GEOG360_EX6_W24_400_001_EDITS TO BE MADE
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Oregon State University – Geography and Geospatial Science
GEOG 360 Exercise 6: Exploring the demographics of High School Dropouts Due Dates: GEOG 360 400 students: due by Tuesday at midnight (11:59 PM) PST in Week 7.
GEGO 360 001 students: due before your lab session in Week 7. Deliverables: Upload a Word doc named as “<LastnameFirstname>_EX6” to the Canvas Assignment page for Exercise 6. 1.
In your Word document, you’ll include
Written answers to numbered deliverables presented in bold text below.
Two maps of high school dropout rates versus census data
2.
Map Exports (as PNGs) A. Poverty Map
B. Plus one of the following:
Unemployment Map
Persons without High School Diploma Map
Female-Headed Households with Children Map
Internet Access map
Renter occupied map
3.
Include a screenshot of your Model Builder workflow diagram along with your written description in your Word document to be handed in. Total points: 30
A.
OVERVIEW: In Exercise 6, we will be using demographic data from the US Census Bureau to analyze high school dropout rates and to make thematic maps of these data. We will also be creating a workflow diagram of these analysis steps using ArcGIS Pro’s Model Builder. Specific learning outcomes for this lab include: 1. Gaining experience downloading and working with census data
2. Exploring different classification methods for numerical data
3. Practicing making thematic maps
4. Starting to think about spatial analysis processes using workflow diagrams created with Model Builder
1
Remember: You should continue updating your GIS Notebook in which you document new commands and procedures that you learn throughout these tasks. Your notebook will be very helpful in recording new terminology and concepts introduced in these labs.
B.
Data Management
As you begin these exercises, review the initial steps that you have taken in previous exercises. But also note that in this exercise, we will NOT be using a geodatabase to hold the feature classes but rather will be using a regular Windows folder and working only with shapefiles. Please review the differences between a standalone shapefile and feature classes within a geodatabase (various resources are included in the Canvas Week 6 module Learning Materials page) . Then complete the following steps to prepare your workspace: 1.
You will want to have an EX6 folder created. Then on Canvas as well as in the Data folder on the R drive, you will find a zipped folder named HSDropouts_2021.zip. Download and unzip this data folder into your newly created EX6 folder. It will create a new folder called HSDropouts_2021. The HSDropouts_2021 folder contains the shapefile SchoolAttendanceZones_2021.shp as well as an Excel spreadsheet entitled ACS2021.xlsx. Be sure to unzip the zipped HSDropouts_2021 folder inside your EX6 folder before moving onto ArcGIS Pro.
2.
Then open up ArcGIS Pro, open a new project and call it EX6. Then click on the Analysis tab of the ribbon, and click the Environments button in the Geoprocessing section of the ribbon to set your Current and Scratch Workspace to your newly created HSDropouts_2021 folder. Note again that we are not working with the geodatabase in this exercise, so the workspace should be pointing to the HSDropouts_2021 folder, not a geodatabase. [Information on shapefiles and geodatabases has been included in the Canvas module for Week 6].
3.
From the Catalog Pane in ArcGIS Pro, create a folder connection to the HSDropouts_2021 folder. Answer the questions presented in these instructions and hand your work in as a Word Document. In addition, export your maps as PNGs and insert as a picture into your Word document.
For all maps produced, please include all these required map elements: ●
Title ●
North arrow ●
Scale bar ●
Legend ●
Neatline or border ●
Data source (US Census Bureau) ●
Projection and datum information (some maps, with unprojected layers may only have a GCS) ●
Author’s name (that’s you!)
●
Date (note: remember that maps need to be readable and understandable! Information such as: author’s name, date, data source, etc. should NOT be the focal point of the map, i.e. please don’t have them be huge and bold!) These map elements are generally found on professional maps. Remember to export your map to PNG format and insert as a picture in your Word document (this seems to be the easiest format for inserting maps into Word). Note: For your deliverables you will be required to make maps
based on the socioeconomic factors we will be investigating that may have some influence on high school dropout rates
. Everyone must make a map based on the provided poverty rate data
(the first set of instructions) and then choose one
of the remaining five variables to map as a finished product.
