scroll wheel. You can also press V and the down arrow key to tilt the map and see the 3-D view.

Chapter 2-

• In this chapter, I worked on adding and changing more symbols, like in chapter 1, specifically changing things like color, color scheme, and text size. 
• To remove duplicate labels, follow these steps: 1) Right click the layer under concern and click Labeling Properties. 2) Click Position, then Conflict Resolution. 3) Expand “Remove Duplicate Labels”, then click Remove All. This removes duplicate labels. 
• Why did we use the numbers 4901, 4902, and 4903 for creating a definition query instead of any other ascending numbers? 
• A choropleth map is a thematic map that uses varying shades or colors to represent data values across different geographic regions, making it easier to visualize and compare data distributions. 
• View tab -> convert -> to local scene -> contents pane -> drag feature class in question to above 3D layers heading -> feature layer tab -> extrusion group -> type -> base height -> extrusion group -> field -> select the relevant field.
•  Importing symbology: symbology pane -> import symbology
• Dot density map: go to symbology and set dot density as primary symbology
• Go to the feature layer tab to utilize the visibility range tool. This changes what distance you can see labels at (zoom in and labels disappear, zoom out and they reappear, and vice versa). 

Chapter 3-

• You can use guides in order to place features of a map precisely. Right click on the space you want to add a feature, and make sure that ruler and guides are selected. Then, you can click on the ruler once you close out of that screen and choose “add guide.”
• On the insert tab, you select legend to add a legend. When one legend is selected, you can choose legend items and show properties to display more information on the legend. 
• You can add text for a title and many other things under the insert tab.  
• Data tab -> visual group -> create chart. At the top of the chart properties plane, choose general, and then add a chart title and x and y axis labels. You can adjust color, size, and thickness on these charts. 
• Sharing a map online: Share tab -> share A’s -> web map -> add your name in name field -> fill in other summary info -> under share, choose with everyone -> analyze -> share.
• I logged into ArcGIS Online and found the map that I just shared under my content. On ArcGIS Online, I was able to change features and symbology. 
• The story maps on ArcGIS were pretty cool, I really liked the format of them and getting to create my own. All of the steps were pretty self explanatory and something that I could have done without the tutorial. 
• To create a dashboard on ArcGIS Online, go to the app launcher (9 dots) and select dashboards. You have to apply the settings relevant to the work that you’re doing. 
• On the dashboard toolbar (left side of screen) you can add different elements, like tables. This didn’t work well for me because after I created the tables, I couldn’t get them to show up on the map at all, but they showed up as a separate tab. As I was following along with the tutorial, I should have been able to accomplish this but it did not work. 

Chapter 4 of the ESRI book is about the usage of density maps to find patterns among features and between different locations. Density maps are good for showing things like population per capita, and what a map represents changes when density is calculated. My immediate thought/comparison was that this is how elections are manipulated. Another way density can be altered is by mapping features or values within the features, which also changes what viewers will see. Mapping with dots shows the features themselves, and patterns can be found in the clusters of dots. Then you can add layers that show feature values, which could show different relationships than just what the dots represent. Another useful way to show density is to shade defined areas like counties or cities with lighter and darker tones to show the density of a feature or population within. Using dots, though, seems to be more useful for seeing patterns at a glance and is kind of aesthetically pleasing but looks like it requires a lot more messing with to get a good result. Then, there’s more explanation of making the raster layer around the dots, and finally a bit about using contours which looked a lot like a classic topographical map to me. Also, I’m not really sure how the centroids in defined areas work, or what the use of mapping them first is? I think that might have just been an image to show how the calculation is made. The chapter’s explanation of how different shapes and ways of layering discrete features helped me understand how shaded surfaces are useful, and they seem to work best in combination with other layers.

 

Key Terms:

-Defined areas

-Contours

-Density Values

 

Chapter 5 concerns mapping features and values inside of other shapes which can be defined loosely by the map maker, by natural boundaries, or administrative/county ones. Mapping what’s inside one area shows the viewer patterns within, but mapping features within multiple defined areas allows for the areas to be compared. Now, I’m starting to understand the usefulness of vectors vs. rasters and how rasters can be used for showing continuous values, classes, and categories, the latter being a classic elevation map and all three showing natural boundaries. Then you have to decide what in the area you want to analyze but once you decide that it seems like the program kind of figures it all out. Once again it seems pretty intuitive to anyone who’s ever told a computer what to do, you just have to decide what you want it to do. You can draw or select an area, or overlay another one to choose the area you want to examine. As with other methods, the one with the least drawbacks takes more time and processing power. For overlaying, it works well and looks nice to shade the area you are looking at, like a watershed, and then parcels and features under it. It’s then up to you to decide if you want to examine only entire parcels within the area or the parts of parcels that touch it.The examples here are where I really start to see the layering that was described in the first reading. GIS can then be used to calculate values within the chosen area. The section on overlaying features gets more in depth with this, and refers back to a lot of the density based calculations in the previous chapter.

