1. BIOPHYS A PHYSICALLY-BASED CONTINUOUS FIELDS ALGORITHM Ecosystem, Climate and Carbon Models FORREST G. HALL, FRED HUEMMRICH Joint Center for Earth Systems Technology (JCET) NASA's Goddard Space Flight Center Greenbelt, MD 20771 Derek Peddle Lethbridge University Alberta, Canada David Landis SSAI Lanham, MD

2. 2005 Activities 2005 our first full year of activity Initial test and development using helicopter MMR (landsat 5 radiometer) –SNF 1983 data sets, 3 solar zenith angles Development of Landsat BIOPHYS Processing of selected Landsat scenes Biophysical structure and succession Preliminary validation Initiation of MODIS development and testing

3. Satellites (spectral, angular, temporal)  si ( Ωi) CANOPY REFLECTANCE MODEL (LUTS) {  si } =  ( LOP,BOP,Cg,LAI C,LAI b,CC) Satellite Measurement ( L2 ) {  si ± ∆  si } i i bands, angles, dates Table Lookup {LOP,BOP,Cg,LAI C,LAI b,CC } k  {  si ± ∆  si } i Compute Parameter Statistics Ecosystem Parameters , Fpar, g c, Z o, P v,NP v = F( ) Biophys Framework Numerical, Non-analytic BIOPHYS CONCEPT

4. Band 1 Band 2 Band 3 Canopy Reflectance Models Zap! Spectral Space Biooptical Parameter 1 Biopoptical Parameter 2 Biooptical Parameter3 Biophysical Parameter Space BIOPHYS uses CRMs to map spectral space Into biooptical parameter space. 1  si (Ωi, Bi) =  (LOP, BOP,Cg, h/w, LAI C, LAI b, CC)  si (Ωi, Bi) = Spectral Space Ωi = view and illumination geometry Biooptical parameters Bi LOP&BOP= leaf&background optical properties Cg = Canopy geometry LAI C = Crown leaf area index LAI b = Branch leaf area index CC = fractional crown cover

5. Biophysical Parameter 1 Biophysical Parameter 2 Biophysical Parameter3 Carbon/Water/Energy Transport Relations Map Biooptical Parameters Into model Parameters, for example Model Parameters   canopy albedo Fpar = Fraction of absorbed photosynthetically active radiation g c = bulk canopy conductance P v,NP v Fraction of photosynthetically and non-photosynthetically active vegetation LAI = Canopy leaf area index

6. Original GeoSail Reflectance LUT BIOPHYS Landsat Processing Program: Creating the “Averaged” Table SELECT avg(green_lai),stddev(green_lai), avg(branch_lai),stddev(branch_lai), avg(fract_canopy_cover),stddev(fract_canopy_cover), avg(crown_h_w_ratio),stddev(crown_h_w_ratio) FROM boreal_gs_test2 WHERE (landsat_b2_refl_sza35 BETWEEN 1 AND 100) AND (landsat_b3_refl_sza35 BETWEEN 201 AND 300) AND (landsat_b4_refl_sza35 BETWEEN 1001 AND 1100); SELECT avg(green_lai),stddev(green_lai), avg(branch_lai),stddev(branch_lai), avg(fract_canopy_cover),stddev(fract_canopy_cover), avg(crown_h_w_ratio),stddev(crown_h_w_ratio) FROM boreal_gs_test2 WHERE (landsat_b2_refl_sza35 BETWEEN 1 AND 100) AND (landsat_b3_refl_sza35 BETWEEN 201 AND 300) AND (landsat_b4_refl_sza35 BETWEEN 1001 AND 1100); Sample SQL Query New “Averaged” Reflectance LUT ASCII File Create the Original LUT The original data was created using the GeoSail model. The biophysical parameters (Green LAI, Branch LAI, Fractional Canopy Cover, & Crown H/W Ratio) were varied sequentially as input to the model. A reflectance for various SZA’s (30  to 70 , in 5  steps) and Landsat Bands (1 to 4) was then output from the model. Create the “Averaged” LUT The original MySQL table was then processed using a C program that runs a series of SQL commands and saves the results to a data file. These commands used SQL to create averages and standard deviations for the biophysical parameters where the reflectance for bands 2, 3, and 4 were all within preset binned values (bin size was 100, which is a 1% tolerance). It also creates “%counts” for the 4 cover types (aspen, spruce, ojp, yjp).This processing took about 48 hours, but only had to be done once. Keep the “Averaged” LUT As an ASCII File The resulting ASCII data file (with 15,000 records) was then used by the image-processing program (next slide). Load the Original LUT into MySQL The GeoSail data file (with 2.5 million records) was loaded into a MySQL table. Then all values were turned into 2-byte integers to match the Landsat file format: reflectances x 10,000 and 4 biophysical parameters x 100.