2
C.
Introduction: The Problem - Exploring high school dropouts
Dropping out of high school is a nationwide problem. Students who drop out of high school have fewer options for employment and are at greater risk for poor health and low self-esteem (Levin and Rouse 2012). High school dropouts usually end up working low-skilled and low-paying positions with fewer possibilities for career advancement. High school dropouts are also more likely to engage in criminal activities than students who graduate from high school. Much attention has been paid to dropout rates in relation to the characteristics of schools, students, and students’ families yet there have been few studies to examine dropout rates in relation to the characteristics of areas (neighborhoods) in which students live. In this lab exercise, you will explore whether certain socioeconomic characteristics of the census tract “neighborhood” appear to be associated with higher high school dropout rates. Location:
State of Oregon
Use this ArcGIS Online Story Map to begin to explore the problem of students not succeeding. This story map presents a picture of high absenteeism across the U.S. According to this Story Map project, half of the nation’s chronically absent students were concentrated in just 4 percent of the reported 16,240 school districts. These 654 school districts are found in both rural and urban areas across the country. You can use the search tool within the map to zoom in to the state of Oregon, which will be the focus of this lab, to explore the distribution of those school districts with chronic absenteeism. https://www.arcgis.com/apps/MapSeries/index.html?
appid=7f567623f36744dda5ad339aba32aca2
(note that the introductory video seems to have been dropped or the URL changed, but just continue to explore the rest of the information presented here). In addition, here are a few articles that discuss the dropout rate in Oregon and recent funding that has begun to change the situation (also note the changes during the last years of COVID): https://www.oregonlive.com/education/2019/01/oregon-generated-second-worst-
graduation-rate-in-us-in-2017.html
https://www.opb.org/news/article/oregon-high-school-graduation-rates-class-2019/
https://www.oregonlive.com/education/2021/01/oregon-graduation-rate-climbs-to-83-a-
new-high-but-schools-may-have-lowered-the-bar-for-a-diploma.html
https://www.kgw.com/article/news/education/oregon-2021-graduation-rates/283-
b537277a-0d84-45b8-b5bf-5fb77531d583
https://www.opb.org/article/2021/01/21/oregon-high-school-graduation-rates/
https://www.opb.org/article/2022/01/20/oregon-class-of-2021-graduation-rate-falls-to-806-
a-drop-from-2020/
https://oregoncapitalchronicle.com/2023/01/26/oregons-high-school-graduation-rate-up-
slightly-in-2022/#:~:text=Dropout%20rates&text=The%20dropout%20rate%20for
%202021,the%2010%2Dday%20dropout%20rule
.
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https://projects.apnews.com/features/2023/missing-students-chronic-absenteeism/in
-
dex.html
https://www.the74million.org/article/empty-desks-new-absenteeism-report-shows-dra
-
matic-surge-in-suburban-rural-latino-students-missing-class/
https://www.oregonlive.com/education/2023/08/oregons-chronic-absenteeism-rate-1-of-
nations-most-alarming.html
Oregon 2021, High School Dropout rate data: https://www.oregon.gov/ode/reports-and-data/students/pages/cohort-graduation-
rate.aspx
D.
GETTING STARTED
We will begin this exercise by retrieving the relevant census tract shapefile from the US Census Bureau’s TIGER website. This shapefile will provide you with the polygons of the census tracts of the state of Oregon. In addition, you will learn how to retrieve Oregon demographic and socioeconomic attribute data from the Census Bureau’s “Explore Census Data” website. These attribute data will provide you with data for the areas you will explore in relation to high school dropout rates.