Key Terms:

-Drawing

-Overlaying

Selecting

 

Chapter 6 is about mapping distances and objects surrounding a feature. Often, this is used for things like travel time. As someone without a car I think it would be interesting to map things like easiest bus routes to and from a location. The book mentions travel distance displayed in geometric patterns in things like roads, which would suit that perfectly, and mapping roads by travel times which could be adjusted for any form of transportation. An important choice here is the choice between showing distance from a feature or mapping out travel costs, and cost would be especially useful for bus riders. Then you once again have to choose an area and whether you need a list of parcels or features, a count, or a statistical summary. The area can be a straight line (radial) distance from a feature, a network of linear features like roads, or a continuous raster. The straight line doesn’t give any information about travel times, the network distance requires roads, and the raster requires more planning and data. Also, the concept of buffers around things like roads and streams might be a good use for one of my project ideas for 110. The chapter then goes back to the concept of ranges to make the data more understandable by using cost layers.I appreciated the note that cost can be money, time, or effort. That’s ART GIS, and the idea of layers and specifically a mask layer to remove areas from the data feels very photoshop coded to me. This might be a bit of a tangent and unimportant but the maps in this chapter were cool looking,  and on that note with the program, I still appreciate that it does the hard math for you.

 

Key Terms: 

-Straight Line Distance

-Network

-List, count, or summary

Chapter 4: Mapping Density

Mapping density helps see patterns of where things are concentrated when mapping areas vary greatly in size. It allows you to measure the number of features using a uniform areal unit (hectares, sq miles). You can map density features( ie locations of businesses) or feature values (# of employees at each business).

Compare methods:

Map density by area: 

• Use if you have data already summarized by area, or lines or points you can summarize by area
• Output
  • Shaded fill map or dot density map
• Trade offs
  • Easy but won’t pinpoint exact centers of density, especially in larger areas
  • May require some attribute processing

Create density surface:

• Use if you have individual locations, sample points, or lines
• Output:
  • Shaded density surface or contour map
• Trade offs
  • Gives a more precise point of view
  • Requires more data processing

Mapping density for defined areas

This section goes through the steps to calculate density for a defined area. It gives example calculations. The GIS can calculate the density for you and shade each area it needs. Then this goes into how to create a dot density map in detail. THe GIS divides the value of the polygon by the amount represented by a dot to find out how many dots to draw in each area. Dot maps are used to get a quick sense of density in a place and represent density graphically. You can compare areas by using GIS to summarize features or feature values for each polygon. 

Creating a density surface:

Density surfaces are created in a GIS as raster layers. They are used to show where point or line features are concentrated. GIS defines a neighborhood around each cell center and then totals the # of features that fall within that neighborhood and then divides that # by the area of the neighborhood. It then creates a running average of features per area which then creates a smooth surface. Parameters such as cell size, search radius, calculation methods and units are used to specify how GIS calculates the density surface. 

Density surfaces can be displayed using graduated colors or contours and are displayed using shades of a single color. Higher values are shown using darker colors. Contour lines connect points of equal density value on the surface, and show the rate of change across the surface. The textbook then goes into detail about how to look at the results depending on how you created the density surface.  

 

Chapter 5: Finding What’s Inside

This chapter focuses on whether an activity occurs inside an area or summarizes info for each of several areas to compare them. It is important to map what’s inside so you can know where or not action is needed. To define what is inside you have to draw an area boundary on top of the features. Single areas allow you to monitor activity about one place and can include a service area around a central facility, a buffer around a feature, a natural boundary, or a manually drawn area. Multiple areas include contiguous, disjunct, or nested. Features can be discrete ( unique and identifiable) or continuous ( represent seamless geographic phenomena). These were both terms learned in chapter one. By now the chapters are starting to connect and make more sense. There is some information needed to form your analysis which can include a list, count, summary, or sum of the data. This chapter outlines three ways to find out what is inside and lists the best way to choose each method:

1. Drawing areas and features
   1. See which features are inside or outside of the area
2. Selecting the features inside the area
   1. You specify the area the the layer with the features and then GIS will select a  subset of the features inside the area
3. Overlaying the areas and features
   1. GIS combines area and features to create a new layer with attributes from both and then compares them

The chapter then outlines the best way to make the map for each of the three methods. The last part of this chapter discusses using your results to display and analyze what you have looked at using tables that list the areal extent of each category in that area of study. When using a raster, GIS takes care of the table for you but if you are using vectors, you have to summarize the category values for each area. This section discusses the methods to help do that. It then talks about looking at single vs multiple areas and single vs multiple categories. 

