1. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: comparing multispectral and hyperspectral observations G.P.Asner and K.B.Heidebrecht

2. Introduction Objective – comparison of multi- and hyper-spectral observations to Objective – comparison of multi- and hyper-spectral observations to decompose remotely sensed data decompose remotely sensed data  Why Important? – Study of impacts of climate variability and land climate variability and land use on vegetation cover use on vegetation cover  Difficulties – small individual canopies - phenological changes - phenological changes - separation of NPV and bare soil in NDVI - separation of NPV and bare soil in NDVI  Approaches – correlation of NDVI - Spectral Mixture Analysis - Spectral Mixture Analysis

3. SMA Assumes linear combination Assumes linear combination Two methods of reflectance Two methods of reflectance coefficient selection coefficient selectionImage-based reflectances used that are likely to exist in the area reflectances used that are likely to exist in the area lack of pure pixels Spectral Libraries data readily collected data readily collected lack of generability and scalability

4. Data used – Image based Landsat TM – commonly available Landsat TM – commonly available Terra ASTER – dense 5-channel sampling at Terra ASTER – dense 5-channel sampling at SWIR2 SWIR2  Terra MODIS – available daily 15-channel sampling of 15-channel sampling of visible and NIR visible and NIR

5. The land under research Chihuahuan Desert, New Mexico Chihuahuan Desert, New Mexico - 210mm ppt per year - 210mm ppt per year - Long-term ecological - Long-term ecological research site research site - mainly grassland and - mainly grassland and shrub shrub  Requirements - low species diversity - low species diversity - strong differences of PV - strong differences of PV and NPV between sites and NPV between sites - nearly constant soil type - nearly constant soil type - few soil crusts - few soil crusts

6. Measurements ADC camera for grassland ADC camera for grassland Ikonos camera for shrubland Ikonos camera for shrubland Areas 8ha each, with 300m N-S Areas 8ha each, with 300m N-S transect established using GPS transect established using GPS  Field Spectroradiometer - measurements every 5m along transects - measurements every 5m along transects - all canopies within 5m of sampling pts measured - all canopies within 5m of sampling pts measured - conversion to reflectance using calibration panel - conversion to reflectance using calibration panel  AVIRIS sensor – NASA ER-2 aircraft altitude 20km - pixels 19m x 19m - pixels 19m x 19m

7. Model and Analysis Auto MCU Auto MCU - Fully automated Monte Carlo based - Fully automated Monte Carlo based derivation of uncertainty of cover fractions derivation of uncertainty of cover fractions - Code carried out on field spectra and - Code carried out on field spectra and sub-sampled to satellite channels sub-sampled to satellite channels  Algorithms – tied SWIR2 PV, NPV, soil spectra ‘tied’ at 2.03μm SWIR2 PV, NPV, soil spectra ‘tied’ at 2.03μm Less dependent on biomass, architecture, biochemistry Less dependent on biomass, architecture, biochemistry - division - division divided spectral reflectance values by reflectance at first wavelength divided spectral reflectance values by reflectance at first wavelength mathematically inappropriate for linear SMA mathematically inappropriate for linear SMA

8. Results Landsat TM convolved data - little difference between shrubland and grassland sites MODIS and most of AVIRIS - spectrally indistinguishable ASTER - some differences AVIRIS – finds negative PV fractions - bare soil overestimated by ~20% - bare soil overestimated by ~20% - NPV fractions good - NPV fractions good Tied SWIR2 – showed consistent accuracy Tied SWIR2 – showed consistent accuracy - corroborated by previous work - corroborated by previous work

12. Future Important to continue this Important to continue this research for ecological research for ecological monitoring monitoring  Further research into the use of instruments such as use of instruments such as AVIRIS (i.e. high SNR AVIRIS (i.e. high SNR in SWIR2) in SWIR2) for use in SMA methods for use in SMA methods