Chapter 4:
In this chapter I learned more about Mapping Density from different aspects starting with why we map density in the first place. Mapping density helps you look at patterns rather than locations in individual features which in turn can be used when mapping areas of different sizes. When we work with areas that contain many features, it can be harder to see which areas have a higher concentration when compared to others, this is when uniform area units are needed which allows for you to clearly see distribution. There are two different ways of mapping density- By defined area, or by density surface with both being comparable. By using a dot density map, you can get a quick sense of density in a place, with the dots representing density graphically with dots being displayed based on smaller areas and drawn boundaries of larger areas. When creating a density surface, GIS calculates density for each cell in layers thus having GIS create a density surface. Calculating density values through cell sizes helps determine how coarse or fine the pattern will be. Larger cells process faster but also have a coarser surface with size equating to the length of a side. I also learned more about search radius with a larger radius meaning more generalized patterns in density surface with GIS considering more features when calculating, and a smaller radius meaning more location variation. Adding to this, if a search radius is too small, the data patterns might not show up when mapping. With units, GIS lets you specify areal units where you want density calculated, if the areal units are different from the cell units, the values in the legend will be extrapolated. Graduated colors allow for classification of values allowing for you to see the pattern. There are different ranges including- natural breaks, quantile, equal interval, and standard deviation.
chapter 5:
In this section, I learned more about why and how people map in order to find what’s inside an area by trying to monitor what’s inside it. This allows for people to compare areas based on findings while summarizing lets people compare areas to see where more or less is. By defining Analysis, you are able to use area bonding which lets you summarize and combine in order to make summary data. You need to consider how many areas you have and what information you need. With this, you can find what’s inside either a single area or several areas through your work. When wondering about discrete or continuous work, discrete is equal to unique identifiable features while continuous is used for seamless geographic phenomena. This both give you the information you need to form a summary, connected with lists, counts, or summaries. There are three different ways of finding out what’s inside- by drawing areas and features, selecting the features inside of an area, or by overlaying areas and features in order to create a new layer with the attributes that you would want to summarize. This is useful for again finding out how much of something there is, with this you will need new data containing areas of a data set with these features. GIS is useful by checking to see which area each feature is in while also assigning the areas Identification and attributes to the features that area read on the data table. When making a map, you are mapping individual locations, similar to mapping location using geographic selection.
Chapter 6:
In chapter 6, I learned more about finding what’s nearby. This helps you see within a distance or travel range of a feature while also letting you monitor events in an area or find the area that is surveyed by a community. This can be connected to features affected by a setting or activity. By mapping nearby, you are finding what’s within a set distance that identifies with the area including a tracing range being measured using distance, time, or cost- this can help define the area surveyed by a facility. When defining your analysis, you are deciding how to advertently measure “realness”. There are different subsections including straight line distance, the measure of distance or cost over a network, and the measure of cost over a surface. When defining and measuring near, you are basing it off of a set distance you specify, and the travel to or from a feature (measuring using distance or travel cost). When creating a buffer, you specify the source feature as well as the buffer distance, you can save the lines as a permanent boundary or use it temporarily when you are finding out how much or something is inside of an area. When selecting features within a distance, you use selection to find what’s nearby- like creating a buffer. GIS helps you out by selecting the surrounding features that are within the distance after you specify the distance from the source. Selecting features can be useful if you were to need a summary of features that are near a source while you don’t need to display or even create a buffer boundary. GIS can also help you with feature to feature if you are finding individual locations that are near a source feature. When calculating cost over a geographic surface, you are able to find out what’s nearby when traveling overland. GIS helps by creating a raster layer where the value of each cell is the total travel cost from the closest source cell.