 

Chapter 6: Finding What’s Nearby

This chapter focused on seeing stuff within a set distance of a feature in order to monitor events or activity. It is important to map what is nearby to figure out what is happening with a certain distance that you measured. This chapter then goes into detail on defining your analysis which means figuring out what is nearby by measuring a starting line distance, measuring distance or cost over a network, or measuring a cost over a surface. Similar to chapter 5, when you identify the nearby features, you must then determine what info you need including a list, count, or summary . This chapter then highlights the three ways you can find out what is nearby and they include:

1. Straight line distance
   1. Used to define an area of influence around a feature and creating a boundary or selecting features within the distance
2. Distance or cost over a network
   1. Used for measuring travel over a fixed infrastructure
3. Cost over a surface
   1. Used for measuring overland travel and calculating how much area is within the travel range

The chapter then discusses choosing the correct method for what you are trying to achieve, how to make a map. It discusses creating a buffer using the straight line distance method where GIS will draw a line around a feature at the distance you tell it to and see what information is within it. GIS can use boundaries either manually which is more flexible, or having the GIS do it which can draw either a compact or general boundary. It talks about what a cost is (can be time, money, or other measured source) which is calculated by specifying the layer containing the source features and a second layer that has the cost value of each cell. For each method it discusses the processes of making a map and the features that are important to the process. Chapter 6 felt like it tied a lot of the concepts we learned in earlier chapters together.

Chapter 4 – Mapping Density
This chapter focuses on map density which is useful when it comes to figuring out the location or concentration of an individual feature to figure out where lost reside. This can turn data into a visualization on a map.

• Why map density?
  • It makes it easier to compare different areas due to the way it is shown on the map. They are especially useful when it comes to data of a large area.
• Deciding what to map
  • To map density an area is shaded based on density value or a density surface is created. What is being mapped out helps to decide which to use.  You can either map features which might be locations  or feature values which could be a number of features. 
• Two ways of mapping density
  • Defined area- mapped graphically using a dot map. A dot map is used to represent the density of individual locations summarized by defined areas. This also makes the map easier to read.
  • Density surface- Typically in the GIS as a raster layer. Each cell in the layer would get a density value. This provides the most information but also is a lot of work to create/ read.
• Mapping density for defined areas
  • To calculate density, you first add a new field to the feature data table. Then, you calculate the density value for each polygon by dividing the value you’re mapping by the polygon’s area. If the units for the area and density don’t match, you’ll need to include a conversion factor in your calculation. This will typically be shown as a shaded map.
  • With a dot density, you decide how many of a particular feature each dot will represent. The GIS then calculates the number of dots to draw within each area by dividing the total count in that area by the value of a single dot.
• Creating a density surface
  • GIS defines a neighborhood around each cell. The total is then divided by the area around the cell then that value is given to the cell. The smaller the cell size the smoother the surface will be. The larger the radius the more generalized the patterns will be. There are 2 calculation methods. The results depend on how the map was created.

Chapter 5 – Finding What’s Inside

This chapter focuses on spatial selection and overlay analysis. This is a fundamental task in GIS that allows you to identify parts of features that fall within a boundary.

• Why Map What’s Inside?
  • This type of analysis is used to determine which features, such as points or lines, are located within another feature. It can also be used to find which portions of a feature are contained within another. Allowing to combine data from different layers to answer a specific question.
• Defining Your Analysis
  • Before starting what is trying to be achieved needs to be determined. Are you simply trying to count the number of features inside an area or do you need to create a new layer that combines data from both the inside features and the boundary area?
• Three Ways of Finding What’s Inside
  • Drawing Areas and Features: Sometimes the simplest way to find what’s inside is to draw a new area or feature on a map and then visually see what falls in it. While not precise a great starting point.
  • Selecting Features Inside an Area: A more precise method that uses select features based on their location relative to another layer. Quick way to get a count without changing the underlying data.
  • Overlaying Areas and Features: Advanced technique that combines the geometry and attributes of two or more layers to create a new one. The new layer contains the combined information and more complex analysis. 

