Remote Sensing and Ecophysiology

1. Remote Sensing and Ecophysiology Remote Quantification of Photosynthesis

2. Measurement and Modeling:Portions of Literature Review • Measurement • Remote sensing • Direct Measurements • Leaf level estimations of Chl, N, Pn, etc. • Ecosystem flux measurements • Modeling • CASA • CENTURY • PnET… etc.

3. Egg Chicken Measurement and Modeling (cont.) Data Model Induction Deduction

4. Francis Bacon • Now although it be true, and I know it well, that there is an intercourse between causes and effects, so as both these knowledges, speculative and operative, have a great connection between themselves; yet because all true and fruitful natural philosophy hath a double scale or ladder, ascendent and descendent, ascending from experiments to the invention of causes, and descending from causes to the invention of new experiments; therefore I judge it most requisite that these two parts be severally considered and handled. --From Of the Proficience and Advancement of Learning

5. The Etymology of “Scale” Scale > Scala, ae (from scandere) • Stairway, allegorically stairway to heaven Transformation of measurements from the selective to the synoptic

6. Scale, cont. • Rastetter et al (2003) • Using mechanistic models to scale measurements through space and time

7. Scaling Ecological Estimates Ollinger, Aber & Fedderer (1998)

8. What is Needed for Modeling(e.g. what RS inputs) • Nitrogen-based Modeling • Photon-Use-Efficiency • Et cetera

9. What can we detect?Stress • Terrestrial plants are regularly stressed • Can detect responses to stress-- • Conversion of carotenoids for heat dissipation • Dissipation of extra light through fluorescence

10. Estimate Foliar N with Hyperspectral Techniques Gong et al (2002)

11. Importance of Photosynthetic Pigments (and more!) • Chlorophyll estimation (also useful, as is often correlated with total foliar N) • Carotenoid Estimation • Fluorescence-based photosynthesis estimation • related to direct measurement of canopy productivity • Useful for PUE models (Freedman et al (2002)

12. Estimation of Chl and Carotenoids Blackburn (1998)

13. Estimation of Chl and Carotenoids Blackburn (1998)

14. Estimation of Chl and Carotenoids Blackburn (1998)

15. Licor 6400 Fluorometer Addition

16. Problems with estimating Fluorescence Outside the Chamber • Multiple Components to apparent reflectance signal: • Reflectance/ Fluorescence • Loss via transmittance • Loss via absorbance

17. Incoming Solar Radiation Leaf Reflectance Component Chlorophyll Fluorescence Component Problems with estimating Fluorescence Outside the Chamber Leaf

18. Problems with estimating Fluorescence Outside the Chamber • Additional Problems • Leaves heterogeneous • Canopies Complicated

19. 3D Model of Canopy Fluorescence Camenen et al (1996)

20. Modeling of Leaf Reflectance and Fluorescence • Zarco-Tejada et al (2000) • Dawson et al (1998) • PROSPECT (combined with SAIL), Haboudane et al (2003)

21. Modeling Fluorescence Zarco-Tejada et al (2000)

22. Leaf Level Radiative Transfer:LIBERTY Dawson et al (1998)

23. SAIL and PROSPECT Parameters Haboudane et al (2002)

24. Impact of Leaf Absorbance on Measurements Peterson et al (2001)

25. Net Pn vs. Red/ Far Red Ratios Freedman et al (2002)

26. Comparison of Fluorescence Ratios, Photosynthesis and Stomatal Conductance Flexas et al (2002)

27. Double Peak Zarco-Tejada et al (2001)

28. Final Comments • Fluorescence viable technique for canopy level estimation of Pn • Useful for estimation of Pn in realtime (model validation and tuning) • Useful toward PUE modeling • Nutrient Concentration Estimations possible (useful for PnET and other N driven models

29. Further Directions • Linkages between RS and models need to be explicitly sought for scaling between selective and synoptic estimations (deeper lit. on models) • “Direct” measurement components-- eddy-covariance biophysics and relevance to modeling process

30. Heterogeneity of Pn within Leaves Lichtenthaler & Babani (2000)