Code
knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//table table_1.PNG") 
Westside San Antonio & Eastside Austin, TX: A Growing Megalopolis in Central Texas and its Implications On Those Historically Marginalized Populations within the two Urban Cores of Bexar & Travis County observing Demographic & SES Trends
Introduction
Over the decade of 2010 through 2020 there has been alot of growth in both San Antonio and Austin, Texas. With this growth a concern may rise of what may happen to the most vulnerable populations that live in those urban cores of those two cities. We start by focusing on the Westside of San Antonio being an area that has experienced systemic multi-generational poverty (Miller, 2021). We then observe Austin, Texas and Travis county as a whole which is also known for its extremely ridged redlining historically (Koch & Fowler, 1928; Goudeau, 2018).
Central Texas & The I-35 Corridor - A Future Megalopolis
The reason for looking at Bexar County and Travis County is because they are on the polar sides of a region in Central Texas that is possibly undergoing a spatial transformation turning into a “Megalopolis”. “Megalopolis” as coined by Gottmann is used to explain urban clustering when it occurred in the Northeast region of the US with the cities of Boston, New York, Philadelphia, Baltimore, and Washington (Gottdiener, et. al., 2019).
These “Megalopolis’s” have been slowing formulating throughout the decades with the Northeastern region of the US experiencing this first due to its history and initial migration patterns found in the US that included higher proportions of European migrants and others from the Eastern Hemisphere. In Texas this Megalopolis is forming in the Central region of the state along the I-35 corridor concerning these two observed metroplex’s as mentioned. Because of this as most Megalopolis’s are, the region will become a hub for the main factors of the state’s economy as well as the states experiences with migration.
Although other major Texas cities are also present such as Dallas and Houston; the Central Texas area has seen a large increase of population throughout the decade. It is important to understand the overall growth and changing demographics of the Austin and San Antonio area because these two urban centers are the main drivers of this urban sprawl that is occuring in Central Texas along the I-35 corridor. As the two cities continue to grow they will eventually collide with each other which then will have many possible political implications of being able to say where the greater San Antonio are ends and the greater Austin area begins. These same political drivers may also be existent for those living on the outer counties of Travis and Bexar. Being that to whos economy will the majority of those population be participating in? Austin or San Antonio? And again to further emphasize, what does this urban growth mean for those families that have lived in central Austin and San Antonio for multiple generations; especially of those populations that are historically marginalized neighborhoods within those cities.
From observing US Census data from the years 2010 to 2020 we will be able to observe if this poverty in both San Antonio and Austin continues to persist. Also being able to see any potential changes that have occured within those two cities over that decade.
Eastside Austin, TX
Due to extremely poor investment and management of the infrastructure of many parts of the city initially deemed undesirable in Austin; that space was set aside for people of color to live in accordance to the City Plan of 1927 (Koch & Fowler, 1928). Due to this multiple generations of poverty were created in many pockets of Austin, Texas but especially in the Eastside of Austin, Texas (Goudeau, 2018; Koch & Fowler, 1928).
In 1938, then Congressman Lyndon Bains Johnson spoke on a radio address called the “Tarnish of the Violet Crown” where he speaks of himself walking around Austin on Christmas Day seeing the “absolutely devastating poverty”. (Goudeau, 2018) From his efforts once US President Austin was one of three cities to get federally-funded housing projects in the country; Rosewood Courts for Blacks, Santa Rita Courts for Hispanics and Chalmers Courts for Whites. (Goudeau, 2018)
Since 2010 areas such as the neighborhood Johnston Terrance located east of the city was ranked fourth in the country as one of the fastest gentrifying neighborhoods in the US; this is measured over a 5-year span (Leon, 2019). Neighborhoods in Austin that have historically been home to African-Americans and Hispanic residents will lose their cultural character and become enclaves for largely white and wealthier residents.” (Leon, 2019).
Westside San Antonio, TX
The degree rigidity of redlining and political misrepresentation of much of those areas in San Antonio that has experienced generational poverty such as the Westside was so egregious that the US Justice Department in 1977 had to step in and revised the voting charter in place at that time into a new charter that comprised of 10 city council districts (Miller, 2021).
San Antonio, TX due to its geographic location is very prone to major flooding especially in the more downtown areas that represent central San Antonio. After one particular flood in 1921 occurred the overall devastation that occurred in central San Antonio left the downtown area completely flooded with large amounts of property damage whereas areas like the Westside families homes completely washed away where close to if not more than 100 people were pronounced dead or missing due to this flood especially in the Westside area of the city (Miller, 2021).
