Lab 1: Review of GIS I

Goals and Background:

The first lab was dedicated to a review of topics covered in GIS I. These topics include: ArcGIS, map features, layers, attribute tables, and editing symbology.

Methods:

The first goal was to become re-familiarized with ArcGIS, including ArcCatalog and ArcMap. ArcCatalog is similar to Window's File Explorer program, where you can view, preview, and edit files. The main difference is that ArcCatalog works primarily with file types used by ArcGIS such as .mxd, .gdb, and .shp. It is a powerful program as you cannot view these files in Windows Explorer. The difference is shown in Figure 1.

Figure 1. ArcCatalog on the left, and Windows Explorer on the right. The same folder is open in each program. Note how the programs view the same files differently. 

ArcMap was also part of the review. ArcMap is a program that has tools to create, manage, and edit geographic data. Data can be in the form of points, lines, or polygons. The program is shown in Figure 2 below.

Figure 2. ArcMap with a map open. There are points (donut shops), lines (streets), and polygons (land use). 

ArcMap features many tools, such as identify (a user clicks on a feature and information is displayed about the feature), and attribute tables. Attribute tables display records, which represent individual features. Attributes can be organized and queried, as well as created. Symbology is used to represent different features. In the case of the map in figure 2, symbology is used to represent the different land use types. Two maps were created using provide data, displayed in the results section below.

Results:

Map 1. Persons per square mile. 

 In Map 1 above, persons per square county is displayed. The data is normalized, meaning persons is divided by square mile giving population density. The map shows that population density is greater in the north western area of the map as there is a cluster of dark red areas. Perhaps here is where the larger cities lie.

Map 2. Median rent value. 

In the second map above, lower rent value is clustered generally in the north western portion of the map, however there are a few outliers (one notable in the north eastern portion). Higher rent values are then around those lower values, although a few are located in the middle of the lower values. This could correspond to a wealthier neighborhood, or suburbs of a city in the county. The median rent value does not directly match the pattern of persons per square mile, but someone could get a general idea of where population centers lie.

Sources:

Curtis, C., Dr. (n.d.). [Map data.]. Unpublished raw data.