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Learning objectives of Module 3
The main objectives of this module were to explore the different ways to see GIS, through the development of queries in catalog view and via specific attributes and spatial circumstances. We gained an understanding of methods to link different views between the maps and the meta data in tabular and graphical form associated with those data. This exercise explored measurements across different surface types, including slope, aspect and elevation.
Problem:
In this exercise, data existed for two watershed areas in San Diego, CA. Questions existed about how to produce awareness programs about watershed management with local school districts.
Analysis Procedure:
After opening the ArcMap document, the processing began with identifying and studying the land use types and their relative proportions within the watersheds by creating a graph from the View menu. Isolating the polygons that fell within the areas of interest allowed us to answer various questions about our study area, including how many acres of land were in the southern watershed. Census tracts were identified via a query expression within the southern watershed. Further graphing and a query conducted with a *.cal file showed population growth and growth rates within these areas.
Results:
A map was produced showing school districts that fall completely within each of the two watersheds in San Diego, CA (Figure 1). Within this exercise, in addition, population growth rates were calculated via a .cal file (data not shown).
Figure 1. Map of school districts
Application and Reflection:
Queries and measurements allow us to answer questions about the nature of the data with which we are working. In a standard data set, there are frequently several if not many different categories of information or attributes that queries help extract. Queries can help extract these attributes for assessment on an individual basis, or more complex queries can be designed to perform calculations using several attributes. For example, in the process of generating the map of Eno River State Park (see Our Mushroom Hunting for the map and the supporting data), I wanted to create a layer with contour regions at 100-foot increments (see Module 1 - Basics of Data and Information). With this information, I hope to be able to understand if there are optimal elevation bands at which mushroom varieties will be found. Designing a query to count the number of sightings of each mushroom variety within each elevation band may help elucidate this question.
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