Month: September 2025

Chapter 4-

• Right click on fields in an attribute table to edit and remove them.
• On field view of an attribute table, you can add fields. Be sure to click save!
• Joining a data table to a feature class attribute – Joins and relates -> Join -> Input join field -> Join table field -> Validate -> OK
• Exporting a feature class – Contents pane -> Right click -> Data -> Export features -> Enter relevant info -> Run tool
• Calculating sum of fields -> Fields view of attribute table -> Right click field -> Calculate field (calculating % is same except expressions)
• Creating a query – Map tab -> Selection group -> Select by attributes -> Add clauses
• Aggregating data with spatial joins – Search spatial join tool -> Fill in fields -> Run

Chapter 5-

• State plane coordinate system – livingatlas.arcgis.com
• Could not get shapefile to work. File would not be extracted and uploaded.
• Adding X,Y data -Contents pane -> right-click ie. Libraries > Display XY Data -> Output Feature Class: ie. Libraries -> X field: XCOORD -> Y field: YCOORD -> Coordinate System: Current Map -> Run
• Use the KML to Layer tool to convert a KML file to a feature class
• Not going to lie, couldn’t get half of these chapter 5 tutorials to work so there isn’t much to note

 

Chapter 6-

• Pairwise Dissolve tool – Dissolves block groups to create neighborhoods.
• Select attributes to create a study area, then remove original layer to leave only what you want to see.
• Use Select by Location to create study area block groups
• While holding shift, select different block groups. Then, use export features tool to separate them from the rest of the blocks and remove the original layer.
• Pairwise clip tool is for clipping streets
• Merging water features – Merge tool -> choose inputs/outputs -> run tool -> turn off original water layers
• use the Append tool to add features to an existing feature class, considering that both have the same attributes
• The Union tool overlays the geometry and attributes of two input polygon layers to generate a new output polygon layer aka helps determine area.

Mitchell Chapter 4 – Mapping Density – 

Density mapping highlights concentrations of features, making it useful for identifying patterns rather than exact locations. Density maps rely on areal unit to show distribution. Mapping density is especially useful when mapping areas, such as census tracts or counties, which vary greatly in size. The next step is deciding what to map, whether you need to represent features themselves, or their values, as this choice shapes the patterns revealed. Points or lines are usually mapped with a density surface, while summarized data is mapped within defined areas. there are two main approaches: mapping density by defined areas or creating a density surface. Defined areas can show density through calculated values or dot maps, where each dot represents as set amount. A density surface, on the other hand, is a raster layer where each cell holds a density value. To build one, you set parameters and units, which influence how patterns appear – call size control detail, search radius controls generalization, and calculation methods vary by approach. Finally, density surfaces can be displayed with graduated colors or contour lines. The patterns in a density surface are affected by the distribution of sample points. The more sample points, and the more dispersed they are, the more valid the patterns will be. Be aware that the values in the areas between the points are estimates. Looking at the results are very important to determine what the information is telling you.

Mitchell Chapter 5 – Finding What’s Inside –

Mitchell Chapter 6 – Finding What’s Nearby – 

Finding what’s nearby is a key GIS function used to evaluate events in an area, determine the reach of a service, or identify features affected by a condition—for example, homes impacted by flooding. Understanding what occurs within a set distance or travel range is critical for many applications. There are three main approaches to measuring what’s nearby: straight-line distance, distance or cost over a network, and cost over a surface. Straight-line distance is appropriate when there is no movement between the source and surrounding features. When movement is involved, travel can be measured across a geometric network, such as streets, or across the landscape itself. Cost surfaces add another layer of analysis by incorporating factors like time, money, or effort, rather than just physical distance. GIS calculations also consider the shape of the Earth. On a small scale, distances can be measured using the planar model, which assumes a flat Earth. For larger areas, where distortion becomes significant, the geodesic model is used to account for Earth’s curvature and provide more accurate results. When analyzing nearby features, it is important to determine whether the goal is to produce a list, a count, or a summary of attributes. Another consideration is how to structure distance or cost ranges. For example, if evaluating the accessibility of fire stations, you might want to know how many streets fall within one, two, or three miles. In such cases, GIS can create inclusive rings, where each range builds on the previous one, or distinct bands, where each ring represents a separate distance category. Ultimately, finding what’s nearby helps answer practical questions about proximity, accessibility, and impact. Whether measuring straight-line distances, network travel times, or cost surfaces, GIS provides flexible tools to analyze spatial relationships and support decision-making.