These demographic and socioeconomic attributes are from the 2021 American Community Survey (ACS) five-year dataset. Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates. The attributes we will explore are listed below:
Percent of unemployment, population of ages 16 and older (UNEMPL)
Percent of persons without high school diploma, population of ages 25 and older (NOHSDIPL)
Percent of female-headed households with children under 18 years old, no spouse or partner present (FEMHHC)
Percent of persons whose income is below poverty level (POVERTY)
Percent of households who are renters (do not own home) (RENTERS)
Percent of households with Internet subscriptions (INTERNET)
The ACS data is based on ongoing statistical surveys carried out by the Census Bureau on a small percentage of the population. This dataset is intended to provide users with the most up-to-date data available between each decennial (10 year) census. A. Download the census tract shapefile:
Use your web browser to go to the 2021 TIGER/Line Shapefiles at: https://www.census.gov/cgi-bin/geo/shapefiles/index.php
4
After that:
Select year = 2021
Select a Layer Type = Census Tracts
Click Submit
Then on the next page
Select a State = Oregon
Click Download
5
Metadata: https://catalog.data.gov/dataset/tiger-line-shapefile-2021-state-oregon-census-
tracts
1. Click the blue “Download” button to the right of the text label that says
“Shapefile Zip File”. Make sure that you are downloading this shapefile to
your EX6 folder and unzip it. 2. The file you have downloaded is named “ tl_2021_41_tract.zip
”. This
naming scheme indicates that it is a “Tiger/Line (tl) file of census tracts for
the year 2021 for the state with an ID number of 41 (Oregon)”. 3. From your web browser, navigate to this Technical Documentation page
of the US Census Bureau for the 2021 TIGER/Line files (below), open the
Chapter 3 pdf and then within the document, scroll down to section 3.3.
Read through this section of the metadata, especially focusing on section
3.3.3.
https://www.census.gov/programs-surveys/geography/technical-documentation/
complete-technical-documentation/tiger-geo-line.2021.html
https://www2.census.gov/geo/pdfs/maps-data/data/tiger/tgrshp2021/
TGRSHP2021_TechDoc_Ch3.pdf
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Then, using Notepad on your computer (or the remote desktop), from Windows Explorer open the tl_2021_41_tract.prj
file (it’s a text file, even though it says “.prj” at the end for the file extension) and confirm that you understand this spatial referencing information. Note: if the prj file is not available to open in the notepad, right click on the file in your file folder, select open with, and choose Notepad. You have now completed the first part of this exercise: retrieving the census tracts for the state of Oregon.
4. In ArcGIS Pro, add the layer tl_2021_41_tract to your map and examine the Oregon census tracts. Remember
that you will not be able to “see” this shapefile in ArcGIS Pro until this archive is unzipped. If you unzip the archive and cannot find the Tiger shapefile in your HSDropouts folder (or a subfolder) in ArcGIS Pro using the
Content Pane, be sure to refresh your view (circle with arrow icon).
Then, open the census tract attribute table, and examine the attribute table fields which contain numeric codes for the State, County, and Census tract, as well as the area of land (ALAND) and water (AWATER) and the latitude and longitude coordinates for the center of each census tract. But notice that the attribute table does not contain any of the demographic data we discussed earlier that could be used to investigate high school dropout rates. That information is stored in separate Census Bureau tables that we will join
to our census tract polygons in order to better understand Oregon’s high school dropout rates. B. Join the census attribute data:
We’ve downloaded the polygons that define the census tracts (the spatial data) but now we want to also add the 2021 non-spatial data (attribute data) to these polygons. So we are now going to turn our attention to the ACS2021.xlsx
spreadsheet that is also in your HSDropouts folder. These American Community Survey (ACS) data are compiled from yearly estimated data published by the US Census Bureau that is based on the decennial data (in this case from 2010). We will be joining this spreadsheet of attribute data to the Census Tract (polygons) shapefile from part A.
1. If you are interested in seeing where we got these data from, check out this website: https://data.census.gov/cedsci/
. In the interest of streamlining this lab, we have provided ACS2021.xlsx, an Excel spreadsheet containing six (6) socio-economic demographics, downloaded from the website, that we identified previously as possibly impacting high school dropout rates. These variables represent the percentage of the population per census tract that meet these characteristics: a.
