1. Land Color May 2, 1996 North of Denver, CO August 16, 1995 Central Brazil

2. violet - blue - green-yellow-orange - red - near IR

3. By carefully measuring the wavelengths and intensity of visible and near-infrared light reflected by the land surface back up into space a "Vegetation Index" may be formulated to quantify the concentrations of green leaf vegetation around the globe. Normalized Difference Vegetation Index (NDVI) Distinct colors (wavelengths) of visible and near-infrared sunlight reflected by the plants determine the density of green on a patch of land and ocean. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4-0.5 and from to 0.6-0.7 μm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 μm). The more leaves a plant has or the more phytoplankton there is in the column, the more these wavelengths of light are affected, respectively. Measuring Vegetation

4. What colors do we need to observe? OceanPlantsSoils

5. Attenuation in the Visible Wavelengths Grant Petty, 2004 Blue light scattered

7. Daytime Visibility Distant Dark Objects Appear Brighter “Clear” Day Hazy Day

8. Daytime Visibility White Sunlight Top of Atmosphere Color and Intensity Distance to the Dark Object consider scattering by aerosols

9. Daytime Visibility White Sunlight Top of Atmosphere Increased contribution of white light Object appears lighter with distance Longer Distance to the Dark Object

10. Daytime Visibility Distant Dark Objects Appear Brighter “Clear” Day Hazy Day

11. What the satellite sees White Sunlight Top of Atmosphere molecular and aerosol scattering 400→ 500 nm ocean water 450-480 nm plants 500-600 nm near IR transparent

12. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Upwelling Radiance at Satellite due to molecular and aerosol scattering Cloudy Cloudless-Polluted

13. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Cloudy More Polluted Upwelling Radiance at Satellite due to molecular and aerosol scattering

14. Angstrom Exponent

15. 500 nm RV Ron Brown Central Pacific AOT=0.08 Sea of Japan AOT=0.98 AMF Niamey, Niger AOT=2.5-3 Sky Imaging

16. Miller, Bartholomew, Reynolds

17. Atmospheric Correction Methods Develop Theoretical Atmosphere including: Rayleigh Scattering - (Strongest in Blue region) Ozone Aerosols - (Absorption and Scattering Characteristics) Use Data from Infrared (IR) band and assume that all of this signal comes from the atmosphere to get knowledge of aerosols. Solve Radiative Transfer Equation Geometry Location (types of aerosols possible)

18. NDVI NDVI is calculated from the visible and near- infrared light reflected by vegetation. Healthy vegetation (left) absorbs most of the visible light that hits it, and reflects a large portion of the near-infrared light. Unhealthy or sparse vegetation reflects more visible light and less near-infrared light. Real vegetation is highly variable.

19. NDVI NDVI = (NIR — VIS)/(NIR + VIS) Calculations of NDVI for a given pixel always result in a number that ranges from minus one (-1) to plus one (+1) --no green leaves gives a value close to zero. --zero means no vegetation --close to +1 (0.8 - 0.9) indicates the highest possible density of green leaves. NASA Earth Observatory (Illustration by Robert Simmon)

20. NOAA 11 AVHRR 1980200019901985201020051995 NOAA 7 AVHRR NOAA 9 AVHRR NOAA 14 AVHRR SeaWiFS SPOT MODISes NOAA-16 NPP NOAA 9 NOAA-17 Satellite NDVI data sources NOAA-18 C. Tucker

21. In December 1999, NASA launched the Terra spacecraft, the flagship in the agency’s Earth Observing System (EOS) program. Aboard Terra flies a sensor called the Moderate-resolution Imaging Spectroradiometer, or MODIS, that greatly improves scientists’ ability to measure plant growth on a global scale. Briefly, MODIS provides much higher spatial resolution (up to 250-meter resolution), while also matching AVHRR’s almost-daily global cover and exceeding its spectral resolution.MODIS,