After this flood the majority of investment was placed with the downtown area as the main area to protect from the flooding as well as parts of northern San Antonio. For the rest of the city such as the Westside some rivers and canals were widened but no where near the degree of investment was placed into those communities as was the downtown area and the Northside (Miller, 2021).
A few decades after this flood in 1968 a documentary called Hunger in America visited some of the most impoverished areas of the country that experienced extreme hunger San Antonio, TX being one of them (Davies, 2018).
With this continued observed poverty found in the Westside of San Antonio as well as the East Austin area we will see how these cities look in general over time but will be able to spatially observe these areas over time as well to see what has occured between the years of 2010-2020.
Data & Methods
For this analysis we will be observing the Westside of San Antonio in comparison with various other demographic groups as well as San Antonio as a whole for the year of 2020. Observations of descriptive statistics will be observed for that year. The index variable of the “Westside” is constructed using the census tracts 1105, 1106, 1107, 1601, 1602, 1605.01, 1605.02, 1606, 1607.01, 1701.01, 1701.02, 1702, 1703, 1704.01, 1704.02, 1707, 1708, 1709, 1710, 1711, 1712, 1713.01, 1714.02, 1715.01, 1715.02. Numerous socio-economic and demographic variables are reviewed. The data used is from the American Community Survey 5-year estimates (2016-2020).
From here we will then observe the Metropolitan Statistical Areas (MSA) for both San Antonio, Texas & Austin, Texas for the years of 2010 & 2020. Again we observe various demographic and socio-economic variables for both of these MSA areas. This was done by gathering MSA data from the US Census for those two waves. For Austin, the surrounding urban areas of Round Rock and San Marcos are captured to be identified as the Austin Metroplex for 2010. For the Austin Metroplex in 2020 it captures the surrounding urban areas of Round Rock & Georgetown. For San Antonio, the surrounding area of New Braunfels is captured to be identified as the San Antonio Metroplex for both years of 2010 and 2020.
Finally we will observe various predictor variables spatially per census tracts for both Bexar County and Travis County for the years of 2010 & 2020. This is done using the American Community Survey 5-year estimates for both waves (2016-2020 & 2006-2010).
This analysis was done using both Microsoft Excel & R statistical software.
Results
Descriptive Statistics
the Westside of San Antonio; ACS 5-year estimates (2016-2020)
The Westside is much younger with an elderly population about on par with the city. The sex ratios show healthy fertility and being a predominantly male workforce. Educational disparities in higher education in the Westside when compared to all other groups are very prevalent with those who live in San Antonio almost 5 times more likely to earn a bachelors degree or higher compared to those living in the Westside. Latinos who live in San Antonio are more than 3 times more likely to earn a bachelors degree or higher than those who live in the Westside. With Non-Hispanic whites being almost 8 times more likely to earn a bachelors degree or higher compared to those Westside residents. A Westside population that is at least 93% Latino in composition.
When observing overall poverty the Westside experiences the highest compared to all other groups. With families in the Westside experiencing poverty double the rate of those families in San Antonio and those Latino families in San Antonio. With Westside families almost 5 times more likely to experience poverty than those families that are Non-Hispanic white.
Finally it is seen again with those who are with out health insurance notably much higher in the Westside compared to all other groups.
Homeownership in the Westside is higher than the city of San Antonio. When observing the rest of the city during 2020, a migration of Latinos appears (3.5%) within the last year but almost double is found for non-Hispanic whites (7.14).
The majority of these non-Hispanic whites are males and are much older. These non-Hispanic whites exhibit the lowest fertility and overall poverty when compared to all other groups. They are also the most insured compared to all other groups in the table. They also have the highest medium household income, more than double that of the Westside.
Metropolitan Statistical Area Observations - Austin and San Antonio (2010-2020)
Total Population
Code
knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//total pop_1.png") 
When observing the past decade between these two metroplex’s they both experienced growth with the Austin Metroplex having the largest growth of 546233 compared to 452429 for the San Antonio Metroplex. Overall, the Central Texas area that observes these metroplex’s experienced a growth of 998662 from 2010 to 2020.
Much of this growth happening north of the I-35 corridor in the Austin Metroplex. These are initial signs of higher numbers of those migrating to the Austin Metroplex compared to those migrating to the San Antonio Metroplex. Also, could be signs of differing fertility and potential fertility growth between the two metroplex’s which will be observed.