Percent of unemployment, population of ages 16 and older (UNEMPL)
b.
Percent of persons without high school diploma, population of ages 25 and older (NOHSDIPL)
c.
Percent of female-headed households with children under 18 years old, no spouse or partner present (FEMHHC)
d.
Percent of persons whose income is below poverty level (POVERTY)
e.
Percent of households who are renters (do not own home) (RENTERS)
f.
Percent of households with Internet subscriptions (INTERNET)
2. Then return to your EX6 project in ArcGIS Pro, and from the Catalog Pane, navigate to your HSDropouts folder (create a folder connection if you need to), then double click on ACS2021.xlsx
and drag the “
Sheet1$
” that appears under the .xlsx over to the Content Pane or right-click and choose Add to Current Map. Down at the bottom of your Content Pane you will now see Sheet1$
listed as a Standalone Table. 3. Right click on Sheet1$
and click “Open”. 7
Note: Depending on which computer you are accessing the ArcGIS Pro software from, if you get an error message when you try to access the *.xlsx file that states 'exception of
type 'ArcGIS.Desktop.Core.Geoprocessing.GPItemException' was thrown', this is an indication that you need to download and install the Microsoft Access Database Engine drive - specifically the 2016 Excel driver
in order to work with Excel within ArcGIS Pro. https://pro.arcgis.com/en/pro-app/latest/help/data/excel/work-with-excel-in-arcgis-
pro.htm
To determine if you are running 32-bit or 64-bit Windows applications, use this site: https://support.microsoft.com/en-us/windows/32-bit-and-64-bit-windows-frequently-asked-questions-c6ca9541-8dce-4d48-0415-94a3faa2e13d
Here is the Microsoft Download site for the appropriate driver: https://www.microsoft.com/en-us/download/details.aspx?id=54920
Note that you can also try using the ArcGIS Pro tool called Excel to Table to convert the *.xlsx to a table format within ArcGIS Pro - https://pro.arcgis.com/en/pro-app/latest/tool-reference/conversion/excel-to-table.htm
4. Examine the attributes in the Sheet1$
table. Then using this table
,
explore these socio-economic demographics for the state of Oregon and answer the following questions:
Note: Several attributes have <NULL> for values. These represent areas that have no data. Deliverable
1:
(0.5 pts)
Which census tract (CensusTract) has the greatest number of people (largest percent) living below the poverty line (POVERTY)? Deliverable
2:
(0.5 pts)
Which census tract has the highest percent of unemployment
for population 16 years and over? Deliverable
3:
(0.5 pts)
In which census tracts are there more than 15
% of households defined as female head of household with children under 18 years old? C.
Prepare a Census map with Attribute Tables:
1.
We now have the non-spatial U.S. Census attribute data along with the census tract polygons that we will need to begin to explore the issue of high school dropouts. But before we can create a map, we need to combine the polygons of the census tracts with their corresponding attributes in the ACS census data (
Sheet1$ from the ACS2021.xlsx
.) 2.
Note that from this point on in the lab, the steps you complete will be included in the ModelBuilder exercise later in this lab (Section F will step you through this process). The ModelBuilder diagram at the end of this document may help you organize your thoughts about the geoprocessing steps throughout much of the rest of this lab. You will be asked to describe these steps in words at the end of the exercise.
3. Open the Properties for the census tract shapefile,
tl_2021_41_tract
. Examine the Properties as well as the attribute table of this shapefile and answer the following questions:
8
Deliverable
4:
(0.5 pts)
What is the current coordinate system for this shapefile? Deliverable
5:
(1.0 pt)
(a) What are the attribute fields of this shapefile and how are they defined (i.e. what are the data types)? (b) Which of these fields are also found in Sheet1$ of ACS2021.xlsx and what are the names of those fields? 4. We will now project the shapefile, tl_2021_41_tract. Using the same approach, you’ve used in previous labs, PROJECT this shapefile into NAD 1983 (2011) Oregon Statewide Lambert (Intl Feet). Note that this is a “State System” in the categories of projections within ArcGIS Pro. Lambert is a commonly used State Plane projection used for the state of Oregon. Accept the default name for the projected output shapefile as tl_2021_41_tract_project
.
