Department of Geography, University of California, Santa Barbara An assessment of correlation between vegetation parameters measured on the ground and endmember fractions from remotely sensed data of varying spatial resolution Seth Peterson Department of Geography, University of California, Santa Barbara

Acknowledgements: USFS - 4 years of funding

Presentation Overview 1) Fire / fuel loads 2) SMA 3) Sample Endmember fractions 4) MESMA 5) Sample Endmember fraction / biomass correlations

Why is fire important? Fuel loads have increased Urban encroachment into wildlands These processes may be different for different ecosystems (study sites are in 5 western states)

How can we study fire fuel loads? Massive amounts of ground-based sampling Small, well-designed ground-based studies to calibrate large area remotely sensed scenes - Correlate different indices and products from image processing techniques with ground-based data

Spectral Mixture Analysis (SMA) Expresses pixel values as mixtures of the scene components, called endmembers (EMs) Typical EMs used are: green vegetation (GV -- e.g. green leaves) nonphotosynthetic vegetation (NPV -- e.g. bark, branches, litter) rocks, soils shade

GV NPV Landsat TM imagery for MCAS Miramar with Endmember fraction images Soil Shade

The mixed pixel problem / Endmember analysis GV Soil NPV ADAR data, 1 m pixels Landsat TM data, 30 m pixels

GV soil soil NPV shade shade GV Feature space plots for the MCAS Miramar Landsat TM scene, with approximate EM locations GV soil shade GV soil NPV shade Band 4 Band 7 Band 3 Band 4

Multiple Endmember SMA (MESMA) - Allows for flexibility in the number of EMs used to model each pixel - Allows for flexibility in the type of EMs used to model each pixel Modeled EM fractions will be most accurate when the fewest, most appropriate EMs are used to model each pixel GV_1 GV_2 soil_1 soil_2 NPV_1 NPV_2 shade_photo shade_phyto Band 4 Band 7

EM Fractions vs. time for stands of chamise chaparral GV NPV Soil Shade

Summary Fire is a problem Remote Sensing is one way to look at it