1. An Analysis of Land Use/Land Cover Changes and Population Growth in the Pedernales River Basin Kelly Blanton-Project Manager Paul Starkel-Analyst Erica Tice-Analyst William Weldon-Analyst Prepared By:

2. Overview  The Pedernales River Basin is an area of approximately 815,000 acres located in the central Texas Hill Country.  Watershed covers the counties of Blanco, Gillespie, Burnett, Hays, Kerr, Kendall, Kimble, and Travis.  Blanco and Gillespie are the counties with the majority of coverage by the Pedernales River Basin.  Prone to water level fluxuation.  Provides habitat for numerous fish and wildlife.  Provides 23% of Lake Travis’ flow, a critical drinking water source for Austin.

3. Problem Statement  Is land use and land cover changing in the Pedernales river basin area?  To solve this problem:  Maps with GIS data analyzed will be beneficial to show change in each individual group  Change over time period and population growth

4. Scope

5. Data  Landsat 8 imagery from the U.S.G.S Earth Explorer site.  Population projection data from Texas Water Redevelopment Board.  Pedernales vector polygon and Road data from TNRIS.  LU/LC data form the Multi- Resolution Land Characteristics Consortium.

6. Methodology: Task 1: Shapefile Creation and Change detection maps  First step: create outline of our study area boundary  Second step: create shapefiles of LU/LC for each of the years  Third step: get a visual representation of LU/LC changes in the area via creation of change detection maps

7. Methodology: Task 2: Population projections  Population projections were pulled from the Texas Water Development Board.  Placed in Excel using a newly created table.  Showing projections through the year 2070 for each county within the study area.

8. Methodology: Task 3: 2014 Update of LU/LC for the Pedernales  Downloaded LANDSAT 8 imagery  Mosaicked together two different images, one with leaves, one with no leaves  Projected and clipped images in ERDAS  Created training data using 4 groups for supervised classification  Ran supervised classification  Transfer supervised classification result to Arcmap from ERDAS  Clip study area from classification result in Arcmap

9. Results  LU/LC experienced a decrease in overall forestland.  Developed, High Intensity Land experienced a nearly 50% increase.  Growing population is a contributing factor.  LU/LC maps of 1992, 2001, 2006, and 2011 data.  Change Detection maps from 2001-2006, 2006-2011, and 2001-2011.  Final deliverable of Updated 2014 map.

18. Discussion  Classifying each land class proved very time consuming and difficult.  Classes were grouped together, presenting a challenge for the computer who had a hard time differentiating these classes.  Led to accuracy issues of overabundant developed land on 2014 map.

19. Conclusion  A decrease in forested areas and an increase in developed land.  LU/LC classification is a very difficult and time consuming process.  To accurately produce a LU/LC classification takes a highly trained and skilled team to analyze differentiate spectrally similar classes.  NAIP imagery is more appealing but not multispectral which is needed for analysis.