For the Central Texas region only observing both metroplex’s, the sum of the total population of the two metroplex’s in the year of 2010 was 3,685,353. This sum of the total population has grown in 2020 to 4,684,015. The Texas population in 2020 according to the US Census was 29.36 million. Over one-seventh of the total population in the state of Texas is estimated to be found when observing the population of both metroplex’s alone. Further evidence of a growing Megalopolis in the Central Texas region.
Age-Sex Pyramids
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knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//age pyramid_1.png")
In 2020 for San Antonio, only one population bulge is found at age intervals 25-29 with a steady decline found for both males and females as aging progresses.
In 2020 for Austin, there is a large bulge of population for the age intervals of 25-29 lasting till 35-39 before a sharp decline in the population occurs.
When comparing the two metroplex’s in 2020 San Antonio has a much younger population with those under the age of 18 and a much larger elderly population when compared to Austin. Although both metroplex’s share a similiar point of population bulging within the pyramid around the age interval of 25-29, the overall population is much more concentrated around this age interval in the Austin metroplex whereas San Antonio’s population is much more equally spread across the observed age groups.
New Residents that moved into the county
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knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//new resident_1.png")
The Austin Metroplex always had a higher internal migration (observing those moving from outside the county and a different state) and external migration (those who moved abroad) with a percentage of those 1 year of age and older who moved into the county as a resident was about 12 and 13 percent for the years of 2020 and 2010 in Austin, respectively. A decrease is shown within the decade of about 1.5% in San Antonio.
For the Austin metroplex the population has always encompassed a newly resident population from outside of the county of over 10%. Overall, the San Antonio Metroplex has never surpassed 10% of their new residents being from outside of the county.
Individuals & Children living in poverty
Code
knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//MSA poverty_1.png")
When looking at the Austin Metroplex a decrease in the percentage of persons living in poverty as well as those living in poverty under the age of 18 over the decade.
Compared to the San Antonio Metroplex, a decrease in the percentage of those in poverty for both populations observed is found but only by about 2%-4% for those persons in poverty as well as those in poverty under the age of 18, respectively.
Compared to the Austin Metroplex a difference of 6% for the total percentage of those in poverty as well as 8% of those under the age of 18 living in poverty in the metroplex.
The San Antonio Metroplex overall has shown higher percentages of poverty for the total population as well as those in poverty under the age of 18.
Percentage of those living in poverty per ethnicity
Code
knitr::include_graphics("C://Users//BTP//Documents//Inequality 23//Final//Final Project Pics//MSA ethnicity_1.png")
When observing the Austin Metroplex in 2010 it had very high percentages of blacks (25%) and Latinos (26%) living in poverty compared to whites (9%). A large decrease is found in 2020 for those two populations of about an 8% for blacks and 12% for Latinos; only a slight decrease in poverty for whites found of about 2%.
When observing the San Antonio Metroplex, those non-Hispanic blacks throughout the decade of 2010-2020 maintained a relatively similar percentage living in poverty with a noticeable decrease for those Latinos living in poverty of about 5%. The white population also stayed the same throughout the decade being much lower than the other two populations.
When observing the two metroplex’s San Antonio has overall higher poverty but those who are Non-Hispanic whites tend to maintain the same levels of poverty in both Austin and San Antonio between the years of 2010 to 2020. With the Austin metroplex having the largest decrease in overall poverty per ethnicity compared to the San Antonio metroplex.
