1. Remote Sensing Presentations Matthew DrewLidar (Land Surface) Alvan ChaoMODIS Jeff DeppaPolarization Radar Geof Heidelberger Eric NielsenCalipso Joel Berenguer Charles Thomson Courtney TaitCloudSat/GOES or SODAR Stephanie Winter Christina SpecialeNexrad Kevin RomeroCloudSat Lauren Jefferson George Orpanides Alexander HarrisonMODIS/AQUA NDVI Danielle HoldenMODIS AQUA Nicole Peterson Chris SheridanAurora Borealis Tez AmesSea-Surface Temperature Matt NiznikTRMM Benedetto ShiraldiLightning Detection Lalitha Kommajosyula Brian Marmo

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

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

5. What colors do we need to observe? OceanPlantsSoils

6. Attenuation in the Visible Wavelengths (molecular/no aerosol) Grant Petty, 2004 Blue and light blue scattered ozone 765 nm 865 nm

7. Blue and Light Blue

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

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

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

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

12. 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

13. 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.

14. Ocean Color Haze Bloom?

15. RV Ron Brown Central Pacific AOT=0.08 Sea of Japan AOT=0.98 Aerosols over Ocean

16. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Ln (Optical Thickness) Cloudy Cloudless-Polluted Molecular Scattering Aerosols Satellite Channels Aerosol Molecules

17. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Cloudy More Polluted Ln (Optical Thickness) Black-dashed: Aerosol Scattering Blue-dashed: Molecular Scattering Over 90% of the satellite measured radiance is contributed by atmospheric aerosols and molecular scattering

18. Atmospheric Aerosol Correction Procedure BlueGreenRedNear-IR Cloudy More Polluted Ln (Optical Thickness) Black-dashed: Aerosol Scattering Blue-dashed: Molecular Scattering Over 90% of the satellite measured radiance is contributed by atmospheric aerosols and molecular scattering

19. Atmospheric Aerosol Correction Procedure for Ocean Color Near IR Wavelengths

20. Angstrom Exponent

21. Miller, Bartholomew, Reynolds Neg Over-Ocean Aerosol Optical Thickness

22. NDVI NDVI is calculated from the visible and near- infrared light reflected by vegetation. Healthy vegetation – absorbs visible light and reflects a large portion of the near-IR light Unhealthy or sparse vegetation – reflects more visible light and less near-IR light Real vegetation is highly variable

23. 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)

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

25. Terra Satellite December 1999: Terra spacecraft Moderate-resolution Imaging Spectroradiometer, or MODIS, that greatly improves scientists’ ability to measure plant growth on a global scale.MODIS, MODIS: higher spatial resolution (up to 250-meter resolution) than AVHRR

26. MODIS Global NDVI

27. Average NDVI 1981-2006 ~40,000 orbits of satellite data C. Tucker

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

29. Beltsville USA winter wheat biomass C. Tucker

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

31. Species mapping with physiological indices Meg Andrew

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

33. Global Vegetation Mapping SeaWiFS Ocean Chlorophyll Land NDVI

34. 5 SeaWiFS land bands

38. Tasmanian Sea

40. 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.

42. Supplements

43. 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)

44. 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

45. Nighttime Visibility Distant Bright Objects are dimmer

46. Attenuation in the Visible Wavelengths Grant Petty, 2004

47. 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

48. 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.

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

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

51. Vegetation Indices from Susan Ustin C. Tucker

52. Winter wheat biomass “harvest” C. Tucker

53. 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]