Chapter 6 – Finding What’s Nearby

This chapter focuses on proximity analysis, a set of tools that help you figure out the distance or travel cost from a feature.

• Why Map What’s Nearby?
  • Determining what is nearby is not always as simple as measuring a straight line. Due to proximity analysis nearby can be defined a few different ways. Helps to account for barriers like mountains or rivers where with a simple straight-line measurement would be ignored.
• Defining Your Analysis
  • What is trying to be achieved needs to be determined first whether that be the closest feature, trying to avoid something etc.The answers to these questions will determine which proximity tool is used.
• Three Ways of Finding What’s Nearby
  • Using Straight-Line Distance: Most straightforward method. Measures the shortest distance between two points. A common tool for this is creating a buffer.
  • Measuring Distance or Cost Over a Network: This method calculates travel distance or time along a network. This is more accurate for real-world scenarios where travel is limited to specific paths.
  • Calculating Cost Over a Geographic Surface: Complex method that calculates distance or cost based on a raster layer where each cell has a value representing the cost of moving across it.

Mitchell- Chapter 4

Why Mapping Density?

• Shows concentrations of features
• Good for overall patterns
• Density map uses uniform areal unit to show feature distributions

Deciding What to Map

• Map density in one of two ways:
  • Shading defined areas based on density values
  • Create a density surface
• Mapping the density of points or lines is usually done using density surface
• Can map data already summarized by defined areas (ex: census tracts, forest districts, administrative boundaries)
• Can map density of features or of feature values

Two Ways of Mapping Density

• Density map gives you density per area measurement
• By Defined Area:
  • Dot density maps show density graphically, rather than showing density value
  • To calculate density value for each area, divide total number of features by area of polygon
  • Each area then shaded based on calculated value
  • Can see areas of higher density but not centers of density
  • Could also create shaded fill map
• By Density Surface:
  • Density surface usually created in GIS as a raster layer
  • Each cell gets density value based on number of features within radius of cell
  • This provides more detailed info, but more effort
  • Point data used to create density surface may be
    • Locations of features
    • Sample points you’ve collected data for
  • Can create density surfaces for individual locations or linear features
  • Can also create contour map

Mapping Density For Defined Areas

• Dot density map or calculated density for an area
• Calculating Density Value for Defined Areas:
  • To do so, add new value for feature, then assign density value by dividing value being mapped by area of designated polygon
  • Make sure units align
  • Use range of shades of a couple hues
  • Density treated as ratio and graphed like one
  • ArcGIS lets you calculate density easily, but values are temporary and not stored in database
• Creating a Dot Density Map:
  • Map each area based on total count/amount and specify how much each dot represents
  • GIS divides value of polygon by amount represented by a dot to find how many dots to draw in an area
  • Give quick sense of density in a space
  • Dots represent totals rather than calculated density values
  • Specify dot value and size (don’t be scared to play around)
  • Display dots based on smaller areas, draw boundaries of larger areas
  • That way boundaries won’t obscure dots

Creating a Density Surface

• • Created in GIS raster layers (good for showing where point or line features are concentrated)
  • To create density surface GIS:
    • Defines a neighborhood (based on specified search radius) around each cell center
    • Totals number of features in this neighborhood
    • Divide number by area of neighborhood
  • If using data value instead of features GIS:
    • Totals that value for all features in neighborhood
    • Divides that by area of neighborhood
  • Parameters that affect how GIS calculates density
    • Cell size
      • Determines how coarse or fine patterns will appear (smaller cell size = smoother surface, but longer processing time and more storage space)
      • Larger cell = faster processing but coarser surface
      • In general, set cell size to have 10-100 cells per density unit
      • To calculate cell size
        • Convert density units to cell units
        • Divide by number of cells per density unit
        • Take square root of cell area to get length of one side
    • Search Radius
      • Larger the search radius the more generalized the patterns in the density surface will be (GIS also considers more features when calculating value of each cell)
      • Smaller radius shows more local variation (be careful not to make too small or you’ll lose broader patterns)
    • Calculation Method
      • Two Methods For Calculating Cell Values:
        • Count features in search radius of each cell
          • Result is a series of overlapping rings
        • Weighted method
          • Uses mathematical function to give more weight to values closer to center of cell
          • Weighting drops off rapidly for features outside search radius
          • Every cell in layer is counted and assigned a value
          • Smoother, more generalized surface and easy-to-interpret patterns
    • Units
      • Choose a value for units that reflects features being mapped
      • If areal units are different than cell units, legend values are extrapolated
  • If you have data summarized by defined areas create a density surface:
    • Use center points (centroids) of defined areas to create density surface based on value assigned to each area
    • Do this to highlight patterns in the map with less emphasis on individual polygons
  • Display density surface using either graduated colors or contours
    • Graduated colors
      • Classify unique density values for each cell to see patterns
      • Create custom class ranges or specify standard classification scheme and let GIS create classes for you
      • Classification schemes:
        • Natural breaks– based on groupings of data values
        • Quantile– each class same number of cells inside
        • Equal interval– difference between high and low value the same for each class