Spatial Analysis
Bexar County 2020 variables
Code
bexar2020<-get_acs(geography = "tract",
state="TX",
county = c("Bexar"),
year = 2020,
variables=c("B07013_005E", #Estimate!!Total!!Same house 1 year ago!!Householder lived in owner-occupied housing units
"B07013_004E",
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES
"B06011_001E",
#Median Income in past 12 months
"B01003_001",
#Total Population
"B01001I_001",
#Total Hispanics/Latinos
"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families)
"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY
"B15003_022E",
#Estimate!!Total:!!Bachelor's degree
"B15003_001E",
#summary_var Estimate!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B05002_013E",
#Estimate!!Total:!!Foreign born
"B05002_001E"),
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS
geometry = T, output = "wide")
#create a county FIPS code - 5 digit
bexar2020$county<-substr(bexar2020$GEOID, 1, 5)Travis County 2020 Variables
Code
travis2020<-get_acs(geography = "tract",
state="TX",
county = c("Travis"),
year = 2020,
variables=c("B07013_005E", #Estimate!!Total!!Same house 1 year ago!!Householder lived in owner-occupied housing units
"B07013_004E",
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES
"B06011_001E",
#Median Income in past 12 months
"B01003_001",
#Total Population
"B01001I_001",
#Total Hispanics/Latinos
"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families)
"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY
"B15003_022E",
#Estimate!!Total:!!Bachelor's degree
"B15003_001E",
#summary_var Estimate!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B05002_013E",
#Estimate!!Total:!!Foreign born
"B05002_001E"),
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS
geometry = T, output = "wide")
#create a county FIPS code - 5 digit
travis2020$county<-substr(travis2020$GEOID, 1, 5)Bexar County 2010 Variables
Code
bexar2010<-get_acs(geography = "tract",
state="TX",
county = c("Bexar"),
year = 2010,
variables=c("B07013_005E", #Estimate!!Total:!!Householder lived in owner-occupied housing units
"B07013_004",
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES
"B06011_001E",
#Median Income in past 12 months
"B01003_001",
#Total Population
"B01001I_001",
#Total Hispanics/Latinos
"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families)
"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY
"B15002_015E",
#Estimate!!Total!!Male!!Bachelor's degree
"B15002_032E",
#Estimate!!Total!!Female!!Bachelor's degree
"B15002_002E",
#summary_var Estimate MALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B15002_019E",
#summary_var Estimate FEMALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B05002_013E",
#Estimate!!Total:!!Foreign born
"B05002_001E"),
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS
geometry = T, output = "wide")
#create a county FIPS code - 5 digit
bexar2010$county<-substr(bexar2010$GEOID, 1, 5)Travis County 2010 Variables
Code
travis2010<-get_acs(geography = "tract",
state="TX",
county = c("Travis"),
year = 2010,
variables=c("B07013_005E", #Estimate!!Total:!!Householder lived in owner-occupied housing units
"B07013_004",
#summary_var Estimate!!Total!!Same house 1 year ago GEOGRAPHICAL MOBILITY IN THE PAST YEAR BY TENURE FOR CURRENT RESIDENCE IN THE UNITED STATES
"B06011_001E",
#Median Income in past 12 months
"B01003_001",
#Total Population
"B01001I_001",
#Total Hispanics/Latinos
"B17013_002E",
#Estimate!!Total:!!Income in the past 12 months below poverty level: (Families)
"B17013_001E",
#summary_var Estimate!!Total:POVERTY STATUS IN THE PAST 12 MONTHS OF FAMILIES BY HOUSEHOLD TYPE BY NUMBER OF PERSONS IN FAMILY
"B15002_015E",
#Estimate!!Total!!Male!!Bachelor's degree
"B15002_032E",
#Estimate!!Total!!Female!!Bachelor's degree
"B15002_002E",
#summary_var Estimate MALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B15002_019E",
#summary_var Estimate FEMALES!!Total:EDUCATIONAL ATTAINMENT FOR THE POPULATION 25 YEARS AND OVER
"B05002_013E",
#Estimate!!Total:!!Foreign born
"B05002_001E"),
#summary_var Estimate!!Total:PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS
geometry = T, output = "wide")
#create a county FIPS code - 5 digit
travis2010$county<-substr(travis2010$GEOID, 1, 5)Variables Recoded For 2020 Bexar County
Code
#rename variables and filter missing cases
bexar2020_1<-bexar2020%>%
mutate(
homeown2020= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar/Travis County per census tract
Latinos2020=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar/Travis County per census tract
bachelors2020= (B15003_022E/B15003_001E)*100,
#Percentage of bachelors degrees in Bexar/Travis County per census tract
medincome2020=B06011_001E,
#Median income in Bexar/Travis County per census tract
fampov2020=(B17013_002E/B17013_001E)*100,
#Percentage of family poverty in Bexar/Travis County per census tract
foreignb2020=(B05002_013E/B05002_001E)*100) %>%
na.omit()Variables Recoded For 2020 Travis County
Code
#rename variables and filter missing cases
travis2020_1<-travis2020%>%
mutate(
homeown2020= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar/Travis County per census tract
Latinos2020=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar/Travis County per census tract
