Chapter 1:
Throughout this first chapter, we get an introduction to the world of GIS through various definitions and skill sets that we will apply when using the arcGIS database later in the course.
GIS is defined as a process of looking at geographic patterns in data as well as the relationship between features. GIS analysis in turn helps you see patterns and relationships in geographic data with results that give you insight into a place, helps focus actions, or helps you choose the best option. We also learn that spatial data is more abundant than ever and even has new sources such as Lidar and drones which were brought upon by Gis being shared more openly leading to advances in Gis software. Through GIS, you are able to employ spatial analysis and address pressing issues throughout the world. You can figure out why things are the way they are through accurate and up-to-date information (GIS allows you to create new information). The information that you find and create then helps you gain a more distinct understanding of a place, make the best choices, or be able to prepare for future events and conditions. In order to do GIS analysis effectively, you need to know how to structure your analysis and you have to be able to understand tools to use for specific tasks. You need to understand how to frame the question, understand your data, choose a method, and process the data. To aid in this there are different types of features including discrete features, continuous phenomena, interpolation, features summarized by data, representing geographic features with sub sections for vectors and rosters. When doing map projections and coordinate systems, all data layers should be in the same projection and coordinate system. This ensures accurate results when combining the layers in order to see relationships. We need to consider geographical attributes such as categories, ranks, counts, amounts, and ratios. Adding to this, when you work with data tables, you need to understand selecting, calculating, and summarizing.
chapter 2:
In the second chapter we learn more about how to look for locations and features and how that helps you begin explaining the cause for the patterns that you found and observed. When deciding what to map, you interpret your information based on the features you need to display and the understanding that you need to display them based on the information you need and how the map is used. You can use GIS to map the location of information like a street sign, address, or latitude/longitude values- these are read by GIS and then appropriately assigned category values. GIS is able to store the location of each feature of geographic coordinates as a set of coordinate pairs that are able to define it’s shape. You can map all features in a data layer ar a subset based on a category value. This is more commonly done for individual locations, sharing a subset of continuous data leaves the feature without a context. Through mapping by category, you can provide an understanding of how a place functions. Connecting with this, you can not display more than seven categories because anything over seven will be confusing and hard to understand when people are interpreting your maps/graphs. If you do use more than seven categories, you can make the graph easier to understand and differentiate by using symbols to display categories. ArcGIS has basemaps that you can use for mapping reference pictures in your own work. When analyzing geographic patterns, you may be able to see patterns in data. In Single categories, features may seem clustered, uniform, or randomly distributed. When mapping the most and least, you map features based on a quantity that is associated with each- this adds an additional level of information.
Chapter 3:
Chapter three is almost a reiteration of information from the past chapters, explaining how to do data processes that we will be doing once we personally begin mapping on GIS. We again learn about mapping most to least and the idea that you need to map features based on a quantity that is associated with each number or group. You can map quantities associated with discrete features, continuous phenomena, or data summarized by area. We also learn again why we need to map and how mapping features and patterns with similar values helps you see where the most and least (as referred to earlier), are. Discrete features can be seen as individual locations, linear features, or areas. With locations and linear features, they are usually represented with graduated symbols with areas shaded to represent quantities. When referring to continuous phenomena, it can be seen as defined areas or a surface of continuous values. These area as portrayed using graduated colors, contours, or even a 3D perspective view. When you are summarizing data by area, it is usually displayed by shaded area based on its value. You can als ouse charts and shows the amount of each category that is in each area. You are able to summarize individual locations, linear features, or areas. While remembering the purpose of your map and what you are intending to show, you need to decide how to present the information that is being displayed on your map. When you map the most and least, you assign symbols to features that are based on a character or attribute containing a quantity. These quantities can be counts, amounts, ratios, or ranks. After deciding the quantities you want, you then need to decide how to represent them on the map.