Land and Ocean Color Measuring Vegetation NDVI EVI and Ocean Color Though we often take the plants and trees around us for granted almost every aspect of our lives depends upon them 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 to 0 7 m 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 m The more leaves a plant has or the more phytoplankton there is in the column the more these wavelengths of light are affected respectively Attenuation in the Visible Wavelengths Grant Petty 2004 Attenuation in the Visible Wavelengths Grant Petty 2004 Daytime Visibility Distant Dark Objects Appear Brighter Clear Day Hazy Day Nighttime Visibility Distant Bright Objects are dimmer Revisiting Daytime Visibility Henceforth we shall only consider scattering by clouds and aerosols White Sunlight Top of Atmosphere Horizon Color and Intensity Horizon always Whitened relative to Sky above Distance to the Dark Object Revisiting Daytime Visibility White Sunlight Top of Atmosphere Increased contribution of white light Object appears lighter with distance Longer Distance to the Dark Object Daytime Visibility Revisitied Distant Dark Objects Appear Brighter Clear Day Hazy Day 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 ENVI 1200 Atmospheric Physics Sky Imaging 500 nm AMF RV Ron Brown Central Pacific Sea of Japan Niamey Niger AOT 0 08 AOT 0 98 AOT 2 5 3 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 NDVI NDVI is calculated from the visible and nearinfrared 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 right reflects more visible light and less near infrared light Real vegetation is highly variable Advanced Very High Resolution Radiometer AVHRR NOAA has two polar orbiting meteorological satellites in orbit at all times with one satellite crossing the equator in the early morning and early evening and the other crossing the equator in the afternoon and late evening Morning satellite data are most commonly used for land studies while data from both satellites are used for atmosphere and ocean studies Satellite NDVI data sources NOAA 7 AVHRR NOAA 9 AVHRR NOAA 16 NOAA 14 MODISes AVHRR NOAA 11 AVHRR SPOT NOAA 9 1980 C Tucker 1985 1990 NPP 1995 NOAA 18 SeaWiFS NOAA 17 2000 2005 2010 EVI Enhanced Vegetation Index 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 History of the NDVI Vegetation Indices Compton Tucker NASA UMD CCSPO Vegetation Indices from Susan Ustin Index Simple Ratio Normalized Difference Vegetation Index Formula Details RNIR RR Green vegetation cover Various wavelengths depending on sensor e g NIR 845nm R 665nm Pearson 1972 RNIR RR RNIR RR Green vegetation cover Various wavelengths depending on sensor e g NIR 845nm R 665nm Tucker 1979 Enhanced Vegetation Index Perpendicular Vegetation Index Soil Adjusted Vegetation Index Modified Soil Adjusted Vegetation Index Transformed Soil Adjusted Vegetation Index Soil and Atmospherically Resistant Vegetation Index C Tucker Citation C1 6 C2 7 L 1 G 2 5 Huete 1997 Rs Rv 2 NIRs NIRv 2 NIR R 1 L NIR R L a NIR aR b R a NIR b 0 08 1 a 2 NIR R 2 5 1 NIR 6R 7 B Perpendicular distance from the pixels to the soil line L soil adjusted factor L 1 2a x NIR aR x NDVI Self adjusting L f on to optimize for soil effects Higher dynamic range Richardson and Wi egand 1977 Huete 1988 Qi et al 1994 a slope of soil line b intercept of soil line Baret and Guyot 1991 More independent of surface brightness Huete et al 1997 Beltsville USA winter wheat biomass C Tucker Winter wheat biomass harvest C Tucker NDVI vs total dry biomass Explained 80 of biomass accumulation C Tucker Marked contrasts between the dry and wet seasons C Tucker 300 mm yr Senegal Average NDVI 1981 2006 40 000 orbits of satellite data NDVI ir red ir red C Tucker Species mapping with physiological indices Meg Andrew Spectral Indices NDVI NDVI RNIR Rred RNIR Rred Creosote Ag NDVI 0 922 NDVI 0 356 More info cstars ucdavis edu classes ECL290 docs Andrews ppt Meg Andrew Global Vegetation Mapping SeaWiFS Ocean Chlorophyll Land NDVI 5 SeaWiFS land bands Ocean Color Locates and enables monitoring of regions of high and low bio activity Food phytoplankton associated with chlorophyll Climate phytoplankton possible CO2 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 Tasmanian Sea 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 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