22. Average NDVI 1981-2006 NDVI = (ir- red) (ir+red) ~40,000 orbits of satellite data C. Tucker

23. Marked contrasts between the dry and wet seasons (~300 mm/yr @ Senegal) C. Tucker

24. Beltsville USA winter wheat biomass C. Tucker

25.   NDVI vs. total dry biomass Explained 80% of biomass accumulation C. Tucker

26. Species mapping with physiological indices Meg Andrew

27. Spectral Indices: NDVI Creosote Ag NDVI = 0.922 NDVI = 0.356 Meg Andrew, UC Davis

28. Global Vegetation Mapping SeaWiFS Ocean Chlorophyll Land NDVI

29. Ocean Color Locates and enables monitoring of regions of high and low bio-activity. – Food (phytoplankton associated with chlorophyll) – Climate (phytoplankton possible CO 2 sink) Reveals ocean current structure and behavior. – Seasonal influences – River and Estuary influences – Boundary currents Reveals Anthropogenic influences (pollution) Remote sensing reveals large and small scale structures that are very difficult to observe from the surface.

30. 5 SeaWiFS land bands

31. a) The light path of the water-leaving radiance. b) Shows the attenuation of the water-leaving radiance. c) Scattering of the water-leaving radiance out of the sensor's FOV. d) Sun glint (reflection from the water surface). e) Sky glint (scattered light reflecting from the surface). f) Scattering of reflected light out of the sensor's FOV. g) Reflected light is also attenuated towards the sensor. h) Scattered light from the sun which is directed toward the sensor. i) Light which has already been scattered by the atmosphere which is then scattered toward the sensor. j) Water-leaving radiance originating out of the sensor FOV, but scattered toward the sensor. k) Surface reflection out of the sensor FOV which is then scattered toward the sensor. L w Total water-leaving radiance. L r Radiance above the sea surface due to all surface reflection effects within the IFOV. L p Atmospheric path radiance. (Gordan and Wang)

35. Tasmanian Sea

37. A break in the clouds over the Barents Sea on August 1, 2007 revealed a large, dense phytoplankton bloom to the orbiting MODIS aboard the Terra satellite. The bright aquamarine hues suggest that this is likely a coccolithophore bloom. The visible portion of this bloom covers about 150,000 square kilometers (57,000 square miles) or roughly the area of Wisconsin.

39. Supplements

40. Nighttime Visibility Distant Bright Objects are dimmer

41. Attenuation in the Visible Wavelengths Grant Petty, 2004

42. ENVI-1200 Atmospheric Physics Aerosol Hygroscopic Growth Deliquescence – Dry crystal to solution droplet Hygroscopic – Water-attracting Efflorescence – Solution droplet to crystal (requires ‘nucleation’) Hysteresis – Particle size and phase depends on humidity history

43. Atmospheric Correction Methods Develop Theoretical Atmosphere. Include: Rayleigh Scattering - (Strongest in Blue region) Ozone Aerosols - (Absorption and Scattering Characteristics) Use Data from Infrared (IR) band and assume that all of this signal comes from the atmosphere to get knowledge of aerosols. Solve Radiative Transfer Equation Geometry Location (types of aerosols possible) Other considerations: – Sun Glint. Avoid - Use wind speed to estimate surface roughness. – White Caps. Measure - Use wind speed to estimate coverage.

44. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Upwelling Radiance At Satellite Cloudy Cloudless-Polluted Clear H2O Biological

45. History of the NDVI & Vegetation Indices Compton Tucker NASA/UMD/CCSPO

46. Vegetation Indices from Susan Ustin C. Tucker

47. Winter wheat biomass “harvest” C. Tucker

48. This figure shows four typically observed wavelength bands and the water leaving radiance in high (dotted) and low (solid) chlorophyll waters without the atmospheric signal (lower curves) and with the atmospheric signal (upper curves). The satellite observes the water leaving radiance with the signal due to the atmosphere (upper curves). [Gordon and Wang]