Background on the Oregon statewide Lambert Conic Conformal projection: https://www.oregon.gov/geo/pages/projections.aspx
Deliverable
6: (1.0 pt)
Take a moment to read the webpage in the link above. (a) How many projections have been used commonly at some time in the state of Oregon? (b) In one sentence
, please describe whether or not you think having multiple projections for data in a single state may be a problem, and why. 5. Locate your newly projected shapefile in the Contents pane. Remove the original tl_2021_41_tract. Also add a base map of Imagery with labels. 6. Refer back to your answer to Question 5. Also refer to this ArcGIS Pro page on Joining data so that you understand the requirements of the common key for a join to work properly. We are going to be joining the attributes of a table. https://pro.arcgis.com/en/pro-app/latest/help/data/tables/joins-and-relates.htm
7. Open the attribute tables of the
Census Tract spatial layer,
tl_2021_41_tract_project
, and of the stand-alone non-spatial Sheet1$
table. You want to confirm that these two tables have a field that is defined the same, which permits them to be joined together. Once joined, the data in the ACS2021$$
table will be visible in each row of the corresponding census tract polygon in t1_2021_41_tract_project
.
8. From the Analysis toolbox, open the Join Field tool and specify the Input table to be your census tract spatial layer and the Join Table to be your Sheet1$. The Join fields should be the field, GEOID, that you have identified as being the
same. This tool changes the input census tract spatial layer so that all the
attributes are now held in this shapefile. Open the attribute table and scroll to
the right end of the attributes to ensure that your tables have been joined
properly (you should see the new fields from your Sheet1$, such as UNEMPL,
NOHSDIPL, etc.). 9
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9. Our map layer name is getting quite long and one technique we can use is to change the name of the map layer as it appears in our contents pane. To do so, open the Layer Properties for t1_2021_41_tract_project. Click on General and then in the Name box, change the name to
“Census2021_ACS”. Click OK and then save your project.
10. Open the attribute table for Census2021_ACS and examine the values in this table. Notice that there are some census tracts that have no data <NULL> for the socioeconomic characteristics that we are interested in examining. Select all of the records that have values of <NULL>. Then, click on the gray box to the far left of the left-most column in the table along this row.
Note: values of 0 are not the same as values of <NULL>
Notice that the record is now highlighted in cyan-blue both in the attribute table and along the border for the polygon associated with this record. Zoom in to this area and examine the basemap imagery (turn off your shapefile in the table of contents). Deliverable
7:
(0.5 pt)
Why do you think these census tracts have no data (<NULL>)? 11. Make sure you have saved your HSDropouts_2021 project.
D. Create a Thematic Map of Poverty and High School Dropouts:
We now have all our relevant data in the correct GCS/PCS, and have all the census attribute data joined to the census tracts. To be consistent in terms of our georeferencing and map making, navigate to your Map > Properties and change the coordinate system to match the GCS/PCS of your data (i.e. NAD 1983 (2011) 10
Oregon Statewide Lambert (Intl Feet)). This will ensure that our maps will be properly georeferenced (remember that the Map coordinate system is set by the first layer that you initially add to your map). We can now begin to investigate our data. Before we can create a map we need to add one more layer to our map, the school attendance zones.
So in the next sections, you will add the school attendance zones, and then create a chart and map to visually explore “the association” between demographic and socioeconomic characteristics and the rate of high school dropouts. 1. Open your EX6 project if you have closed it.
