The Normalized Differential Vegetation Index (NDVI) is a standardized vegetation index which allows us to generate an image showing the relative biomass. The chlorophyll absorption in Red band and relatively high reflectance of vegetation in Near Infrared band (NIR) are using for calculating NDVI. ( From ESRI)

“An NDVI is often used worldwide to monitor drought, monitor and predict agricultural production, assist in predicting hazardous fire zones, and map desert encroachment. The NDVI is preferred for global vegetation monitoring because it helps to compensate for changing illumination conditions, surface slope, aspect, and other extraneous factors” (Lillesand 2004).

Monitoring the intensity and the density of the green vegetation growth can be done using the reflection from the red band and the infrared band. Green vegetation reflects more energy in the near- infrared band than in the visible range. It observe red band more for the photosynthesis process. Leaves reflects less in the near-infrared region when they are stressed, diseased or dead. Features like Clouds, water and snow show better reflection in the visible range then the near-infrared range, while the difference is almost zero for rock and bare soil.

Output of the NDVI method creates a single-band dataset that only shows greenery. Values close to zero represent rock and bare soil and negative values represent water, snow and clouds. Taking ratio or difference of two bands makes the vegetation growth signal differentiated from the the background signal. NDVI method was developed by the NASA scientist popularly known as Normalized Difference Vegetation Index (NDVI). By taking a ratio of two bands drop the values between -1 to +1. Table below shows the red and infrared bands reflectance values of features and their NDVI values. Water has an NDVI value less than 0, bare soils between 0 and 0.1, and vegetation over 0.1. Increase in the positive NDVI value means greener the vegetation.

NDVI image

RED= DN values from RED band

NIR= DN values from Near Infrared band

COVER TYPE

RED

    NIR

NDVI

Dense vegetation

0.1

0.5

0.7

Dry Bare soil

0.269

0.283

0.025

Clouds

0.227

0.228

0.002

Snow and ice

0.375

0.342

-0.046

Water

0.022

0.013

-0.257

Fig: Table 1

Table shows typical reflectance values in the red and infrared channels, and the NDVI for typical cover types. Water typically has an NDVI value less than 0, bare soils between 0 and 0.1 and vegetation over 0.1.

Here we are using the Landsat image acquired from USGS Earth Explorer. The data is in GeoTiff format with 16 bit radiometric resolution (ranges from 0-65535). Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images consist of nine spectral bands with a spatial resolution of 30 meters for Bands 1 to 7 and 9. The resolution for Band 8 (panchromatic) is 15 meters. In addition it also have two Thermal IR bands with a spatial resolution of 100m (later resampled into 30 m).Before calculating the NDVI the DN data must be converted to reflectance using the equations given in their website. Here the IR and NIR bands are 4 and 5 respectively.

Table shows the Spectral characteristics of Landsat 8

Landsat 8

Operational

Land Imager

(OLI)

and

Thermal

Infrared

Sensor

(TIRS)

Bands

Wavelength

Resolution

Band 1 – Coastal aerosol

0.43 – 0.45

30

Band 2 – Blue

0.45 – 0.51

30

Band 3 – Green

0.53 – 0.59

30

Band 4 – Red

0.64 – 0.67

30

Band 5 – Near Infrared (NIR)

0.85 – 0.88

30

Band 6 – SWIR 1

1.57 – 1.65

30

Band 7 – SWIR 2

2.11 – 2.29

30

Band 8 – Panchromatic

0.50 – 0.68

15

Band 9 – Cirrus

1.36 – 1.38

30

Band 10 – Thermal Infrared
(TIRS) 1

10.60 – 11.19

100 * (30)

Band 11 – Thermal Infrared
(TIRS) 2

11.50 – 12.51

100 * (30)

 (Obtained from USGS website)

Step 1: Calculating Reflectance value from the Satellite data

OLI spectral radiance data can also be converted to TOA planetary reflectance using reflectance rescaling coefficients provided in the landsat8 OLI metadata file. The following equation is used to convert DN values to TOA reflectance for OLI image:

 

 

 

ρλ’ = M ρQ cal + A ρ

Where:

ρλ’ = TOA planetary reflectance, without correction for solar angle. Note that ρλ’ does not contain a correction for the sun angle.

M ρ = Band-specific multiplicative rescaling factor from the metadata (Reflectance_Mult_Band_x, where x is the band number)

A ρ = Band-specific additive rescaling factor from the metadata (Reflectance_Add_Band_x, where x is the band number)

Q cal = Quantized and calibrated standard product pixel values (DN).

(Metadata means the .txt file you can find along with the data)

I. Open ArcMap and add satellite images band 4 and band 5 for calculating NDVI.

Arc toolbox in Arc map

II. Open Arc toolbox in ArcMap

II. From the Arc toolbox open Raster calculator (Arc toolbox >Spatial Analyst tool > Map Algebra tool > Raster Calculator tool)

Raster calculator

IV. Find M ρ Band-specific multiplicative rescaling factor from the metadata    (Reflectance_Mult_Band_x, where x is the band number)

A ρ Band-specific additive rescaling factor from the metadata (Reflectance_Add_Band_x, where x is the band number)

metadata

An example of where the M ρ Band-specific multiplicative rescaling factor from the metadata

(Reflectance_Mult_Band_x, where x is the band number) is found within the metadata file

Apply and perform values in Raster calculator for both RED and NIR bands (4 and 5 bands)

Example

Band 4 reflectance= (2.0000E-05 * (“sub_tif_Band_4”)) + -0.100000

Where

REFLECTANCE_MULT_BAND_4 = 2.0000E-05

RFLECTANCE_ADD_BAND_4 = -0.100000

sub_tif_Band_4= 4th band (Red band)

Set the output folder and file name then click “OK”

Raster Calculator function
Raster Calculator function to perform reflectance calculation

Reflectance calculated
Reflectance calculated for band 4

V. Calculate the Reflectance of band 5th by using the same method.

Reflectance of band 5th
Reflectance calculated for band 5

Step 2: Correcting the Reflectance value with sun angle

Reflectance with a correction for the sun angle is then:

 

 

ρλ = ρλ ‘/cos θSZ = ρλ ‘/sin θSE

Where:

ρλ = TOA planetary reflectance

θSE = Local sun elevation angle. The scene center sun elevation angle in degrees is provided in the metadata (Sun Elevation).