bachelors2020= (B15003_022E/B15003_001E)*100,
#Percentage of bachelors degrees in Bexar/Travis County per census tract
medincome2020=B06011_001E,
#Median income in Bexar/Travis County per census tract
fampov2020=(B17013_002E/B17013_001E)*100,
#Percentage of family poverty in Bexar/Travis County per census tract
foreignb2020=(B05002_013E/B05002_001E)*100) %>%
na.omit()Variables Recoded For 2010 Bexar County
Code
#rename variables and filter missing cases
bexar2010_1<-bexar2010%>%
mutate(
homeown2010= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar County per census tract
Latinos2010=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar County per census tract
bachelors2010= ((B15002_015E+B15002_032E)/(B15002_002E+B15002_019E))*100,
#Percentage of bachelors degrees in Bexar County per census tract
bachelors2010men=(B15002_015E/B15002_002E)*100,
bachelors2010women=(B15002_032E/B15002_019E)*100,
medincome2010=B06011_001E,
#Median income in Bexar County per census tract
fampov2010=(B17013_002E/B17013_001E)*100,
#Percentage of family poverty in Bexar County per census tract
foreignb2010=(B05002_013E/B05002_001E)*100) %>%
na.omit()Variables Recoded For 2010 Travis County
Code
#rename variables and filter missing cases
travis2010_1<-travis2010%>%
mutate(
homeown2010= (B07013_005E/B07013_004E)*100,
#Percentage of those who are homeowners in Bexar County per census tract
Latinos2010=(B01001I_001E/B01003_001E)*100,
#Percentage of Latinos in Bexar County per census tract
bachelors2010= ((B15002_015E+B15002_032E)/(B15002_002E+B15002_019E))*100,
#Percentage of bachelors degrees in Bexar County per census tract
bachelors2010men=(B15002_015E/B15002_002E)*100,
bachelors2010women=(B15002_032E/B15002_019E)*100,
medincome2010=B06011_001E,
#Median income in Bexar County per census tract
fampov2010=(B17013_002E/B17013_001E)*100,
#Percentage of family poverty in Bexar County per census tract
foreignb2010=(B05002_013E/B05002_001E)*100) %>%
na.omit()Data Cleaning
Bexar & Travis County Data Cleaning
Code
library(tmap)
library(tmaptools)Percentage of Family Poverty
Code
bexar2020fampov <- tm_shape(bexar2020_1)+
tm_polygons("fampov2020", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Family Poverty per Census Tract in Bexar County (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2020fampov <- tm_shape(travis2020_1)+
tm_polygons("fampov2020", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Family Poverty per Census Tract in Travis County (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bexar2010fampov <- tm_shape(bexar2010_1)+
tm_polygons("fampov2010", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Family Poverty per Census Tract in Bexar County (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2010fampov <- tm_shape(travis2010_1)+
tm_polygons("fampov2010", title="Percentage of Family Poverty per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Family Poverty per Census Tract in Travis County (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
fampovcomb<- tmap_arrange(bexar2020fampov, bexar2010fampov, travis2020fampov, travis2010fampov)
fampovcomb
When observing family poverty between Bexar County and Travis County we can again see that Bexar County has overall higher family poverty compared to Travis County. The extreamly large decline of family poverty that is found in Travis County is striking whereas areas that persisted with family poverty of over 40% tended to remain over 40% of families living poverty in San Antonio from the years of 2010 to 2020. The main change for San Antonio would be the slight shift towards the Westside of San Antonio where it seems to be concentrating over the decade.
Percentage of Owner-Occupied Homes
Code
bexar2020home <- tm_shape(bexar2020_1)+
tm_polygons("homeown2020", title="Percentage of owner-occupied homes per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Bexar County Homeownership; Percentage of Owner-Occupied Homes, Same house the past year", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bexar2010home<-tm_shape(bexar2010_1)+
tm_polygons("homeown2010", title="Percentage of owner-occupied homes per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Bexar County Homeownership; Percentage of Owner-Occupied Homes, Same house the past year", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2020home <- tm_shape(travis2020_1)+
tm_polygons("homeown2020", title="Percentage of owner-occupied homes per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Travis County Homeownership; Percentage of Owner-Occupied Homes, Same house the past year", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2010home<-tm_shape(travis2010_1)+
tm_polygons("homeown2010", title="Percentage of owner-occupied homes per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Travis County Homeownership; Percentage of Owner-Occupied Homes, Same house the past year", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
homeowncomb <- tmap_arrange(bexar2020home, bexar2010home, travis2020home, travis2010home)
homeowncomb
When observing owner-occupied homes from 2010 to 2020 we can see a decrease in homeownership in both counties with a slightly larger decrease being seen in Bexar county.
