Radiometric and biophysical measures of global vegetation from multi-dimensional MODIS data

1. Radiometric and biophysical measures of global vegetation from multi-dimensional MODIS data Ramakrishna Nemani NTSG

2. Acknowledgements: University of Arizona Boston University NTSG Alfredo Huete Ranga Myneni Joe Glassy Kamel DidanY. KnyazikhhinPetr Votava Tomoaki MiuraY. Zhgang Hiroki YoshiokaY. Tian Laerte Ferreira Xiang Gao Karim Batchily

3. Radiometric Measures Vegetation Indices SR (Simple Ratio), MSR (Modified SR) SAVI (Soil Adjusted VI), MSAVI, ARVI, GEMI NDVI (Normalized Difference Vegetation Index) EVI (Enhanced Vegetation Index) Biophysical Measures Leaf Area Index (Area of leaves per unit ground area, m2/m2) FPAR (Fraction of incident PAR that is absorbed)

4. VEGETATION INDICES • Vegetation Indices are ‘robust’ spectral transformations of two or more bands designed to enhance the ‘vegetation signal’ and allow for reliable spatial and temporal inter-comparisons of terrestrial photosynthetic activity and canopy structural variations.

5. APPLICATIONS • Indicators of seasonal and inter-annual variations in vegetation (phenology) • Change detection studies (human/ climate) • Tool for monitoring and mapping vegetation • Serve as intermediaries is the assessment of various biophysical parameters: leaf area index (LAI), % green cover, biomass, FPAR, land cover classification

6. Spatio-temporal vegetation dynamics

7. 1999 Onset of Greenness

9. Departure from Average Maps from the Wildland Fire Assessment System Departure from Average maps relate current year vegetative greenness to average vegetative greenness for the same time of year.

10. Leaf Area Index (LAI) Fraction of intercepted photosynthetically active radiation (FPAR)

11. Global Leaf Area Index derived from Pathfinder NDVI and NDVI-LAI relationships

12. Global FPAR derived from Pathfinder NDVI and NDVI-FPAR relationships

13. Relating transpiration and photosynthesis to NDVI, 1988

14. Theoretical basis for spectral vegetation indices: Spectral reflectance of leaves

15. SVI Formulations Simple Ratio = NIR/Red Normalized Difference = (NIR-Red)/(NIR+Red) Vegetation Index Advantages: simple Disadvantages: residual influences of atmosphere, background and viewing geometry

16. Atmospheric Influences on Spectral Response Functions Total Radiance Path Radiance Sunlight Reflected Energy Water vapor absorption Scattering by aerosols Skylight Atmosphere influences are not the same for Red and NIR

17. Background Influences Band 6 : 10.4 - 12.5 Reflectance 5 7 4 1 2 3 4 TM Vegetation Dry Soil Wet Soil 0.5 0 1.0 1.5 2.0 2.5 Wavelength in Micrometers

18. Angular dependence

19. VI Equations • Enhanced Vegetation Index: -where r is atmospherically-corrected, surface reflectances, L is the canopy background adjustment, G is a gain factor, and C1 , C2 are coefficients for atmospheric resistance.

20. MODIS Standard VegetationIndex Products Products • The MODIS Products include 2 Vegetation Indices (NDVI, EVI) and QA produced at 16-day and monthly intervals at 250m/ 500m, 1km, and 25km resolutions • The narrower ‘red’ MODIS band provides increased chlorophyll sensitivity (band 1), • The narrower ‘NIR’ MODIS band avoids water vapor absorption (band 2) • Use of the blue channel in the EVI provides aerosol resistance

21. RED NIR Dotted lines indicate AVHRR bands 1 2

22. Normalizing the VIs to nadir values

23. Compositing Algorithm • Provide cloud-free VI product over set temporal intervals, • Reduce atmosphere variability & contamination • Minimize BRDF effects due to view and sun angle geometry variations • Depict and reconstruct phenological variations • Accurately discriminate inter-annual variations in vegetation. Physical and semi-empirical BRDF models Maximum VI (MVC) or constrained VI (CMVC)

25. MODIS-VI Compositing Scheme Flow Diagram

26. Global NDVI at 500 mDOY 113-128

27. Tapajós 500m NDVI subset DOY 113-128

28. MOD13A1 QA 500m

29. 1km EVI Time Series 1km NDVI Time Series South America

30. NDVI EVI 1 km VI’s Tapajós 113 - 128 ‘Forest’ EVI NDVI

32. MODIS & AVHRRNDVI Comparisons

33. RED NIR Dotted lines indicate AVHRR bands 1 2 AVHRR & MODIS Red and NIR bands

34. White: Needle forest Blue : Broadleaf forest Green: Grass Purple: Crop Yellow: Shrub Red : Water

35. White: Needle forest Blue : Broadleaf forest Green: Grass Purple: Crop Yellow: Shrub Red : Water

36. SUMMARY • Both indices were robust and performed well in global vegetation monitoring and analysis • The improved spectral and spatial resolutions of MODIS offer the potential for improved change detection / land use and conversion studies,

37. BIOPHYSICAL MEASURES Leaf Area Index (m2/m2): FPAR (Fraction of absorbed PAR): Incident Radiation Leaf Leaf Leaf Leaf Leaf Leaf Ground PAR absorption (radiometric) Leaf Area (structural)

38. Applications of FPAR and LAI • FPAR and LAI are useful variables which help describe: • canopy structure • radiation absorption • vegetative productivity • seasonal boundaries, phenological state • global carbon cycling

39. Remote Sensing Inputs Model Outputs Land Cover Weekly and Annual Productivity FPAR NPP = GPP - Respiration LAI Daily Weather (Tmin, Tmax, Rnet) MODIS Terrestrial Productivity

41. Functional relations Leaf Area Index (LAI) Fraction of intercepted photosynthetically active radiation (FPAR)

42. Need for a more robust approach 0.70 NDVI

44. FPAR, LAIAlgorithmic Approach • Two-tier algorithmic approach: • LUT based approach using spectral as well as angular observations • simple VI based backup

45. Controlling factors: Leaf optical properties (refl,tran,abs) Canopy structure Background reflectance Sun-sensor geometry Leaf area

46. Controlling factors: Leaf optical properties (refl,tran,abs) Canopy structure Background reflectance Sun-sensor geometry Leaf area White: Needle forest Blue : Broadleaf forest Green: Grass Purple: Crop Yellow: Shrub Red : Water

49. 0.70 NDVI White: Needle forest Blue : Broadleaf forest Green: Grass Purple: Crop Yellow: Shrub Red : Water

50. Controlling factors: Leaf optical properties (refl,tran,abs) Canopy structure Background reflectance Sun-sensor geometry Leaf area