θSZ = Local solar zenith angle; θSZ = 90° – θSE.

I. Find Sun Elevation from the metadata

Apply and perform the values in Raster calculator for both RED and NIR band reflectance values (4 and 5 bands)

Example

Band 4 corrected_ reflectance= (“4th_rflctnce”) / Sin (49.36816761)

Where:

SUN_ELEVATION = 49.36816761

4th_rflctce =uncorrected reflectance

Set the output folder and file name then click “OK”

Raster Calculator function
Raster Calculator function to perform sun angle corrected reflectance

corrected reflectance for band 4th
Sun angle corrected reflectance for band 4th

II. Calculate the Reflectance of band 5th by using the same method

Reflectance of band 5th
Sun angle corrected reflectance for band 5th

Step 3: Calculating NDVI from 4th and 5th bands

As we discussed earlier to find NDVI we use the formula of

NDVI

Here band 4= RED and band 5=NIR

I. Open Raster calculator and apply this formula and execute the program as follows

NDVI= (Band 5 correctedBand 4 corrected)/ (Band 5 corrected + Band 4 corrected)

Set the output folder and file name then click “OK”

Raster calculator
Raster Calculator function to perform NDVI

Normalized Differential Vegetation Index
Normalized Differential Vegetation Index

The value of NDVI is always between 1 and -1

Step 4: Calculating SAVI from Reflectance

Soil Adjusted Vegetation Index shows background soil conditions. SAVI is a hybrid between NDVI and PVI (Perpendicular Vegetation Index).

SAVI

Where NIR is the 5th band and RED is the 4th band respectively. L is the Soil brightness correction factor. The value of L varies by cover of green vegetation. High vegetation areas L= 0; the areas have no green vegetation then L=1. Generally L=0.5 in most causes and it works well. When L=0 then NDVI=SAVI

I. Open Raster calculator and apply this formula and execute the program as follows

SAVI= (Band 5 correctedBand 4 corrected)/ (Band 5 corrected + Band 4 corrected)*(1+L)

Raster Calculator function to perform SAVI
Raster Calculator function to perform SAVI

Soil Adjusted Vegetation Index
Soil Adjusted Vegetation Index

Step 5: Calculating Tasseled cap indices

Tasseled cap indices give the measure of Greenness, Brightness and Wetness of each pixel and utilize a linear combination of 6 Landsat bands (From 2nd band to 7th band). Tasseled cap indices is calculated by the following equation

Tas_cap =     (coeff * band2) + (coeff₃ * band3) + (coeff₄ * band4) +

                         (coeff₅ * band5) + (coeff₆* band6) + (coeff₇ * band7)

Where Tas_cap is the calculated tasseled cap index for brightness, greenness, or wetness from the coefficient given

 

Index

Band
2

(Blue)

Band
3

(Green)

Band
4

(Red)

Band
5

(NIR)

Band
6

(SWIR
1)

Band
7

(SWIR
2)

Brightness

0.3029

0.2786

0.4733

0.5599

0.508

0.1872

Greenness

−0.2941

−0.243

−0.5424

0.7276

0.0713

−0.1608

Wetness

0.1511

0.1973

0.3283

0.3407

−0.7117

−0.4559

 Given by Muhammad Hasan Ali Baig et al (2014)

 

Step 6: Calculating Tasseled cap Brightness indices

I. Calculate the Reflectance of Band 2, 3, 4, 5, 6, 7, using the same method mentioned above (Process 1 and 2)

II. Open Raster calculator and apply the formula for Brightness index and execute the program as follows

Tas_cap = (0.3029 *(2nd_Band_correted))+

                         ( 0.2786 *(3rd_Band_correted))+

                         ( 0.4733 *(4th_Band_correted))+

                         ( 0.5599 *(5th_Band_correted))+

                          ( 0.508 *(6th_Band_correted))+

                          ( 0.1872 *(7th_Band_correted))

Raster Calculator function to perform SAVI Raster Calculator function to perform SAVI

AVI Raster Calculator
Raster Calculator function to perform Brightness index

Tasseled cap brightness index
Tasseled cap brightness index

Step 7: Similarly calculate the other indices using the same method mentioned above

Tasseled cap wetness index
Tasseled cap wetness index

Tasseled cap Greenness index
Tasseled cap Greenness index

References:

http://landsat.gsfc.nasa.gov/?p=3186

http://hydrology1.nmsu.edu/teaching/soil698/greenseeker/what_is_ndvi.htm

http://www.pvts.net/pdfs/ndvi/3_3_ndvi.PDF

http://wiki.landscapetoolbox.org/doku.php/remote_sensing_methods:normalized_difference_vegetation_index

Muhammad Hasan Ali Baigab, Lifu Zhanga, Tong Shuaiab & Qingxi

Tonga- “Derivation of a tasselled cap transformation based on Landsat 8 atsatellite reflectance” (2014) Remote Sensing Letters

http://www.tandfonline.com/loi/trsl20

Grant J. Firl, Lane Carter” Calculating Vegetation Indices from Landsat 5 TM and Landsat 7 ETM+ Data”(2011)

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