7. Initial Test Landsat ( MMR), vis, nir  0.01) 16 Black Spruce sites 3 solar angles (3 dates) 1983 Superior National Forest, Minnesota

8. SNF Landsat Analyses: Results Landsat data acquired at multiple solar view angles improved retrieval precision. Mean of non-unique solutions appear to converge on actual mean

9. BIOPHYS Landsat Processing Program: Using the “Averaged” LUT, Logic-flow Diagram New “Averaged” Reflectance LUT ASCII file repeat for each point in the 4 lines repeat for each line in the 3 bands Start End Output Files Read in the file name and the SZA. Extract all records from the “averaged” ASCII LUT for that SZA (about 1600 records) and store them in a 4D array “the_table[r2][r3][r4][c]” within the program (the 3 major indexes are the 3 refl/100). This is the only time the program accesses the LUT file. Open the Landsat RAW files (bands 2, 3, & 4) and the QA file (if present). Open 13 output files to write the results to: AV and STDEV for each of the 4 biophysical parameters, NDVI, and 4 %cover files (aspen, spruce, ojp, yjp). Read line Y of QA & band 2,3,4. If no QA problem, use point X of line Y of each band (binned into values of 100, then divided by 100) as an index number into the stored array “the_table[r2][r3][r4]” and return the 1 unique array record that fits that combination of reflectances in those bands. Store the 12 values from the array (AV and STDEV for the 4 biophysical parameters, 4 %counts) into the same point in the 12 output lines. Computer NDVI. When all the values for this line Y are processed, write each of the 13 output lines to its open file. Close all 13 output files, and the 3 input files. This processing takes about 60 seconds total. Landsat Image Files in RAW binary format crown_green_lai_av RAW binary file crown_green_lai_av RAW binary file crown_green_lai_sd RAW binary file crown_green_lai_sd RAW binary file crown_branch_lai_av RAW binary file crown_branch_lai_av RAW binary file crown_branch_lai_sd RAW binary file crown_branch_lai_sd RAW binary file fract_canopy_cover_av RAW binary file fract_canopy_cover_av RAW binary file fract_canopy_cover_sd RAW binary file fract_canopy_cover_sd RAW binary file crown_h_w_ratio_av RAW binary file crown_h_w_ratio_av RAW binary file crown_h_w_ratio_sd RAW binary file crown_h_w_ratio_sd RAW binary file %cover Aspen RAW binary file %cover Aspen RAW binary file %cover Spruce RAW binary file %cover Spruce RAW binary file %cover OJP RAW binary file %cover OJP RAW binary file %cover YJP RAW binary file %cover YJP RAW binary file Computed NDVI RAW binary file Computed NDVI RAW binary file Check the QA bits for point X in line Y. If there is a problem, fill the LUT return array values with “-99”.

10. BIOPHYS Landsat Output: Canopy Green LAI Average BOREAS Region (p37 r22) Aug 12, 2001, SZA 45°

11. BIOPHYS Landsat Output: Canopy Green LAI St-Dev BOREAS Region (p37 r22) Aug 12, 2001, SZA 45°

12. BIOPHYS Landsat Output: Fractional Canopy Cover Average (%) BOREAS Region (p37 r22) Aug 12, 2001, SZA 45°

13. BIOPHYS Landsat Output: Canopy Branch LAI Average BOREAS Region (p37 r22) Aug 12, 2001, SZA 45°

14. BIOPHYS Landsat Output: Aspen Cover (%) Note: this is actually the percent of retrieved solutions from the LUT that corresponded to this cover type. BOREAS Region (p37 r22) Aug 12, 2001, SZA 45°

15. ~1990 Landsat ~2000 Landsat 1990-2000: 1.03 Mha burnt, logged (5.8% of area) 0.89 Mha in early regrowth (4.9% of area) LEDAPS Activity Landsat 5 Uncorrected Landsat 5 Corrected Landsat 7 Corrected

16. BIOPHYS AND A BOREAL CHRONOSEQUENCE

17. INITIAL MODIS INVESTIGATIONS MODIS pixels extracted from acquisitions for 16 day period during August 2001 over BOREAS Black Spruce Site Atmospherically corrected using MODIS aerosol product and 6s. RESULTS MODIS provided very limited sample of BRDF Retrieved parameter values sensitive to view & illumination geometry Number of non-unique solutions decreased rapidly with number of angles used in retrievals

18. What’s Next Complete exploratory work Finalize RT Model (GOMS, GORT …) selection. Build the LUTs Run MODIS BIOPHYS Algorithm over selected regions Evaluate MODIS Products and Iterate –PRODUCE PROVISIONAL DATA SETS WITH BIOPHYS OVER SELECTED STUDY REGIONS. –PLACE PROVISIONAL DATA SETS ONLINE; INITIATE USER EVALUATION.