• Standard Deviation– classes defined by number of standard deviations from mean of all values in layer

• • • • GIS lets you specify number of classes to assign the density values
      • Using a few classes highlights the areas with highest density but may not show subtleties in the patterns
      • Density surfaces usually displayed using different shades of a single color
      • If using standard deviation use shades of one color for values above mean, and shades of a different color for values below the mean
      • Areas of higher value use darker colors
    • Using Contours

• Contour lines connect points of equal density value on the surface

• • • • Most GIS software makes contour lines automatically (just specify contour interval)
      • Contours are good for showing rate of change across the surface (closer contours = more rapid change)
      • Play around with interval until the lines aren’t too far apart nor too close
  • Density surface can show how values vary across a region
  • patterns in density surface are affected by distribution of sample points
  • May not actually be any features where highest density is

• Interpolation process- generalizes and smooths the data so that extremely high/low values may disappear

• • Makes patterns easier to see

Mitchell- Chapter 5

Why Map What’s Inside?

• Monitor what’s happening inside an area, or compare it to other areas
• Let’s people compare areas to see where there’s more or less of something

Defining Your Analysis

• • Consider how many areas you have, what types of features you have inside the areas
  • Single area:
    • Service area around central facility
    • Buffer that defines distance around some feature
    • Administrative or natural boundary
    • Area drawn manually
    • Result of a model
  • Multiple areas:

• Contiguous- touching or adjacent

• Disjunct- separated

• Nested– areas within each other

• Discrete features- distinct and identifiable

• Continuous features- represent seamless geographical phenomena

• • Spatially continuous categories or classes
  • Continuous values
• Do you need a list, count, or summary?
  • GIS can:
    • Find out if feature is inside an area
    • Find number of features in an area
    • Get list of features in area
    • Get summary of what’s inside an area
• Linear features and discrete areas might lie partially inside and outside an area (can choose whether or not to include these)
• If you need list/count of features include those partially in
• If need to know amount of something in area only include those inside

Three Ways of Finding What’s Inside

• Drawing Areas and Features
  • Create map showing boundary of area and the features
  • Good visual approach to finding what is in an area
  • Need dataset containing boundary area and dataset containing the features
• Selecting the features inside an area
  • Specify area and layer containing features, GIS selects subset of features in area
  • Gets list/summary of features inside single area
  • Need dataset of areas and dataset of features
• Overlaying the areas and features
  • GIS combines area and features to create new layer with attributes of both or compares two layers to calculate summary statistics
  • Good for finding features in multiple areas or how much of something is in an area
  • Need dataset of areas and dataset of features
• Overlay the areas and features if:
  • Have multiple areas and want summary of what’s inside
  • Have single area and you need a list or summary of discrete features
  • Have a single area and need summary of continuous values

Drawing Areas and Features

• Key is to create map that makes it easy to see which features are inside the area
• Individual locations/linear features can be drawn using single symbol (or symbolize by category/quantity)
• Discrete areas:
  • Shade the outer area with light color and draw boundaries of features on top (emphasizes features)
  • Fill outer area with translucent color or a pattern on top of discrete area boundaries (emphasizes outer area)
  • Draw outer area boundary with thick line and discrete area boundaries with thin line in lighter shade/different color (use if shading discrete areas by category or class range)
• Use contrasting shades/colors to distinguish areas
• If graphing continuous data
  • Draw areas symbolized by category or quantity
  • Then draw boundary of areas on top

Selecting Features Inside an Area

• • With this, specify features and the area
  • Can also find what’s inside set of areas you’re treating as one

• Geographic selection- quick way to find out which features are within a given distance of another feature

