William H. Farrand Space Science Institute Boulder, CO

1. Using AVIRIS Data to Map and Characterize Subaerially and Subaqueously Erupted BasalticVolcanic Tephras: The Challenge of Mapping Low Albedo Materials William H. Farrand Space Science Institute Boulder, CO

2. Rationale for Research • Earlier work mapping basaltic volcanic fields using 1989 AVIRIS data was frustrated by low SNR • Features of interest in basaltic volcanic fields can include hydrovolcanic edifices: tuff rings and tuff cones • Project thus has relevance for research on a search for hydrovolcanic features on Mars

3. Study Areas • Pavant Butte/Tabernacle Hill, Utah • Tuff cone and tuff ring formed subaqueously, sub-aerial lava flow • AVIRIS data collected October 8, 2002 • Mauna Kea/Mauna Loa, Hawaii • Recent basaltic volcanic ash deposits and lava flows • AVIRIS data collected April 14, 2000

4. Pavant Butte/Tabernacle Hill • Pavant Butte is a basaltic tuff cone formed in glacial Lake Bonneville approximately 16,000 years ago • It, and the Tabernacle Hill tuff ring to the south, are part of the Black Rock Desert volcanic field of southwestern Utah

7. Pavant Butte / Tabernacle Hill scene(R = 1.7 mm, G = 0.8 mm, B = 0.45 mm)

10. The Value of Studying Dark Materials • Many materials of interest have low albedo • Basaltic lava flows • Water • Man-made features (roads, runways, buildings) • Being able to map materials in basaltic terrains is of direct relevance for studies of Mars

11. The Power of the Dark Side • “Luke… if only you knew the power of the Dark Side”-- Darth Vader, Star Wars Episode 5 “The Empire Strikes Back”

12. How well do various processing algorithms work on low albedo scenes? • All algorithms are affected by inherent challenge of less signal returned from dark terrains • Spectral Mixture Analysis is affected by albedo differences • SAM and approaches using continuum removed data (Spectral Feature Fitting, Tetracorder) should be unaffected

13. Spectral Mixture Analysis r = aM + nr is a m X 1 vector, n= residual error -- where m = # of bands a pX1 vector of abundances -- where p = # of endmembers M = (u1… , up) mXp matrix of endmember spectra

14. RMS error • Root Mean Square (RMS) error is used to determine appropriateness of endmembers used and as a gauge of whether further endmembers are required

15. Confusion of dark materials with shade • As originally implemented by Adams et al. at the U. of Washington, SMA makes use of a shade endmember • In non-albedo normalized data the shade endmember can incorporate low albedo materials such as basalt flows • In the albedo normalized data used in this study, the shade endmember is not used

16. Endmembers • In non-albedo normalized data, using iterative SMA (starting with a small set of endmembers and selecting new endmembers as indicated by RMS error image), high albedo materials are preferentially determined

17. Final RMS error image of Pavant Butte scene (HATCH corrected reflectance) Pavant Butte reflectance endmember spectra. No dark materials required to produce bland RMS error image.

18. Hyperspherical Directional Cosine (HSDC) transform • HSDC is basically an albedo normalization routine • It removes topographically induced and inherent brightness variations so that spectral properties are enhanced

19. HSDC transformed data (R = 1.7 mm, G = 0.8 mm, B = 0.45 mm) Original

20. Basalt fraction image obtained from running SMA on non-transformed (standard reflectance) data Basalt fraction image obtained from running SMA on HSDC transformed data

22. Application of other techniques to HSDC transformed data • Other processing techniques such as Foreground/Background Analysis (FBA) can also benefit from using HSDC transformed data • Example of mapping hydrovolcanic tuffs • Well palagonitized (orange) tuff • Poorly palagonitized (gray) tuff and ash

26. Fractions of poorly palagonitized ash > 0.4 (yellow). Fractions of well palagonitized tuff > 0.4 (red). Pavant Butte composite

27. Tabernacle Hill tuff ring composite Fractions of poorly palagonitized ash > 0.4

28. Composite of 1.7, 0.8, and 0.45 mm bands of HSDC transformed data Composite of 1.7, 0.8, and 0.45 mm bands of un-normalized data

31. Mapping of lava flows using TIMS and NS001 data by Abrams et al. (1991) Mapping of lava flows using SAM on AVIRIS data

32. SAM results for HSDC transformed data SAM results for reflectance data

33. Conclusions regarding processing approaches • SMA results are affected by albedo • Removing albedo through application of HSDC transformation improves results of SMA, and related techniques such as FBA, when applied to dark targets • SAM results are not affected by albedo

34. Results on mapping of volcanic units • Able to map both high albedo palagonite tuff and dark, poorly palagonitized tuff and ash at Pavant Butte and Tabernacle Hill • Mapping results of Mauna Loa lava flows obtained in VNIR through SWIR with AVIRIS compare favorably with combined NS001/TIMS mapping

35. Acknowledgments • Thanks to the AVIRIS team for the collection of the Pavant Butte data • Thanks to Alex Goetz and Eric Johnson of CSES for HATCH correction of Pavant Butte data • Thanks to Gregg Swayze for providing reflectance data of Mauna Kea/Mauna Loa • Research funded in part by NASA OSS grant NAG5-10577