AUSTIN, T

X

AN ANALY

SIS O

F GROW

TH A

ND DRIV

ING FA

CTORS

RESEARCH GOALS

-Model some driving factors of development for the city

-Employment

-Residence

-Geographical: slope

-Land prices

-Service areas of Technology Industry

AUSTIN’S ABNORMAL GROWTH

-- Part of the Sunbelt region of the Southern US

- this was the fastest growing area in form 1970-1980

-- Traditionally has grown along with the technology industry

-- Rated 8th fastest growing metropolitan areas by CNBC

-2007 growth of 4.5%

-Population of 1,598, 161 in 2007 with addition of 65,800

-- Proximity to other cities: Dallas, Houston, San Antonio

-- Business Climate

-Favorable tax structure

-Labor Laws

-State government favors business

SOURCE: HTTP://WWW.CNBC.COM/ID/23846249/?PHOTO=4

AUSTIN’S CENTERS OF EMPLOYMENT

-- founded for state government central location

-provided a stable economy for growth

-state government jobs = 19% of labor in the city

-- Historically, no deep water transportation for heavily polluting industries such as petrochemicals, refining, chemicals, or steel

-The Chamber of Commerce recruited less-polluting industries

-Has led to quality business without growth restrains of socially unacceptable activities

-more demand to live and work here, quality of life

--has emerged as center for technology business and manufacturing

--besides governmental jobs, most main top employers are part of the technology sector

SOURCE: LYNDON B. JOHNSON SCHOOL OF PUBLIC HEALTH - POLICY STUDY OF AUSTIN

DATA – LED ON THE MAP

--U. S. Census Bureau data

--Interface for Longitudinal Employment Data: http://lehdmap4.did.census.gov/themap4/

--can import shapefiles into ArcMap

--very confusing!

--Basic Steps

Search for place – used “Austin” and “Micropolitan/Metropolitan Areas”

Base Map with county lines, highway data, etc.

Analysis –

1. chose either work place/home area, year (2002 and 2008), labor market segments (all workers)

2. advanced area selection – can pair with home area or add modifications to original selection

DATA - LED ON THE MAPAnalysis –

1. DATA SETTINGS - chose either work place/home area, year (2002 and 2008), labor market segments (all workers)

2. STUDY AREA SELECTION - advanced area selection – can pair with home area or add modifications to original selection

-normal are selection – shows where people are employed who live in the selection area or vice versa

-our output maps use this

-advanced are selection – shows where people are employed who ALSO live in the same area

-can help analyze distance people travel to work place

-not shown in output maps right now, but will continue

DATA – LED ON THE MAP

Analysis –

3. MAP OVERLAY/REPORT options

-work area profile analysis

-Labor Shed Analysis (commute shed if chose home area)

--where workers live who are employed in the selection area

---our output maps defined as this

OUTPUT MAP 1 – CHANGE IN JOB AREA

--imported LED shapefiles of:

1. job area labor shed analysis from

2002

2008

2. LED on the map gives points and thermals

--from thermal files, reclassified the raster

1. changed density to one value

-important assumption or “liberty” taken with the data:

interested in spatial change, where jobs are being created in previously empty space or no job areas rather than increasing density in high value areas

2. with raster calculator, subtracted 2002 data from 2008

3. now have a ring of job development

OUTPUT MAP 1 – CHANGE IN JOB AREA

OUTPUT MAP 2 – CHANGE IN HOME AREA

- Similar to job area, but change to commute shed analysis

- End up with spatial infringement of home area

- Combining the 2 to compare-Can see overall rings of home development around

job development

OUTPUT MAP 2 – CHANGE IN HOME AREA

OUTPUT MAP 3 – HOME CHANGE AND LAND VALUE

-obvious that land value is changing as development happens

-the high land values could be areas under the highest demand

-where job and home growth is happening

-zoomed insert of boundaries and how closely the land value and prices match

OUTPUT MAP 3 – HOME CHANGE AND LAND VALUE

OUTPUT MAP 4 – WELLS AND LAND SLOPE

-correlation between wells and elevation

-historically development has happened along north-south corridor, and growth has occurred where slope is the lowest

-wells data shows the increasing trend of moving away from this linear form

-the areas with the highest slope are seeing the least wells drilled

-we can predict that these will be the last areas to see well development

OUTPUT MAP 4 – WELLS AND LAND SLOPE

OUTPUT MAP 5 - WORKING POINTS INTERPOLATION

-job points, working profile density

-MAIN GIS FUNCTION = Spatial analysis

--from shape file of points, interpolated to form raster to represent density

-Shows two major concentrations of jobs

-government in center

-technology emerging to the north

OUTPUT MAP 5 – WORKING POINTS INTERPOLATION

OUTPUT MAP 6 - INDUSTRIAL ACCESSIBILITY-MAJOR GIS FUNCTION: Network Analyst Service Area calculation

-major employers – selected technology industry

-represents service area according to Network Analyst

-routes shapefile used to create network database

-service area provided in terms of radial distance and roads

-want to add in bus routes and light rail line to look at accessibility for workers

-will continue with network analyst:

-add in major suburban points

-calculate best transport routes between these major residential areas outside of city center and technology employer points

OUTPUT MAP 6 – INDUSTRIAL ACCESSIBILITY

RESEARCH CONCLUSIONS

-Overall, employment has increased where technology industry has increased, and where land prices are lowest

-Residence has directly followed employment, as seen in concentric rings of output map

-Geographically, slope influences where wells can be placed which also influences urban sprawl in terms of single family homes

-Land prices are highest where there is the most spatial growth in jobs, with residential development following this

-Service areas of Technology Industry are covering those areas with the most growth in jobs and population density. The technology Industry is emerging as second concentration of jobs besides governmental.

-We will continue to model future growth regions by a transportation analysis between suburban areas and technology points with Network Analysis.