A main difference between the counties would be seen in San Antonio homeownership with the Westside, Eastside, and Southside remaining relatively constant in homeownership compared to the more northern parts of San Antonio where a decrease can be seen.
While in Austin those areas that tended to be historically marginalized such as the southside and eastside has declined slightly in homeownership where the Westside of Austin remains to show the highest rates of homeownership over the entire decade.
Observing these spatial differences shows that those historically marginalized areas in San Antonio such as the Westside tend to have overall higher rates of homeownership and maintained that homeowner status over the decade of 2010 to 2020 whereas historically marginalized areas in Austin such as the Eastside saw a decline in homeownership over that period of time.
Percentage of those with a bachelors degree
Code
bexar2020bachelors <- tm_shape(bexar2020_1)+
tm_polygons("bachelors2020", title="Percentage of those with a bachelors degree per census tract (2016-2020)", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="San Antonio Educational Attainment; Percentage of those with a bachelors degree", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bexar2010bachelors<-tm_shape(bexar2010_1)+
tm_polygons("bachelors2010", title="Percentage of those with a bachelors degree per census tract (2006-2010)", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of those with a bachelors degree", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2020bachelors <- tm_shape(travis2020_1)+
tm_polygons("bachelors2020", title="Percentage of those with a bachelors degree per census tract (2016-2020)", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Austin Educational Attainment; Percentage of those with a bachelors degree", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2010bachelors<-tm_shape(travis2010_1)+
tm_polygons("bachelors2010", title="Percentage of those with a bachelors degree per census tract (2006-2010)", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of those with a bachelors degree", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bachcomb<- tmap_arrange(bexar2020bachelors, bexar2010bachelors, travis2020bachelors, travis2010bachelors)
bachcomb
When observing the percentage of those who earned a bachelors degree we can see both counties polarizing to specific areas of the city.
From 2010 to 2020 only in the Northside of San Antonio saw a true increase of those with a bachelors degree while in Austin the Westside only saw increases of those with a bachelors degree. With those who have a bachelors degree tending to be concentrated in that Westside of Austin.
Austin overall from observing the given scales exhibits a higher proportion of their population that has a bachelors degree compared to San Antonio. With the population in the Westside of Austin being much more spread out across census tracts whereas in San Antonio it is clustering more into specific census tracts in the Northside of the decade being much less dispersed.
Percentage of those who are Latino
Code
bexar2020latino <- tm_shape(bexar2020_1)+
tm_polygons("Latinos2020", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Latinos in San Antonio, TX (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bexar2010latino<-tm_shape(bexar2010_1)+
tm_polygons("Latinos2010", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Latinos in San Antonio, TX (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2020latino <- tm_shape(travis2020_1)+
tm_polygons("Latinos2020", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Latinos in Austin, TX (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2010latino<-tm_shape(travis2010_1)+
tm_polygons("Latinos2010", title="Percentage of Latinos per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Percentage of Latinos in Austin, TX (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
latinoscomb<- tmap_arrange(bexar2020latino, bexar2010latino, travis2020latino, travis2010latino)
latinoscomb
When observing the population that is Latino we can observe in Bexar county the Latino population has increased but is very much concentrated in the Westside and Southside neighborhoods of the city of San Antonio.
When observing Austin almost all of the Latino population is found on the eastside, southeast, and northside’s of the city. The Westside of Austin from 2010 to 2020 never truly had a census tract exhibit a proportion of their population being Latino over 20%.
The areas that were prodominantly Latino in Austin in 2010 maintained that status in 2020 except for the downtown eastside census tracts that seem to have decreased in some cases at least 60% in the proportion of the population that was Latino over the decade.
