By: GeoTrek

Hunter Krenek: Remote Sensing analyst & GIS analyst Joe Dowling: Assistant Project Manager & GIS analyst Peter Vogt: Website Designer & GIS analyst Alfredo Perez: Project Manager & GIS specialist

Purpose: Build a functioning geodatabase Create a brochure with map atlas Land cover classification of huisache This project is designed to enable future research and assist in the maintenance required to keep up the ranch. The map atlas and brochure will also be used to help navigate the ranch to visitors, research partners, and stakeholders

Freeman Center is 4,200 acres of land in the Texas hill country That is owned by Texas State University Goals are to provide effective stewardship of the center’s ecosystem and infrastructure

Advantages of ArcGIS Digital copy of files Perform spatial analysis Organization Attribute tables File type Display with multiple projections

Cultural Features  Roads  Boundary  Fences  Creeks  Buildings  Pastures  Wells  Drinkers

Data Texas Parks and Wildlife Department (TPWD) Texas Natural Resources Information System (TNRIS) Capital Area Council of Governments (CAPCOG) Digital Ortographic Quarter Quad (DOQQ).kmz file from Google Earth GPS data collection

Our First step was to convert the.kmz files to shape files that could be used in ArcMap.

The newly created shapefiles were then used to populate the geodatabase.

Creating Topology A topology feature class was created to set rules for feature relationships.

Creating Topology Rules Must not have gaps Contains points Must be inside Must not have dangles Must not self-intersect Must not overlap Must be properly inside boundary

Creating Topology Run error reports based on rules created in the topology feature class Fix or omit errors Topology edit tools used: Extend Trim

Creating Feature Classes A polygon feature class was created to encompass the pastures and buildings present on the ranch. The pasture feature class was created based of the fences layer digitized from the original.kmz. The buildings feature class was created by performing a trace while using the 6’’ satellite imagery as a georeference.

Edit Attribute Tables For the roads, fences, pastures, and creeks layers the calculate geometry tool was used to convert distance from decimal degrees to meters and acres. For the fence layer the field calculator was also used to categorize the fences into high fence or low fence.

The boundary layer was used to extract by mask the DOQQ to limit the extent to our study area.

6’’ satellite imagery was used to georeference the locations of features such as: Buildings Drinkers Wells Fences Roads

Website Compilation

Manifold was used to generate a map document that was then exported to a website file.

The Freeman Center is experiencing a huisache encroachment on its property. The Freeman Center has requested a land cover classification for huisache be created for inclusion in the geodatabase provided by GeoTrek.

2008 and m resolution NAIP Imagery (TNRIS) Freeman Center Boundary Line Shapefile SSURGO Soil Survey Shapefile Huisache tree GPS points

Obtain the NAIP imagery from 2008 and 2012 Create mosaic images using Erdas Imagine Extract AOI from mosaic images The extracted false-color composite images of the Freeman Center were then used to perform a landcover classification with the following classes: Water Developed Barren Forest/Shrubland Herbaceous (grassland)

Training data Made using the Grow Region and Polygon Tools with the Signature Editor in Erdas Imagine Google Earth used to make a visual confirmation of the landcover type. Due to poor spectral separability in the training data the Forest and Shrubland classes were merged to yield one class with greatly improved separability.

Accuracy Assessment: Accuracy Assessments were performed with an expected accuracy of 80% and an acceptable error of 10%. A sample size of 64 reference points was derived using Binomial Probability Theory. N=[2 2 (80)(20)]/10 2

After completion of the initial landcover classification, the Forest/Shrubland class was extracted to narrow the AOI for the huisache classification. The GPS point data gathered on site was then used in creating training data. Identified huisache trees in the false-color composite images

Spectral Separability of Huisache vs Mesquite: Positively identifying the preferred soil types of huisache and mesquite GPS Data Point Sampling Design: Training Data and Accuracy Assessments Determining the Best Imagery to Use: NAIP imagery: Good: 1 meter spatial resolution Publicly available Bad: First included the NIR band in images comprised of 3 bands, eschewing the blue band in exchange for NIR.

Task 1: Implement functioning geodatabase Attribute tables with correct measuring units for each feature I e: pastures = acres Maps FEMA Q3 Navigation Soils Ecological Systems website with interactive map

Functional Geodatabase

Correct Unit Measurement in Attribute Tables

Database Composite

Fences

Roads

Drinkers

Wells

Pastures

Buildings

Texas Ecological Systems Map

Remote Sensing analysis produced the following: Classified 2012 Map Image Training Data with polygons 2012 NDVI Map Image 2012 Tasseled Cap Transformation Map Image Methodology Constraints and Advice for Future Researchers

2012 Classified Map Image Accuracy = 85.94% Kappa statistic =.8187

2012 Tasseled Cap Transformation Map Image

2012 NDVI Map Image

Interactive web map

Task 1- Before our team started working on FreemanCenter.gdb., The Freeman Center only possessed.kmz files created using GoogleEarth, and had zero spectral data. The attribute fields of length and area were calculated from degrees into meters and acres respectively. The Freeman Center can now have access to a geodatabase that can be used to make maps and for surface modeling. Task 2- A viable Freeman Center huisache tree classification will be a topic for ongoing research at Texas State University. Although this initial investigation met with setbacks, the project report will contribute to future progress in identifying the spec- tral signature of this species.