differences b etween red and green ndvi, what do they predict and what they don’t predict shambel...

Differences between Red and Green NDVI, What do they predict and what

they don’t predict

Differences between Red and Green NDVI, What do they predict and what

they don’t predict

Shambel Maru

The science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with object, area, or phenomenon under investigation.

The science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with object, area, or phenomenon under investigation.

Remote SensingRemote Sensing

What do sensors measure?What do sensors measure?

Measures the amount of variability of the the light source

It filters the light coming to it along the path way

What is actually being measured in sensor systems is spectral radiance or the radiant energy from the target

LightSource

Plant or SoilSurface

Reflected Light

SensingSystem

Light specturmLight specturm

Major components of visible light spectrum are violet, blue, green, yellow, orange and red

Blue and red are used in photosynthesis

Light absorption at different wavelengths

Green leaves have a reflectance of 20 percent or less in the 500 to 700 nm range (green to red) and about 60 percent in the 700 to 1300 nm range (near infra-red).

1=bacteriochlorophyll, 2=chlorphyll a, 3= chlorophyll b, 4=phycoerythrobilin, 5= beta carotene)

VISIBLE Color AbsorbedVISIBLE Color Absorbed

VISIBLE Color TransmittedVISIBLE Color TransmittedVISIBLE Color Transmitted

Violet Blue Green Yellow Orange RedVioletViolet BlueBlue GreenGreen YellowYellow Orange Orange RedRed

Short wavelengthShort wavelengthHigh frequencyHigh frequencyHigh energyHigh energy

Long wavelengthLong wavelengthLow frequencyLow frequencyLow energyLow energy

0.01 10 380 450 495 570 590 620 750 1x106 1x1011

wavelength, nm0.010.01 1010 380380 450450 495495 570570 590590 620620 750750 1x101x1066 1x101x101111

wavelength, nmwavelength, nm

Gam

ma

Ray

sG

amm

a R

ays

Gam

ma

Ray

s

X-R

ays

XX-- R

ays

Ray

s

Ultr

avio

let

Ultr

avio

let

Ultr

avio

let

Infr

ared

Infr

ared

Infr

ared

Mic

row

aves

and

sho

rt r

adio

Mic

row

aves

and

sho

rt r

adio

Mic

row

aves

and

sho

rt r

adio

Rad

io, F

M, T

VR

adio

, FM

, TV

Rad

io, F

M, T

V

Electronic Vibrational Rotationaltransitions transitions transitionsElectronicElectronic VibrationalVibrational RotationalRotationaltransitionstransitions transitionstransitions transitionstransitions

YellowYellow--greengreen YellowYellow VioletViolet BlueBlue GreenGreen--blueblue BlueBlue--greengreen

Characteristics of visible and non-visible portions of the spectra

NDVI, what is it?NDVI, what is it? It is normalized difference vegetation index. Used to measure green biomass (Tucker, 1979) Degree of greenness = chlorophyll concentration Actually measure photo synthetically active radiation absorbed by the canopy (Sellers, 1985) NDVI values vary with absorption of red light by

plant chlorophyll and the reflection of infrared radiation by water-filled leaf cells. It is correlated with Intercepted Photo-synthetically Active Radiation (IPAR).

NDVI, what is it?NDVI, what is it? It is a function of Incident and reflected

light

RNDVI= NIR – Red ,

NIR + Red

GNDVI= NIR – Green ,

NIR + Green

NIR 750-1300 nm Red 600-700 nm Green 550 nm

Where 0< NDVI< 1

Differences between the Green and Red Differences between the Green and Red NDVINDVI

Red band is used to measure green biomass and estimate changes in vegetation state, but it is only sensitive to low chlorophyll-a concentration

(3-5 g/cm2) (Gitelson et al., 1997) Good at early stage

The Green band (520-630nm) is sensitive to a wide range of chlorophyll-a concentration (0.3 – 45 g/cm2) (Gitelson et al., 1997)

May work for late crop stages prediction

What do NDVI predict?What do NDVI predict?