Median Income
Code
bexar2020medincome <- tm_shape(bexar2020_1)+
tm_polygons("medincome2020", title="Median Income per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Median Income per Census Tract in San Antonio, TX (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
bexar2010medincome<-tm_shape(bexar2010_1)+
tm_polygons("medincome2010", title="Median Income per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Median Income per Census Tract in San Antonio, TX (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2020medincome <- tm_shape(travis2020_1)+
tm_polygons("medincome2020", title="Median Income per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Median Income per Census Tract in Austin, TX (2020)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2016-2020) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
travis2010medincome<-tm_shape(travis2010_1)+
tm_polygons("medincome2010", title="Median Income per census tract", palette="Blues", style="pretty", n=5 )+
tm_format("World", title="Median Income per Census Tract in Austin, TX (2010)", legend.outside=T)+
tm_scale_bar()+
tm_credits("5-Year (2006-2010) American Community Survey \nCalculations by B.A. Flores (M.S.) \nthe University of Texas at San Antonio", size = 0.5, position=c("LEFT"))+
tm_compass()
medincomecomb<- tmap_arrange(bexar2020medincome, bexar2010medincome, travis2020medincome, travis2010medincome)
medincomecombSome legend labels were too wide. These labels have been resized to 0.51, 0.48. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.Some legend labels were too wide. These labels have been resized to 0.51. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.Some legend labels were too wide. These labels have been resized to 0.51, 0.48. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
When observing median income for Bexar County only the Northside experienced growth economically with clustering being found to happen in far north Bexar County and a small area of the northern downtown San Antonio area. The rest of the city outside of the Northside overall maintained a average median income of about $20,000. Whereas most areas of the Northside have median incomes atleast double that amount.
In Travis County, the Westside continued to maintain to exhibit the highest number of neighborhoods earning atleast triple in median income compared to the rest of the city of Austin. This maintained over the decade of 2010 to 2020 but the wealth seems to have concentrated in specific census tracts, just as what has happened in San Antonio over the same amount of time.
There is an extreme showing of clustering being found in what would be downtown Austin for about 1 or 2 census tracts. The rest of Austin saw a decline in median income with the eastside and southside closest to downtown Austin saw a slight increase in median income.
Conclusions
When observing the Westside and its relation to the overall growth of San Antonio compared to historically marginalized areas in Austin such as the Eastside in relation to Austin’s growth; many similarities are found such as the higher poverty, lower overall income, and much higher proporitons of having Latinos.
With the main difference being found in homeownership where the Westside and other historically marginalized population areas in San Antonio have maintained their homeowner status while more higher economic status census tracts found in the Northside saw a decrease over the decade. While in Austin the Westside maintained its homeowner status while areas like the Eastside saw a decline as well as in other areas of Austin where high proportions of Latinos are found.
Also when observing Bexar County and Travis County spatially they are both extreamly rigid in nature socio-economically and demographically. Being that areas in both cities still show signs of rigid segregation and redlining that was historically implemented.
The large decrease in poverty found in Austin coupled with the rest of the findings from the analysis shows that this is most likely due to displacement of those families that lived in poverty due to various mechanisms of gentrification.
As these two cities continue to grow both exhibit vary similar outcomes and spatially show that they both pass vary similar policies to where this spatial data found is segregated and clustered in such a way. No variable observed in this analysis could be explained away as randomness or dispersed in its nature in any way.
Further research is needed to continue to analyze the growing population around the I-35 corridor so that proper urban planning can be implemented rather than un-checked urban sprawl. Where those living in poverty tend to be negatively effected the most from improper planning of housing, resources, and opportunity structures that help create upward mobility. Leaving them to fend for themselves.
References
Davies., D.M. (2018, June 8) Documentary That Exposed San Antonio Poverty. Texas Public Radio. https://www.tpr.org/san-antonio/2018-06-08/hunger-in-america-the-1968-documentary-that-exposed-san-antonio-poverty
Gottdiener, M., Hohle, R., & King, C. (2019). The New Urban Sociology (6th ed.). Routledge. https://doi.org/10.4324/9780429244452
Goudeau, A., (2018, May 2) Austin’s gentrification problem: How we got here. KVUE ABC Austin, TX. https://www.kvue.com/article/news/local/austins-gentrification-problem-how-we-got-here/269-548075155
Koch & Fowler (1928, January 14). “A City Plan for Austin, Texas”. City of Austin. Retrieved March 26, 2021. https://repositories.lib.utexas.edu/handle/2152/65853?show=full
Leon L. D., (2019, April 26). Austin neighborhood named top 10 fastest-gentrifying neighborhood in America. KVUE ABC Austin, TX. https://www.kvue.com/article/money/economy/boomtown/austin-neighborhood-named-top-10-fastest-gentrifying-neighborhood-in-america/269-78a5ac78-a8ef-4503-9200-d869ecffdc98