• If you have data summarized by area, can only summarize it using boundaries that fully enclose the area
• GIS can create report of selected features or create statistical summary
• Common summaries:
  • Count
    • Total number of features inside area
  • Frequency
    • Number of features with a given value inside the area displayed as a table
  • Summary of numeric attribute
    • Sum- overall total or total by category
    • Average- total of numeric attribute divided by number of features
    • Median- value in middle range of values for an attribute
    • Standard deviation- average amount values are from mean
• Draw features inside area one color, outside area different lighter color
• Draw features inside based on attribute value and draw features outside single color
• Draw all features based on attribute value, but outside ones a lighter color

Overlaying Areas and Features

• • Helps find which discrete features are inside which areas and summarize them
  • GIS tags each feature with a code for area it falls within and assigns the area’s attributes to each feature
  • Can get list of features or summary of attribute value by area
  • When line or area feature falls within two or more areas, GIS splits the feature where it crosses the boundary and builds new areas in a new dataset
  • If overlaying single area, can do same kind of analysis you would do with geographic selection
  • If overlaying several areas on set of features, can summarize features by area
  • Can also summarize by category or value
  • If overlaying area on data summarized by area, make sure summarized area falls completely inside
  • If have single area, mapping individual locations similar to geographic selection
  • If mapping line or area features can just draw portion within the area
  • Overlaying areas with continuous categories or classes
    • GIS summarizes how many of each category or class features fall inside one or more areas (can get map, table, or chart of results)
    • Vector method
      • GIS splits category or class boundaries where they cross areas and creates a new dataset with the areas that result

• Slivers- very small areas that are a result of overlaying areas on areas

• • • • Any areas with areal extent less than smallest area in either input dataset should be considered a sliver
      • Consider accuracy of your data
      • Good idea to only remove very small areas first then manually check any remaining small areas
  • Raster method
    • GIS compares each cell on area layer to the corresponding cell on layer containing the categories, counts number of cells of each category within each area, calculates areal extent, displays results in a table
• Vector method provides more precise measure of areal extent but requires more processing
• To display and analyze results you’ll need a table that lists areal extent of each category (GIS creates this with raster overlay)
• If looking at how much of each category is inside a single area, you can use table to create a bar chart showing amount of each category in an area
• For multiple areas with a single category a simple bar chart will show how the areas compare
• If multiple areas with multiple categories create a histogram showing multiple side-by-side bars (can also place pie/bar chart in each area)
• If you have a layer of continuous values, you can have GIS summarize the values and create a map or table of summary statistics
  • Can create chart from the table to compare areas based on a particular statistic

Mitchell- Chapter 6

Why Map What’s Nearby

• • Can find out what’s happening within a set distance of a feature or find out what’s in traveling range

• Traveling range– range measured using distance, time, or cost

Defining Your Analysis

• • Can measure straight-line distance, measure distance/cost over a network, or measure cost over a surface
  • Surrounding features may simply be within a source feature’s area of influence (no movement between source and surrounding features)

• Area of influence- usually measured using straight-line distance

• • May also be movement or travel between source and surrounding features
  • Can measure what’s nearby using distance or cost

• Travel costs- time, money, and effort it takes to go somewhere

• • Decide whether you are measuring along flat surface (planar method) or along curve of Earth (geodesic method)
  • Planar method is appropriate when area of interest is small, geodesic method when investigating large area
  • Output layers made using geodesic method will be displayed correctly over curved surface of the globe
  • \once you identify features near source you can get a list of the features, a count, or a summary statistic based on feature attribute
  • Summary statistic can be
    • Total amount
    • Amount by category
    • Statistical summary (average, minimum, maximum, standard deviation)

• Inclusive rings- useful for finding out how the total amount increases as the distance increases

• Distinct bands- useful if you want to compare distance to other characteristics

Three Ways of Finding What’s Nearby

• Straight-line distance
  • Specify source feature and the distance, GIS finds area or the surrounding features within the distance
  • Good for creating a boundary
  • Use if defining area of influence or want quick travel range estimate
• Distance or Cost Over a Network
  • Specify source locations and a distance or travel cost along each linear feature, GIS finds which segments of the network are within the distance or cost
  • Good for finding what’s within travel distance or cost of a location
  • Use if measuring travel over a fixed infrastructure to or from a source
• Cost Over a Surface
  • Specify the location of source features and a travel cost, GIS creates new layer showing the travel cost from each source feature
  • Good for calculating overland travel cost
  • Use if measuring overland travel

