Classification Exercise UCSB July 2006

Transcription

1 Classification Exercise UCSB July 2006 Purpose This exercise will examine how spatial data is catergorized and the advantages and disadvantages of different classification methods. Terms to know Population, sample Equal interval Histogram Choropleth map Quantile Discrete vs. continuous data A. Introduction Examine the following maps made from US Census Bureau American Fact Finder (a Web enabled interactive map site). Map 1: Quantile method Map 2: Equal interval method

2 Both maps show the same data (median $ income by county) for the same year (1990) and area (N.E. USA). Note that there are five categories of data for each map. These maps show a sample of the total population of data values (they do not show every person s actual income). These maps are choropleth maps, which means they show discrete spatial data and derived data (a rate, %, or central tendency). These maps use the central tendency known as the median or middle value of data for each county (it is like an average income rate for each county). Histograms or bar charts can be constructed for the data in each category. Due to the classification method the histogram will look different for each of the two maps. Estimated # of counties Cat. Cat. Cat. Cat. Cat Part B Manipulating statistical data: ArcMap. This section uses ArcMap software. Among other features it can display choropleth maps using different classification methods. Construct equal interval and quantile choropleth maps with 5 categories in ArcMap for county level data for the Southeast USA. Make both maps in the same ArcMap project by making two dataframes. 1. Open ArcMap and add the Population_Ratio dataset from: /Data/Classification/ This dataset has been prepared for you, but you must still categorize and symbolize the data. The projection of the dataframe should be GCS_North_American_1983. Right-click on the dataframe and confirm this.

3 2. Open the properties for the Population_Ratio layer and select Symbology tab from the dialog box, then Quantities and Graduated colors. 3. Next, choose the POP2000 data field and normalize it by POP90CEN. Select 5 classes. This produces a map of the population ratio between Zoom to the SE of the USA until your map looks like this figure: 5. Under classification select the equal interval classification method. Click OK. Equal Interval Method. Notice spacing of the blue classification lines. The dataset is positively skewed (bunched on the left) as is typical for many geographic datasets. This can be interpreted to mean that there are many counties with a low population growth rate, and a few with a large growth rate. 6. Make a second dataframe: Insert Data Frame. Copy the layer (right-click the layer and select Copy) from the original dataframe and paste it in the new Data Frame. Symbolize this map using the quantile data classification method.

4 7. You can construct histograms for both the equal interval and the quantile map. This allows the viewer to better visualize the data and to see the relationship of the categories to the data. 8. Make a screenshot when the data distribution is being displayed. Double click your data layer and go to Classify. Select equal interval. Press the print screen button. This saves a view of your screen to the clipboard. Open Adobe Photoshop or Microsoft Image and crop the image. 9. Do the same for the quantile map. It s possible to paste these distributions into your layout view. Using Layout view in ArcMap you can set up different Data Frames and paste in the histograms. In this example, the quantile method is shown on the left and the equal interval method on the right. Note the significantly different maps that result although the data remain the same.

5 Questions. Again try to answer as many of these questions as you can. Map analysis questions Q1. Give the min max of the data for each map. Give the min max and the range of each class for both maps (2 maps, five classes each). Range = max min. Q2. Compare and contrast the regional variation in income revealed by Map 1 and Map 2. Cite where are the highs (rich areas) and lows (poor areas), and identify any spatial patterns. 50 words min. Q3. If given Map 2, what would you conclude about the distribution of wealth in the North East United States? If given Map 1? Is either map better at showing aspects of the data and if so why? Cartography questions Q4 What is the scale of these maps as they appear here? Q5. Do these maps have good figure ground? Why/why not? Give detailed examples. Q6. Explain why in choropleth mapping we cannot show the TOTAL income per county and must use derived data, such as medians or averages. Q7. Construct histograms for both of these maps as illustrated above, with the five categories on the horizontal or x axis and the number of counties in each category on the vertical or y axis.