For context, you can add the Oregon County boundaries to your map using ArcGIS Online. (Hint: Add via ArcGIS Online in the Add Data tool, then query for
“Oregon County” )
If you still have any records or polygons selected from Section C, clear the selection. Add the SchoolAttendanceZones_2021
to your Contents. Open the attribute
table and in the DO_Rate field, open the context menu. Click on Statistics for this field. Notice that there are extreme values of 9999 for some of the school districts. This value indicates “No Data”. We want to exclude these school districts from our analysis. To do so, we will use a Definition query for the SchoolAttendanceZones_2021 layer. A.
Open the Layer Properties window for the SchoolAttendanceZones_2021 layer. Click on Definition Query in the left hand pane. Click New Definition Query in the box that opens. Then create an SQL query that will exclude the school district polygons that have values of 9999. Click OK. Save your Project if you have not done so already. 2.
Then right-click the SchoolAttendanceZones _2021 layer and in the context menu, click Create Chart and select Bar Chart. 11
3. Under Category or Date, select School_Dis (also near bottom of list). For Aggregation, it should default to <None>. For the Variables, under Numeric field(s)
,
check off DO_Rate (near bottom of list). This field is the variable that indicates the
dropout rates of public high schools in Oregon in 2021. Click Apply. 4. If you need to, drag the chart up so it is large enough to see. Examine the results of this chart to identify those school districts that have higher dropout rates.
If you click on an individual school bar, the selected bar will be highlighted in cyan and the name of the school district and the Dropout Rate will be displayed. Investigate the chart and your map to identify the school districts with the higher dropout rates. Make sure that you clear your selection after you have explored these data. 5. Now work with the symbology palette and different classification methods to investigate the Dropout rate data
in the SchoolAttendanceZones_2021.
. Using the histogram (see below), experiment with the different classification methods to determine which one
helps you to more clearly visualize the differences in dropout rates. Here is more information on the classification methods for quantitative data: https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-
properties/data-classification-methods.htm
12
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Hint: Open the context menu for SchoolAttendanceZones_2021
and click on Symbology, choosing the Graduated Colors option under “Primary symbology”, select ‘DO_Rate’as the field. You can change the classification method and also adjust the number of Classes
. And then click on the histogram tab to determine whether the chosen method more clearly represents the data. Then choose a color ramp that seems appropriate to your data, such as darker colors for higher dropout rates. 6. Next, right-click on SchoolAttendanceZones_2021
and from the context menu, click Label. Now select Labeling Properties from the shapefile and change the field for which labels will be drawn to ‘DO_Rate (clear the Expression box first, then double-click the ‘DO_Rate’ field name, and then click Apply). Deliverable
8:
(1.5 pts)
Using your chart and map, (a) Which high school in Oregon
had the highest dropout rate in 2021? (b)
In which part of the state is this high school
located? Create a Map of Poverty rates (7 pts)
The next step in our analysis is to create a map that examines a socioeconomic characteristic and the high school dropout rates together
. We will examine Poverty
rates first.
6. Right-click the Census2021_ACS layer and click Symbology.
7. In the Symbology
pane, switch from Single Symbol to Graduated Colors
. 8. Under Field
, select the
POVERTY field
. Note that the Classification
method defaults to Natural Breaks (Jenks) with 5 classes. Under Method, choose another method of classification such as Standard Deviation to view the difference that the classification method makes in the presentation of the data. Then click on the histogram tab to determine whether the chosen method more clearly represents the data. You will want to explore different classification methods to determine which one most appropriately represents the distribution of the data. You can change the classification method and adjust the number of Classes.
Review the standard classification methods that are available through these ArcGIS help documents: https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/graduated-
symbols.htm
http://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/graduated-
colors.htm
9. You can choose the color ramp that you think is appropriate for your map once you have selected a classification method. Deliverable
9:
(0.5 pts)
Which classification method did you choose and why did you choose this method? 13
10. Recall that there were a number of census tracts that had No Data (recorded as <NULL>) in your attribute tables. We don’t want to map these census tracts along with our other data. To exclude these areas, we can specifically select those tracts that have No Data (in this case values of <NULL> or 999) and indicate in the Classes tab (within the Symbology dialogue) that they should be excluded. Within Symbology, click on Advanced symbol options (upper left corner of Symbology window, icon that looks like a paintbrush behind a speech callout box from a cartoon), and expand Data Exclusion. Click New Expression. Create a statement that excludes those records that have a value of <NULL> for the POVERTY
field.