Grain yield from reflectance readings of

NIR and Red (Tucker et al., 1981) Important in variable rate fertilizer

recommendation based on predicted yield Relationship decrease as wheat became ripened. Two late season readings (Feekes 10.5, flowering to

grain filling) may give more stable prediction as compared to that of a single reading (Pinter et al., 1981)

Grain yield from reflectance readings of

NIR and Red (Tucker et al., 1981) Important in variable rate fertilizer

recommendation based on predicted yield Relationship decrease as wheat became ripened. Two late season readings (Feekes 10.5, flowering to

grain filling) may give more stable prediction as compared to that of a single reading (Pinter et al., 1981)

Wheat biomass (NIR) and Nitrogen uptake reliably predicted at Feekes 4 & 5 (Stone et at., 1997, Lukina et al., 2000)

At the same stage percent ground cover and NDVI are co-related with vegetative biomass of wheat.

Wheat biomass (NIR) and Nitrogen uptake reliably predicted at Feekes 4 & 5 (Stone et at., 1997, Lukina et al., 2000)

At the same stage percent ground cover and NDVI are co-related with vegetative biomass of wheat.

What do NDVI predict?What do NDVI predict?

EY

Relationship between Estimated Yield (EY) computed from NDVI at Feekes growth stages 4 and 5, divided by growing degree days and observed grain yield, at six locations, 1998 and 1999.

EY = NDVI1 + NDVI2

GDD

0

1

2

3

4

5

6

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007

INSEY

Gra

in Y

ield

, Mg

ha

-1N*P Perkins, 1998

S*N Perkins, 1998

S*N Tipton, 1998

N*P Perkins, 1999

Experiment 222, 1999


Efaw AA, 1999



N*P Perkins, 2000



Efaw AA, 2000



Hennessey, AA, 2000

y = 4E+07x3 - 296260x2 + 970.66x

R2 = 0.64

N o rm alized D iffe re n ce V eg eta tio n In d ex (N D V I)

= N n IR ref – red ref / N n IR ref + red ref

N o rm alized D iffe re n ce V eg eta tio n In d ex (N D V I)

= N n IR ref – red ref / N n IR ref + red ref

(up – dow n)(up – dow n)

exce llen t p red ic to r o f p lan t N up takeexce llen t p red ic to r o f p lan t N up take

0

20

40

60

80

100

120

140

160

180

200

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

NDVI, Feekes 4-6

Ear

ly-s

easo

n pl

ant N

upt

ake,

kg

ha-1

N*P Perkins, 1998

S*N Perkins, 1998

S*N Tipton, 1998

transect Stillw ater, 1999

transect Perkins, 1999

transect Efaw , 2000, Jan

transect Perkins, 2000 Jan

transect Efaw , 2000 Mar

transect Perkins, 2000 Mar

y = 1019.5x3 - 1507.5x2 + 811.5x - 130.32R2 = 0.78

The image above from July 1989 depicting the continent of Africa from the NOAA AVHRR weather satellite illustrates the NDVI concept. Areas in yellow such as the Sahara desert have very low levels of vegetation (low NDVI). Areas in red the such as the tropics along the equator are highly vegetated (high NDVI). The second image was acquired 6 months earlier and illustrate the effect of less rain on the NDVI's (a lowering effect) – notice the shrinking area of reddish areas along the equator.

The Sahel Zone

The image shows senescence in northern hardwoods in some areas, and higher NDVI in conifer dominated areas in the north, and aspen-birch, and mixed conifer and deciduous forests in other parts of the Lake Superior Basin.

Limitations of NDVILimitations of NDVI

It can only measure the surface vegetation biomass at late growth stages

Reading is 2 dimensional not 3D

It can not predict the amount of nitrogen concentration in the plant

Questions?

differences b etween red and green ndvi, what do they predict and what they don’t predict shambel...

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