# Presentation: 185914

## BIOPHYS:  A Physically-based Algorithm for Inferring Continuous 

**Fields of Vegetative Biophysical and Structural Parameters**

- Forrest Hall1, Fred Huemmrich1, Derek Peddle2,1, David Landis3
- 1 Joint Center for Earth Systems Technology (JCET)
- University of Maryland Baltimore County
- Code 923
- NASA's Goddard Space Flight Center
- Greenbelt, MD 20771
- Forrest.G.Hall.1@gsfc.nasa.gov
- 2 Department of Geography
- The University of Lethbridge
- Lethbridge, Alberta, Canada
- 3 SSAI
- Lanham, MD

**MULTIPLE FORWARD MODE**
- BIOPHYS uses MFM to achieve objectives of inversion modeling, BUT _without_ explicit model inversion.
- Model is run multiple times in forward mode:
-      Model range and increment step – _Exact values are not required_
- 		e.g.  crown width: 0.5 - 4m (step: 0.5m)
- 	         height: 5 - 20m  (step: 1m)
- 	         crown closure: 0 - 100% (step: 5%)
-      Each run produces an output pixel reflectance value: T()
- Results stored in MFM Look-up Table (MFM-LUT)
-      All structural inputs retained in MFM-LUT
- Match MFM-LUT T() values with actual satellite T() values
**FLOW DIAGRAM FOR BIOPHYS DATA PROCESSING**

**ABSTRACT**
- BIOPHYS is a physically-based algorithm presently being developed that uses radiative transfer modeling for inferring continuous fields of vegetative biophysical and structural parameters from MODIS data for input to surface/atmosphere carbon water and energy exchange models. Outputs consist of parameters such as leaf and canopy background optical properties, leaf area, branch area, crown shape, canopy cover, and vertical structure (canopy roughness), with appropriate error estimates. The algorithm requires no training data or classification, is well suited to multiple scenes and sensors with variable view and solar geometries, and produces a variety of biophysical/structural parameters over large areas.  It has been validated and shown superior to other approaches for a variety of ecosystems, forestry parameters, sensors, and canopy optical models and is now being adapted for MODIS and NACP applications.
**APPROACH**
- Canopy reflectance models provide the physical link between canopy characteristics and observed spectral reflectance.  BIOPHYS uses an approach called multiple forward mode (MFM) modeling where canopy reflectance models calculate sets of reflectances using ranges of input structural values (billions of model runs are possible).  Both the reflectance output and the biophysical-structural inputs to the canopy reflectance model are saved in a look-up table (LUT).  Model inversion is simulated by searching the LUT for possible solutions that match the MODIS reflectances. The biophysical-structural input parameters from the model associated with each reflectance match provides the basis for inferring the continuous fields outputs.
**CANOPY REFLECTANCE MODELS**
- Models that account for multiple scattering as well as shadowing by crowns are being used in BIOPHYS.  Examples are GORT and GeoSail.
**Forest stands modeled as:**
- 	• Geometric objects (tree crowns described by shape, height, width)
- 	• Background surface (forest understory/ground)
- 	• Shadows
**Site description in model:**
- 	• Stand density
- 	• Pixel size
- 	• Terrain (slope, aspect)
- 	• Sensor view angle (view zenith, azimuth angle to sun)
- 	• Solar Zenith Angle
**Spectral properties:**
- 	• Component endmembers (by species, per band ):
- 		sunlit canopy:  c()
- 		sunlit background: b()
- 		shadow: s()
- 	• Multiple scattering within canopy
- 		affects reflectance of canopy (c()) and shadow (s()) endmembers

- A graphic interpretation of a MFM-LUT showing both biophysical values and errors. Average (left image) and coefficient of variation (right image) of LAI for July for 45o N latitude, x-axis is visible reflectance and y-axis is near IR reflectance, both from 0 to 0.30. The color in each grid represents the average or coefficient of variation of LAI values of all the model runs whose output reflectances fell within each 0.005 by 0.005 reflectance grid. 9.5 x 109 model runs were used.
- _Using Multiple View/Sun Angles_
- Red and near IR reflectances for spruce forest stands were calculated using GeoSail for multiple solar zenith angles (SZA).  Canopy needle and branch LAI, coverage, and crown shape were varied resulting in 6930 runs for each SZA.  A random model run was chosen as a target.  For each SZA the model runs with reflectances within ±0.5% reflectance of the target were examined, also the runs that were selected for all SZA were determined.

**EXAMPLES**
- _LAI Look-up Tables_

- Left, a graphic showing how multiple view/solar angles can be used in MFM.  Top table on right is the number of model runs that were within ±0.5% reflectance of the target reflectance in both red and near IR bands.  The lower table gives the average and standard deviation of the 13 model runs that were near the target reflectance for all SZA compared with the target values, showing good agreement.
**ADVANTAGES OF THIS APPROACH**
- • It provides a physical basis to biophysical parameter retrieval
- • Requires no training data
- • Provides an estimate of error
- • Takes advantage of different view and solar geometries
- • Accounts for differences in surface slope and aspect
- • Does not depend on image classification as a first step
- • Can be used to classify images
- • Can work with multiple sensors