Note: Rather than excluding these polygons, those polygons that have NULL values can be mapped as “No Data” and labeled as such in the symbology.
11. In composing your map, you will first want to change the symbology of the Dropout Rates in SchoolAttendanceZones_2021 to proportional symbols so that both the SchoolAttendanceZones_2021
and Census2021_ACS are clearly visible on your map. Check out the proportional symbol document below:
https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/proportional-
symbology.htm
12. From the context menu for the SchoolAttendanceZone_2021 layer
,
open the symbology tab
. Under primary symbology, scroll down and select proportional symbol. For field select, DORate and leave Normalization set to none. Finally, adjust your minimum and maximum size values so that the symbols on your map are not too big or small. You may need to set your Maximum size to None so that your symbols don’t overwhelm your map and so that your legend draws correctly. After adjusting the symbology, you should be able to see both layers (
SchoolAttendanceZone_2021 and Census2021_ACS)
in your map viewer. Turn off the basemap so that you can see your new symbols more clearly. If you like, you can experiment with the various symbology options to display the data to identify a different method that you may find more appealing or clear in the representation of the drop out rates. 13. Using your knowledge from previous labs, insert a new layout and compose an aesthetically - pleasing map with all necessary map elements (see the list of required map elements on page 1). Think about the placement of the map elements as well as the classification of the variables and the color ramps used. If you
would like to create a map of a smaller geographic area, zoom into a specific area to focus on the Dropout rate and Poverty status. In this case, make sure that you create an inset map (extent indicator) so that your viewer has a reference to the location. Refer back to the discussion of the five (5) primary design principles in cartography https://www.esri.com/news/arcuser/0112/files/design-principles.pdf
https://support.esri.com/en/technical-article/000016555
14
https://pro.arcgis.com/en/pro-app/latest/help/layouts/extent-indicators.htm
Review map layouts at the link below:
http://pro.arcgis.com/en/pro-app/latest/help/layouts/layouts-in-arcgis-pro.htm
14. When you are happy with the composition of your map, export it as a PNG and insert it as a picture in your Word document. Then answer the following questions. Deliverable
10
: (0.5 pts)
Which regions of Oregon have relatively higher rates of poverty? Deliverable
11: (1.0 pts)
Are there regions with poverty rates that coincide approximately with areas with high dropout rates? E. Create a thematic map of one of the other demographic or socio-economic variables, aside from POVERTY, in relation to Drop out rates. (7 pts)
1. Now we want to examine some of the other demographic and socio-economic variables that may help to explain high school dropout rates. Insert a new layout to compose another map. Remember to change the name of each new layout as you create a new map and to save your project. This will help you track your progress in case you encounter bugs or need to backtrack. 2. To create another map showing a different socioeconomic characteristic, right-click Census2021_ACS in the Table of Contents
and click Properties
. Click Symbology
.