Mitchell Chapter 1 – Introducing GIS Analysis – 

What is GIS Analysis? – GIS analysis is a process for looking at geographic patterns in your data and at relationships between features. The actual methods you use can be very simple—sometimes, just by making a map you’re doing analysis—or more complex, involving models that mimic the real world by combining many data layers. The chapters in this book follow the process you go through when performing an analysis. You start your analysis by figuring out what information you need, this can usually be started with a question. Being specific with the question will make the analysis easier in the end. The type of data and features that you use help determine what method you should go with. There are often multiple different methods to getting your data, one usually being faster or more efficient than the others. Once you’ve selected your method, you then use a GIS to interpret your data. The last step is to interpret your results, they can support or deny what you previously thought as well as give a better insight to your topic of choice.

Understanding Geographic Features – The type of geographic features you’re working with affect all steps of the analysis process. Spending some time up front looking at your data—and figuring out how it can be analyzed—will make the process run smoothly. There are three main feature types: discrete, continuous phenomena, or summarized by area. For discrete locations and lines, the actual location can be pinpointed. At any given spot, the feature is either present or not. Continuous phenomena such as precipitation or temperature can be found or measured anywhere. These phenomena blanket the entire area you’re mapping—there are no gaps. You can determine a value (annual precipitation in inches or average monthly temperature in degrees) at any given location. Continuous phenomena often start out as sample points, the GIS then uses these points to assign values between the points, an example could be a weather map. Continuous data can also be data that is enclosed by boundaries, such as county or state lines. Features summarized by area are summarized data that represents the counts or density of individual features within area boundaries, an example would be the total number of households in a county.

Understanding Geographic Attributes – There are five main types of attribute values: categories, ranks, counts, amounts, and ratios. Categories are groups of similar things. They help you organize and make sense of your data. Ranks put features in order, from high to low. Ranks are used when direct measures are difficult or if the quantity represents a combination of factors. Counts and amounts show you total numbers. A count is the actual number of features on a map. Ratios show you the relationship between two quantities and are created by dividing one quantity by another for each feature.

Mitchell Chapter 2 – Mapping Where Things Are – 

Why map where things are? – By mapping things, we can now look at the picture as a whole, rater than looking at one item at a time, this helps us to pick out pattern and/or correlation between parts of the map. By looking at the locations of the features, you can begin to explore the causes for the patterns you see.

Deciding what to map – To look for geographic patterns in your data, you need to collect all data that you possibly can and then you can filter and sort and overlay exactly what layers and items or locations you want to compare on your map. you can use these “layers” to compare and see what type of event, or thing occurs in the same space or vicinity as anything thing you are looking at. The map should be appropriate to the audience, so it should be user friendly, and it should also be appropriate for the issue or topic being addressed. An audience that is unfamiliar with the area or the data being mapped will want to see information that provides reference locations, such as roads, lakes, or administrative boundaries. The way that the map is presented will also affect how much information you are able to show. Small maps such as one that will be in a journal should only show the imperative information, while larger maps are able to show more information that maybe is not quite as important.

Preparing your data – Before creating your map, make sure the features you’re mapping have geographic coordinates assigned and, optionally, have a category attribute with a value for each feature. Each feature needs a geographic location in coordinates, as well as a code to determine its type, such as whether a crime is an assault, theft or burglary.

Making your map – To create your map, you tell GIS what features you would like to display and what symbol to use for them, you can map them all as a single type or layer, or you can make sure that they all are assigned their correct code value. The GIS stores the location of each feature as a pair of geographic coordinates or as a set of coordinate pairs that define its shape (line or area). When you make a map, the GIS uses the coordinates to draw the features, using a symbol you specify. For individual locations, such as customer addresses, the GIS draws a symbol at the point defined by the coordinates for each address. For linear features, such as streets, the GIS draws lines to connect the points that define the shape of each street. For areas, such as parcels of land, the GIS draws their outlines or fills them in with a color or pattern.

Analyzing geographic patterns – If your map presents the information clearly, you may be able to see some patterns in the data. If you’re mapping a single category, you may see that features appear to be clustered, uniformly spaced, or randomly distributed. The patterns partly depend on the scale of the map. By zooming in or out, you may see patterns that were not evident before. Based on what you know about a place, or similar places, you may discover that the patterns are meaningful. This map of parcels shows the development pattern common to many towns: a central commercial strip abutted by manufacturing and multifamily housing, with single-family housing around the edges, and beyond that, agriculture. You can begin to understand how the town developed and where it might grow.

Mitchell Chapter 3 – Mapping the Most and Least – 

Why map the most and least? – By mapping the most and the least, you gain deeper insight into patterns across point, line, or area features (introduced in chapter one). The chapter emphasizes defining your map’s purpose and tailoring it to your audiences knowledge. With GIS, you can both explore data to uncover patterns and present maps that tell as story or answer questions.