Using Straight-Line Distance

• Create buffer to define a boundary and find what’s inside
• Select features to find features within a given distance
• Calculate feature-to-feature distance to find and assign distance to locations near a source
• Create a distance surface to calculate continuous distance from a source
• Distance calculated from distance formula in math/physics
• Creating a buffer
  • Specify the source feature and buffer distance
  • With multiple features, Gis can create a buffer of equal or variable distance for each
  • Can specify several source features and GIS will create buffer around all of them at once
  • To know how many features are within several distance ranges of a source as inclusive rings you need to create multiple buffers at each interval
  • Show features like streets, administrative boundaries, water bodies, or other landmarks
  • Map should also clearly label buffer distance
  • Can select features within range of buffer, or can do multiple times for multiple distance ranges
  • To create map of features within buffer of source, put all features but make ones within buffer distance a different color
• Can go feature to feature and find each distance from the feature to the source
  • Can put this info in a data table to analyze
• You can specify maximum distance within which locations should be included
• Can use tags for each location to easily map what’s within several distances of a source
• Options for point-to-point maps
  • Surrounding locations color-coded by distance from source
  • Surrounding locations color-coded by closest source
  • Spider diagram
    • Line drawn between each location and its source
  • Source features using graduated point symbols
• Creating a Distance Surface
  • Create raster layer of continuous distance from the source
  • Creating distance ranges
    • Display each cell using graduated colors either as continuous range or grouped into classes
  • Can specify maximum distance to limit GIS when it calculates distances
  • Need to create separate input layer for each source you plan on mapping
  • If mapping discrete features, place them atop distance surface (surface displayed using graduated colors)
  • Continuous data stored as raster cannot be shown on top of distance surface
    • To show, combine reclassified distance surface with surrounding features

Measuring Distance or Cost Over a Network

• • GIS automatically identifies all lines in a network within given distance, time, or cost of source location
  • ArcGIS provides street network that is updated regularly

• Geometric layer- composed of edges, lines, junctions, and turns

• Junctions– points where edges meet

• • Street networks commonly used for finding what’s nearby
  • Travel time is one of most common costs
  • You can specify the cost for turns from one segment onto another or for stops at an intersection, can also limit which segments in a network can be travelled

• Turntable- data table that lists the junctions for which you want to specify a cost

• • Can specify direction of travel along segments
  • If more than one center, GIS assigns segments to each concurrently
  • Create a boundary in these cases
    • Want list of individual locations
    • Need count of locations in area covered by selected segments
    • Have data summarized by area
    • Need a list, count, or amount for linear features or areas
  • Sum as you go in these cases
    • Want a precise count of locations along network segments
    • Don’t need list of individual locations
  • Can manually draw boundary or have GIS make it (compact or general)

• General boundary- connects farthest reaches of selected segments

• Compact boundary- outlines the selected segments

• Can have GIS create distance rings to find what’s within several distance or cost values
• Summing as you go
  • GIS sums counts or amounts as it searches outward from center along the network
  • Can specify that GIS stops assigning streets once it reaches a maximum count or amount
• Once GIS finishes assigning segments it automatically shows the entire network and highlights selected segments
• Display center using symbol easily distinguishable from other locations
• Label centers

Calculating Cost Over a Geographic Surface

• GIS creates raster layer in which the value of each cell is the total travel cost from the nearest source cell
• Calculating cost over surface shows you rate of change
• Make sure to specify what cost is (time, money, distance, etc.)
• To create cost layer based on single factor, reclassify an existing layer based on an attribute value
• To create cost layer based on several factors, combine all the input layers
• Calculated value is assigned to entire area covered by the cell
• Larger the cell, more approximate the value for locations farther from the cell center
• Can modify cost distance by assigning maximum cost or using barriers to specify areas that are off-limits
• Output layer is a surface of increasing cost values radiating outward from source
• When mapping, show discrete features on top of cost distance surface (distance grid displayed using graduated colors)

Chapter 4:

 

This chapter is about mapping Density which reveals where certain features are concentrated. It does this by standardizing values by area to make the comparisons a lot clearer. This is especially helpful when you are working with larger data sets like censuses and crime reports. Before creating your own density map, you should make sure you know what feature you are mapping so you can reveal the proper patterns and information that you are looking for. One of the methods to track density uses defined boundaries and includes dots for tracking or has that area shaded based on the density of what you are measuring. The second method uses a continuous density surface and includes a spreading feature that shows change over time and to highlight hotspots. Area based mapping methods are pretty simple and are very useful for unit comparisons. Density surface mapping which uses more statistical information that helps to show detailed patterns. Overall, both methods to mapping and tracking the concentration of information are very helpful to highlight trends. 

