1. Corrie Hannah Mentor: Dr. Stuart E. Marsh, Office of Arid Lands Studies NASA Space Grant Symposium April 17, 2009 Arizona State University Using Remote Sensing to Map and Manage Buffelgrass Infestations in Tucson and the Santa Catalina Mountains

2. What is Buffelgrass? Invasive species originally brought from Africa to the Americas for cattlegrazing Threatens to out-compete native species Potential to transform the fireproof Arizona Sonoran Desert into a burning savannah National Fire Plan http://www.forestsandrangelands.gov (Pennisetum ciliare)

3. What is Remote Sensing? A science that uses satellite imagery and aerial photography to identify features and natural processes on the Earth’s surface

4. Objectives Identify a practical method of mapping and managing buffelgrass in Southern Arizona Determine benefits of different spectral and spatial satellite and aerial imagery to locate buffelgrass

5. Identifying Remotely Sensed Imagery to Map Buffelgrass Type Spectral Resolution Spatial Resolution PAGAerial Photography 3 color bands1ft DOQQAerial Photography 3 color bands plus near infrared 1m LandsatSatellite Imagery 6 reflective bands30m ASTERSatellite Imagery 3 color & near infrared/6 shortwave infrared bands 15m/30m

6. Methods Identified remotely sensed imagery Manually digitized high resolution aerial imagery Located buffelgrass locations: Presence & Absense Fieldwork! Validated digitized ground control points Classified buffelgrass locations in images Accuracy assessments Area of Study: Santa Catalina Mountains North of Tucson

7. Heads-up Digitizing Buffelgrass!!!

8. Supervised Classifications 1ft Aerial Image 30m ASTER Satellite Imagery 1m Aerial Image 30m Landsat Satellite Imagery Red polygon areas indicate buffelgrass presence

9. Texture Filters and Topography 1ft Aerial Image + Texture + Topography1m Aerial Image + Texture + Topography 15m ASTER Satellite Image + Topography30m Landsat Satellite Image + Topography Red polygon areas indicate buffelgrass presence

10. Multi-temporal Stacks 15m ASTER scene composite: 4/22/2006 and 7/18/2006 15m ASTER scene composite: 7/18/2006 and 11/27/2008 15m ASTER scene composite + Topography: 4/22/2006 and 7/18/2006 15m ASTER scene composite + Topography: 7/18/2006 and 11/27/2008 Red polygon areas indicate buffelgrass presence

11. Binary Ensemble Yellow = 5 or more models predict buffelgrass Red = 10 or more models predict buffelgrass Green/White = less than 5 models predict buffelgrass A composite stack of the twenty classifications: buffelgrass presence or absence

12. Place where the most models were successful at locating buffelgrass Photo from the Field 1ft Aerial photographyBinary Ensemble: Close-up

13. Place where most models were not as successful at locating buffelgrass Photo from the Field 1ft Aerial photographyBinary Ensemble: Close-up

14. Photo from the Field 1ft Aerial photography Binary Ensemble: Close-up Place where the most models were successful at locating buffelgrass

15. Results High-resolution imagery was more reliable than moderate-resolution imagery at locating buffelgrass Manual digitization of the1ft aerial photography was the most accurate method of classifying buffelgrass Of the automated classified images, the 1ft aerial photography with topography and texture was the most accurate

16. Conclusion We suggest that 1ft resolution or higher aerial photography, which covers much of the infested areas surrounding Tucson, should be used to most effectively map and manage buffelgrass infestations in the future.

17. Acknowledgements Aaryn D. OlssonAaryn D. Olsson Kyle A. HartfieldKyle A. Hartfield Stuart E. MarshStuart E. Marsh Barron J. OrrBarron J. Orr Grant CasadyGrant Casady Arizona Remote Sensing CenterArizona Remote Sensing Center Office of Arid Lands StudiesOffice of Arid Lands Studies NASA Space Grant ConsortiumNASA Space Grant Consortium

18. Thank You