Week 2 (Will Sturgill)

Chapter 1:

• I have been a geography student here at OWU for over 6 semesters now. I have taken roughly 10 courses that all involved GIS in some way and I have to be honest it is refreshing to go back to the basics of what really makes up GIS and GIS data. I thought that this chapter did a great job of explaining what makes up GIS and why it is important to understand the geographic features and types of features. “Geographic features are discrete, continuous phenomena, summarized by area.” (Mitchell, 2020). This quote puts into perspective the three different types of geographic features used in GIS. Discrete features like locations and lines can actually be pinpointed on a map. Continuous phenomena such as temperature can typically be found or measured anywhere. Summarized by area means that the summarized data represents the density or counts of individual features within the area’s boundaries. All three are essential in explaining the first chapter and what it means to begin to analyze GIS data. 
• The two ways geographic features can be represented in GIS are raster and vector. These are technically two different types of models within a GIS system. With the vector model each feature is a row in a table and this means that it is typically defined by x,y locations in space. This also includes the use of polygons that define an area based on the x,y location. They can also be defined by boundaries which can be legally defined or naturally occurring. 
• With the raster model features are represented as a matrix of cells in continuous space. Each layer represents one attribute and analysis occurs by combining the layers to create new layers with new cell values. This distinction between raster and vector models is important to note because analysis occurs differently with the two different models. 
• Cell size in a raster model affects the results of the analysis
• Accurate results start with using the same map projection and coordinate system. Map projections translate locations on the globe to the flat surface of your map. 
• A coordinate system specifies the units used to locate features in two-dimensional space and the origin point of those units. This is an important note because it shows what is happening behind the scenes when a certain coordinate system is used for the map and why there may be more than just one coordinate system
• Geographic features have one or more attributes that identify what the feature is or describe it. These attributes are represented as values and are extremely important when creating a map. 
• The different attribute values are categories, ranks, counts, amounts, and ratios. The main difference between some of these attribute values is if they are continuous values or if they are NOT continuous values.
• Tables that contain the attribute values are important to work with in GIS and the different ways to work with them are selecting, calculating, and summarizing.

Chapter 2:

• Mapping has become increasingly important and the best example of this provided by the chapter is that you can map where things are to show you where you need to take action. Police can do this by mapping where the most burglaries might take place in a city and wherever this area may be is where they can take action next.
• This type of mapping analysis includes looking for patterns that occur and where these patterns might be.
• Symbols are used to map features in a layer of a map to show these patterns.
• Multiple features can be mapped at once using GIS to see if these features/attributes are occurring in the same place. An example of this is if police map two features, which are theft and assault, at once and see the connection of these two features occurring in the same place and determine that there is a pattern that shows and this pattern is that theft and assault are occuring in the same place/area.
• The GIS map should be appropriate for the targeted audience and should properly address the issue at hand that the map is highlighting. 
• GIS maps should also include areas of reference for an audience that may not be familiar with the area being presented.
• Preparing your data for a GIS map includes creating a category attribute with a value for each feature and to also have geographic coordinates assigned.
• When mapping each feature mapped must have a code that identifies its type of feature. Many maps will display categories based on hierarchical features and there may be some features that are listed as sub-categories based on the hierarchy used.
• Mapping a subset feature in a data layer is helpful to determine patterns that are not easily seen when mapping all of the features.(this is commonly done for certain individual locations)
• Mapping features by category can help with understanding how a certain place functions.
• GIS helps with the above comment by storing a category value for each feature in the layer’s data table. 
• The way you group categories can change the way readers perceive the information, for example creating a map with more than seven categories makes it difficult for the reader to see the patterns associated with the map. 
• There are different methods of grouping categories that can alter the features that are being represented on the map.
• Patterns on the map will become recognizable when mapping categories, whether it be a single category or multiple categories. 

Chapter 3:

• Mapping the most and least in an area is important to see relationships between places, and to also see if a feature may meet a criteria or if action needs to be taken. 
• To map the most and least you need to map features based on quantity associated with each.
• Discrete features can be mapped using graduated symbols that are often shaded to show quantity. This is an important distinction between normally mapping discrete features and mapping them for quantity.
• Continuous phenomena can be mapped for quantity by displaying graduated colors
• Data summarized by area is usually displayed by shading each area based on its value or using charts to show the amount of each category in each area. 
• It is also important to note again that people can recognize up to 7 colors on a map but after that it becomes difficult and distorted for people to analyze the data
• An amount is different than a count because it is the total of a value associated with each feature, versus the count of the actual number of features on the map
• Ratios show you the relationship between two quantities and are created by dividing one quantity by another for each feature. Common ratios include averages, proportions, and densities
• Ranks put features in order from high to low and they show relative values rather than measured values. When direct measures are difficult this is when ranks come in to play.
• Once the quantities are determined the next important step is to determine how to represent the data and this is commonly done by grouping the values into classes.
• Classes group features with similar values by assigning them the same symbol.
• Standard classification schemes can be used to look for patterns in the data.
• There are various forms of classification schemes and each can be used for certain types of data and features that are represented in the map.
• Outliers are extremely low and high values that can obscure the data represented and the class ranges as well. This means that outliers should be looked at closely because they could show errors in the database or even anomalies with the data.
• This chapter mentions that the features and data values your are mapping must be consider when deciding what map type to use.

Chapter 4:

• Chapter 4 deals with mapping the density of features and the purpose of this is to see possible patterns and where things may be concentrated.
• Density maps are more useful for detecting patterns than for looking at the location of individual features.
• There is a slight difference in mapping features and feature values. This difference is due to feature values being located in features themselves.
• However you can also map individual locations. This is done by using a defined area and using a dot map to represent these locations. This is one way that density can be mapped
• Another way that density can be mapped is mapping density by surface. A density surface is created in the GIS as a raster layer. Each cell in the layer gets a density value based on the number of features within a radius of the cell. This is a more precise way than mapping density via defined area
• You can also map density for  a defined area by calculating a density value for each area and then shade each area based on this value
• With GIS and mapping density, the size of the cell used (specifically for calculating density values) will determine whether the map has a smooth or rougher type of surface. This is the difference between using small cells compared to bigger cells.
• Displaying density surfaces requires using graduated colors or contours. The reason for this is that each cell has a unique value and therefore requires classification which as stated before in previous chapters can be displayed graduated colors and contours.
• Contours can be useful because they connect points of equal density value on the surface. As shown in previous chapters as well as chapter 4, contour lines are typically created automatically by ArcGIS.
• The notes for this chapter above really show how detailed mapping density can be. I had never thought about the true detail and what all goes into mapping density so this chapter was a good insight to the detail of mapping density. 

• Some extra notes: I did think that the reading was a bit lengthy for this week, however I found it to be extremely informative and helpful. I think it should be noted that the maps shown with each chapter were also really helpful in providing examples.