 

Chapter 5:

 

This chapter is about what is inside an area which can help to reveal to see if certain features occur in said area of interest.  This use of GIS is extremely useful for monitoring different activities within a certain area and comparing areas based on what is inside. There are a few things that you need to identify before using this method, one of these things are discrete locations, roads, and areas. You also need to identify continuous features such as categories and values of this area that you are looking into.  When looking at an area and analyzing it, there’s three methods to do so. One of these methods is drawing areas and features which gives you a simple and quick overview of the boundaries. The next method is by selecting features within an area, this allows you to look at lists and counts of features within your data sets. This allows you to see the overall statistical view of your desired area. The final method involves overlaying areas and features, this combines the boundaries into new data sets and calculates summaries for that overall area. This method works with multiple areas and it’s most detailed, but it also requires the most processing out of the three methods. Overall one of the highlights of GIS is using it to see data and change over time within an area and there’s many ways to do that effectively. 

 

Chapter 6:

 

This chapter is all about using GIS to find what’s nearby when looking at a map. The purpose of doing this is so that you can monitor events to find certain areas and identify groups of specified data sets.  You can also see what’s in a certain distance of the features that you’re interested in looking at. When defining the analysis, nearness can be measured in two ways: straight line distance which is a simple area of influence or network distance which might be the amount of time it takes to get to a certain place that you are mapping. There’s two types of methods when looking at the nearness of an area: there’s planar which is when you’re looking at small areas like a city or county, and there is also geodesic which is a larger scale region or even a global analysis.  As we learned before some of the results that we can see are lists counts and summary of statistics. 

Chapter 4:  Chapter 4 talks about map density and the importance of it. Map density is useful when mapping areas on a census or in areas in which vary greatly with size. It explains that in order for you to map density you use shades and the denser a population of whatever it is that you are mapping the darker it is. This chapter explains the differences between map features and feature values explaining t hat essentially the feature is what something is and the feature value is kind of like an adjective for the feature where it is just something that further describes the feature. It explains a couple of ways in which you can map density, the two ways in doing so are mapping density by defined area and mapping density by density surface. The density by defined area is used by mapping dots on the map and is largely considered to be less informational than mapping by density surface which uses blob type images. This chapter explains that you can compare areas to find something that reaches the goal of your map. One major thing this chapter tells you how to do is create a surface layer. These surface areas show you where about the points or line features are concentrated on the map that you are creating. It explains that the GIS calculates density by taking the cell size, search radius and units into account when mapping.

Chapter 5: This chapter explains the reasons in which we map the contents of the area in which the map is surveying. This is helpful regardless of if you are mapping single areas or many different areas at the same time knowing what exactly it is that your map is showing is extremely important. When you are defining what it is that lies within the mapped territory it is important that you summarize the information that you need and/or combine your map features with the area boundary and that in itself will create a summary of your data. Your data will consist of what? That is an important question before you summarize. What features are going to be in this map, what is it that is important for the audience to know? Another question that you will have to ask yourself is, are you features that you have created due to those data points going to be discrete meaning that they are unique and can be easily identified, or continuous which is a seamless representation of that data with no specific point?  After you have asked those questions you will need a list, count, or summary to get an idea of what is inside of the area you are going to map. It explains whether or not you want to show feature of your map that are partially outside of your focused area or whether you would just map partial features like portions of rivers and other large features that could span a large area.

Chapter 6: This chapter explains that you should also map what is nearby your specified area this is because it is nice to know the travelling range to places. The traveling range to areas within your map are measured in distance, time, or cost. This is helpful for when you want to make a map that is explaining the distance from another feature the example in the book is streets within a three minute range of the local fire station. So for other maps that have that same type of purpose it is important to know how to calculate the distance of things from each other and the distance between features on your map. You can define distance or nearness based off of a feature’s travel costs. Something that it explains is that your maps come out in a way that is presented as flat. So, your information will be slightly skewed just due to the curvature of the earth’s surface. So the maps will contain something of a straight line distance which you get from specifying your distance and source feature. This chapter also explains what a buffer is and how you use buffers in order to make your distances more accurate. Basically it has the GIS draw around your distance due to the buffer which leads to more accurate distances. These buffers also show features in which are close to or at least near more than one source of information on the line of distance. Once the buffer is placed you can use the buffer to select features that fall within it.