What do you need to map? – The way that you display your data depands on the feature type, discrete features often use graduated symbols or shading, while summarized data is typically shown with shaded areas or charts. Sometimes you have to dive deep to discover patterns, only to dumb it back down to a generalized map or table to highlight the key trends or important factors of the topic, also to be Able to answer the big question or problem.

Understanding quantities – Quantities can be counts or amounts, ratios, or ranks. Knowing the type of quantities you’re mapping will help you decide the best way to present the data. Counts and amounts show you total numbers. A count is the actual number of features on the map. An amount is the total of a value associated with each feature. Using a count or an amount lets you see the value of each feature as well as its magnitude compared with other features. Ratios show you the relationship between two quantities, and are created by dividing one quantity by another, for each feature. Using ratios evens out differences between large and small areas, or areas with many features and those with few, so the map more accurately shows the distribution of features. Because of this, ratios are particularly useful when summarizing by area. Ranks put features in order, from high to low. They show relative values rather than measured values. Ranks are useful when direct measures are difficult or if the quantity represents a combination of factors. For example, it’s hard to quantify the scenic value of a stream. You may be able to state, however, that the section that passes through a mountain gorge has a higher scenic value than the section passing near a dairy farm.

Creating classes – Classes group features with similar values using the same symbol, and they can be created manually or through classification schemes: Natural Breaks highlights inherent groupings in uneven data; Quantile assigns an equal number of features to each class; Equal interval divides data into equal ranges, making it beginner-friendly; and standard deviation classifies values based on their distance from the mean.

Making a map – When mapping quantities, you can choose from several display methods: Graduated symbols for discrete points, lines, or areas; graduated colors for areas, summarized data, or continuous phenomena; charts to show both quantities and categories for areas or locations; contour lines to illustrate changes across continuous surfaces; and 3D perspective views to visualize continuous phenomena as surfaces.

Looking for patterns – If your map presents the information clearly, you can compare different parts of the map to see where the highest and lowest values are. Looking at the transition between where the least and most are (for example, seeing where change is rapid or gradual) can give you further insight into relationships between places. You’ll want to see whether values cluster or are evenly distributed. In this map, the Asian-American population is clustered in three areas. A store owner selling to this population would focus on these areas for an ad campaign.

Hi my name is Brendon Hess, I am a Sophomore this year and I am majoring in Biology.

I completed the week 1 quiz. After reading Schuurman Chapter 1, I realized how many applications to the real word GIS really has. Without even realizing it, I take for granted how complexly laid out our everyday lives really are. GIS has helped organize basically every part of our lives, the roads we drive to school, the sidewalks we walk, the building layouts and locations we have classes in, the most efficient ways from town to town, GIS is everywhere. One thing I found very interesting after reading this chapter was how the original GIS maps were hand drawn by cartographers! I mean can you imagine how many hours it takes to make one map? Then you need to make multiple by hand, so accurate that they can be laid on top of each other and a route for a road can be created! I found it very cool that that was someone’s job at one point and I can’t imagine the time comitment. Another thing that stuck out to me in this reading was the map on Cholera outbreaks in London in 1854. I thought this map was very interesting because of its significance in which time it was created. This map was made very early on in the storyline of GIS and it does a very good job at indicating that there could be a link between well water and catching a case of Cholera. The reading also brings up a good point that these maps can sometimes help the general public to better understand data. Sometimes its hard for people to collect what’s happening by just looking at a table, but if you have a map to go along with the table, then it may help people understand what’s going on. After reading this chapter I am looking forward to learning about all of the strange things that GIS can help us compare and predict based on overlaying data and maps.

One possible application for GIS that I am interested in is the use of GIS to track animal populations. From what I found, it sounds like it can be used in many ways such as, monitoring movement and habitat use, and human-wildlife conflict and conservation planning by integrating spacial, ecological, and social data. After learning this, I think that the conservation biology applications are something that I am very interested in. Here is a photo from the Ohio Division of Natural Resources showing the use of GIS to show where forests, wildlife, and parks are in the Delaware area.

Another possible application for this technology is the mapping and tracking of marine wildlife. Because we know very little about our oceans, I think it would be cool to know where the fish are going during the different seasons and try to link it to a why. The why, could be a completely different GIS map that we could link it to, such as water temperature.

Sources:

Esri. “Lands and Facilities – ArcGIS Experience.” ArcGIS Experience by Esri, experience.arcgis.com/experience/cd0e442b17b14e16843447a5063997cd/page/Lands-and-Facilities-Main. Accessed [10, Sept., 2025].

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.