Chapter 1Ā
In the first chapter, it focused on what GIS is,Ā all the things it can do, and some basic GIS concepts. GIS analysis is looking for geographic patterns in data and at relationships between features. The first section describes the steps in the process of GIS analysis. It starts with framing a question to understand what type of data you need. This question will help frame the rest of the process. The next step is to understand your data, which this chapter really focuses on. The book explains that you have to know what kind of data you have in order to know what you need to create. The rest of the process is: choose a method, process the data, and look at the results. This little section made me realize the importance of understanding the basics and what you have in order to begin the process of GIS analysis. The chapter then focuses on understanding geographic features and attributes. It gives definitions of types of features, the ways they are represented, and information about map projections and coordinate systems. When it comes to map projections and coordinate systems, the book mentions that all the data layers should be in the same map projection and coordinate system to make sure results are accurate. The last section explains selecting, calculating, and summarizing when working with data tables.Ā Ā
Definitions
discrete features–Ā actual location can be pinpointed
continuous phenomena– can be found anywhere and blanket the entire area that you’re mapping
features summarized by area-Ā represents counts or density of features in an area’s boundaries.Ā
Vector Model- feature is a row in a table, feature shapes are defined by x,y locations, points/lines, areas are defined by borders and are closed polygons
Raster Model- features are represented as a matrix of cells in continuous space, each layer represents an attributeĀ
Categories- groups similar features
Ranks- put features in order, from high to low, used when direct measures are difficult or the quantity represents a combo of factors
Counts and Amounts- count= actual number of features, amount= any measurable quantity associated with a feature
Ratios- relationship between two quantities, are created by dividing one quantity by another for each feature
Chapter 2
Chapter 2 starts off with explaining that there is a lot of helpful information that we gain from mapping. We can see patterns, areas that we need to take action in, and areas that meet our criteria. In order to look for patterns in your data, you have to decide what you are going to map. You also have to take into account the audience and issue that you are addressing when making a map. This is an aspect I hadnāt thought about when using GIS and showing the data. There is a lot of information and the correct presentation is important. The next section is about preparing your data. It states the importance of assigning geographic coordinates and assigning category values. The biggest section in this chapter is about actually making the map. To map a single type, you tell GIS to draw all features using the same symbol. It explains how GIS stores each feature as a coordinate pair to define its shape. You can also map a subset of features in order to reveal any other patterns you might have been missing. You can also map by category and subsets of categories, and use different symbols for each one. It is important to not show more than 7 categories and to have large bordering ones because it will become difficult to see the pattern. If you do have more than 7 categories, grouping them together can be helpful for the patterns to stay visible. It’s important to understand what the categories represent and to group them in a specific way depending on what you are trying to show. The book then explains 3 ways to categorize data. It also states the importance of picking symbols to display categories and mapping reference features. The final section is all about analyzing the patterns. What Iāve taken away from this chapter is how important it is to make sure the pattern can be visible while making your map. There are a lot of choices to be made in order to represent the data in a way that a pattern can be seen and understood.Ā
DefinitionsĀ
Single Type Map– all features use the same symbol
Grouping Categories– grouping similar categories together to make the patternĀ easier to see
Chapter 3
Chapter 3 focuses on mapping the most and least. To do this, you map features based on a quantity associated with most and then with least. The book goes over some terms that we already learned in chapter 1 and applies them to mapping most and least. It talks about using classes to group features with similar values together. It goes over 4 common standard classification schemes to class data together which are: natural breaks, quantile, equal interval, and standard deviation. I enjoyed reading the section with how each scheme works, what they are good for, and their disadvantages. You first must choose a scheme, then decide on how many classes you will have, and then adjust to make the classes easiest to read. This chapter also includes a very large section on making the map. GIS gives you these options to show quantities: graduated symbols, graduated colors, charts, contours, and 3D perspective views. You have to consider your data and features and then pick an option accordingly. I was intrigued by the 3D perspective view and how you have to change the viewing position, pick a specific z-factor, and consider the light source. It seems a little difficult to me but I love that you can do all of that using GIS in order to show data in a better way. This chapter ends with looking for patterns in the highest and lowest values.Ā Overall I hadnāt thought about the mapping of most and least and all the relationships that the data could reveal, so I enjoyed learning all you can do with it.Ā
DefinitionsĀ
Classes- groups features with similar values togetherĀ
Natural Breaks- based on natural groupings of data values
Quantile- Each class contains an equal number of features
Equal Interval-The difference between the high and low values is the same for every class
Standard Deviation- based on how much their values vary from the mean
Graduated symbols- used to show the volumes or ranks for linear networks
Graduated colors- to map discrete areas, data summarized by area, or continuous phenomena
Charts- to map data summarized by area, or discrete locations or areas
Contour lines- to show the rate of change in values across an area for spatially continuous phenomena
3D perspective view- most often used with continuous phenomena to help people visualize the surface