3. Repeating the process you used to map POVERTY
, choose ONE of the variables listed below for your next map. Take a quick look at each variable to decide which of these you think may be more highly associated with high school dropout rates. You will also want to explore which classification method you will use to
map each variable. Remember to change the classification method and then look at the histogram to determine whether the chosen method clearly represents the data. As a reminder, this is a brief background for each of the variables you may try mapping:
▪
Percent of unemployment, population of ages 16 and older (UNEMPL)
▪
Percent of persons without high school diploma, population of ages 25 and older (NOHSDIPL)
▪
Percent of female-headed households with children under 18 years old, no spouse or partner present (FEMHHC)
▪
Percent of persons whose income is below poverty level (POVERTY)
▪
Percent of households who are renters (do not own home) (RENTERS)
▪
Percent of households with Internet subscriptions (INTERNET)
4. Depending on the field you choose, you may need to change the number of decimal places to 3, if necessary. See this discussion: https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/format-
numbers-in-legend-labels.htm
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5. Again in your layout, compare one of these socioeconomic characteristics to the high school dropout rates. 6. Repeat the relevant steps to compose your second map. Make sure to add all essential map elements and, again, save this layout with a new name to preserve your maps. Then export this map as PNG and insert it as a picture in your Word Document. You will have composed two (2) maps for presentation. (7 pts each)
7. Regardless of which other socioeconomic characteristic you chose to compose the second map layout with, please symbolize each of the remaining four (4) variables in your map and take a quick look at noticeable trends in these data prior
to answering the questions below.
Deliverable
12: (3 pts)
(a) Do any of the selected socioeconomic characteristics seem to be visually associated with higher rates of high school dropouts? (b) Which socioeconomic factor seems to be the largest indicator? (c) Are there other variables that you think should be explored to address this problem? F
. ModelBuilder Workflow Diagram: 1.
Read through pages linked below on the Geoprocessing History that is created each time you run a tool in ArcGIS Pro. The second web page describes a visual programming language called ModelBuilder which allows you to create sequential workflows of the geoprocessing of spatial data. https://pro.arcgis.com/en/pro-app/latest/help/analysis/geoprocessing/basics/
geoprocessing-history.htm
https://pro.arcgis.com/en/pro-app/latest/help/analysis/geoprocessing/modelbuilder/what-
is-modelbuilder-.htm
Now let’s practice building a model of our own by replicating what you have just done in this exercise.
And then describe the geoprocessing history in a written description. ▪
First from the Analysis tab, in the Geoprocessing group, click on the History icon to open your
Geoprocessing History pane. The History pane will appear in the right hand side of your map view (I have just
moved this over to the left to include it in this screenshot). ▪
Then in the Analysis tab, under the Geoprocessing group, click on the
ModelBuilder icon to open a new blank model in the map pane. ▪
Now, starting from the Geoprocessing history from Section C of this lab (pg
7), drag and drop each geoprocessing history entry into the blank ModelBuilder window. You will
want to make sure you connect the tools (input – tool – output) in the proper order following
the sequence that you carried out for the exercise itself. ▪
Here is an example of a similar workflow diagram (model), starting from Section C
“Prepare a Census map With Attribute Tables” where the ACS2021
$$ (Sheet1$) table is joined to
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the Census data shapefile. Note that your workflow diagram should include only those
tools that you used in your geoprocessing (i.e. it will not look the same as this model). Deliverable 13: Now describe in your own words, in written form, what your workflow
diagram depicts in terms of the geoprocessing steps that you carried out in this
exercise.
Hint: Create your written description in the form of “Input dataset – Tool used
– Output dataset, the Output dataset is then the Input dataset to….” When you have completed your Model, go to
the ModelBuilder contextual tab, then
Model Group, click the Export dropdown and click on "Export to Graphic". Save your
model diagram as an *.SVG file and include it, along with your written description, in
your Word document to be handed in (5 pts for the description and diagram combined).
Note: Your model diagram does not have to be perfect. We just want you to try and figure out how it works and to gain understanding of what you might use it for.
▪
Make sure you save your Project! Deliverables: Upload a Word doc named as “<LastnameFirstname>_EX6” to the Canvas Assignment page for Exercise 6. 4.
In your Word document, you’ll include
Written answers to numbered deliverables presented in bold text below.
Two maps of high school dropout rates versus census data
5.
Map Exports (as PNGs) A. Poverty Map
B. Plus one of the following:
Unemployment Map
Persons without High School Diploma Map
Poverty Map
Renters’ Map
Female-Headed Households with Children Map
Household with Internet Subscription Map
6.
Include a screenshot of your Model Builder workflow diagram along with your written description in your Word document to be handed in. 17