Home Articles A relationship between NDVI and tasseled cap techniques

A relationship between NDVI and tasseled cap techniques

Shima Sajadi
Lecturer of Geodesy Department, Eshragh University,

North Khorasan, Bojnourd, Iran

[email protected]

NDVI is particularly used to assess the presence and condition of vegetation. Tasseled cap is another index which creates three band images. The three bands represent brightness, greenness, wetness for area under consideration. The present study aims particularly at comparing high NDVI area and greenness values given by tasseled cap and low NDVI values and high brightness values.


NDVI calculations are based on the principle that actively growing green plants strongly absorb radiation in the visible region of the spectrum (the “PAR,” or “Photosynthetically Active Radiation”) while strongly reflecting radiation in the Near Infrared region. The concept of vegetative “spectral signatures (patterns)” is based on this principle. Given the following abbreviations:

PAR: Value of Photosynthetically Active Radiation from a pixel

NIR: Value of Near-Infrared Radiation from a pixel

The NDVI for a pixel is calculated from the following formula:

Where NIR shows Near Infrared band and R shows Red band.

NDVI has been in use for many years to:

  • To measure and monitor plant growth (vigor), vegetation cover, and biomass production from multispectral satellite data.
  • To model the abundance of living planet material from satellite image and data.
  • To simply and quickly identify vegetated areas and their condition

The value of NDVI varies between -1( usually water) to 1( strongest vegetative grothw).

High NDVI represents an area with healthy vegetation. And NDVI of an area with dense vegetation will tend to positive values (0.3 to 0.8).

Tasseled cap
Tasseled Cap transformation is one of the available methods for enhancing spectral information content of Landsat TM data. Tasseled Cap transformation especially optimizes data viewing for vegetation studies. Tasseled Cap index was calculated from data of the related six TM bands. Three of the six tasseled cap transform bands are often used:

band 1 (brightness, measure of soil)

band 2 (greenness, measure of vegetation)

band 3 (wetness, interrelationship of soil and canopy moisture)

The Tasseled Cap Transformation in remote sensing is the conversion of the readings in a set of channels into composite values; i.e., the weighted sums of separate channel readings.

One of these weighted sums measures roughly the brightness of each pixel in the scene.

The other composite values are linear combinations of the values of the separate channels, but some of the weights are negative and others positive. One of these other composite values represents the degree of greenness of the pixels and another might represent the degree of yellowness of vegetation or perhaps the wetness of the soil. Usually there are just three composite variables.

The weights used in principal component analysis are determined statistically from the data but it was soon observed that typically the first principal component typically corresponded to roughly equal weights. In other words, the data generally fall along the diagonal when channel values are plotted together. If the weights used in a weighted-sum transformation are equal then the values obtained are proportional to the sum of the channel values and hence correspond to “brightness.”

Principal component analysis is equivalent to transforming the data to a new coordinate system with a new set of orthogonal axes. The tasseled cap transformation also corresponds to a transformation of the data to a new set of orthogonal axes. While the tasseled cap transformation was inspired by the method of principal component analysis combined with generalization from empirical observations the actual details had a more analytical basis.

In the other hand, the concept of tasseled cap transformation is a useful tool for compressing spectral data into a few bands associated with physical scene characteristics (Crist and Cicone 1984). Originally constructed for understanding important phenomena of crop development in spectral space (Kauth and Thomas 1976), the transformation has potential applications in revealing key forest attributes including species, age and structure

1.2.1. Brightness – Greenness -Wetness
The Brightness, Greenness, Wetness transform was first developed for use with the Landsat MSS system and called the “Tasseled Cap” transformation. The transform is based on a set of constants applied to the image in the form of a linear algebraic formula.

The transform developed for the MSS consisted of coefficients that extracted brightness and greenness. This was due to the spectral resolution of the MSS that focused primarily in the visible and near infrared.

Following the launch of Landsat 4 and the inclusion of the Thematic Mapper, these coefficients were recalculated to take advantage of the increased spectral resolution of the TM. This allowed for the extraction of an additional component called wetness due to the inclusion of the MIR channels that are sensitive to moisture absorption.

Table 1: Tasseled cap coefficients
Location (Study area):
Study is done at Manipur valley in Northeast India to determine the healthy vegetated area.

Manipur is a state in northeastern India making its capital in the city of Imphal. Manipur is situated between 23.83oN and 25.68oN latitude and 93.03oE and 94.78oE longitude. It comprises 1820 sq.km of flat plateau of alluvial valley and 20507sq.km of hill territory and forms a part of the Himalayan mountain system which carries this cup-shaped wonderland inside its series of hill ranges.

Figure1: Study area- Manipur valley and surrounding area

Figure 2: NDVI image Legend

Figure 3: Tasseled cap image
Result and Conclusion:
Band 1 represents the Green band in MSS and LISS III sensors.

Band 2 represents the Red band in MSS and LIS III sensors.

Band 3 represents the Near.IR band in MSS and LISS III sensor.

Band 4 represents the Mid.IR band in MSS and LISS III sensor.

Each band has a different DN value. Consider the below example:

According to the tasseled cap coefficient table which is acquired from tasseled cap image, this image involves 3 bands that are called as Greenness, Brightness and Wetness.

The value of each of them is calculated by this formula:

DN value of each band *tasseled cap coefficient
At the end, the summation of all values will give the brightness or wetness or green ness value of that pixel, (Table 1)

  • The original image (satellite image) used in this study involves green (B1), red (B2), nearIR (B3), midIR (B4).
  • The high NDVI value represents healthy vegetated area in NDVI image.
  • The tasseled cap image involves greenness, brightness and wetness bands. The high greenness value represents healthy vegetated area in tasseled cap image. This is confirmed by overlapping NDVI classes on TC image and it is found that high NDVI areas and areas of high Greenness overlap.
  • Similarly high wetness areas overlap the low NDVI areas and high brightness areas overlap moderate NDVI areas.
  • Based on the overlapping of tasseled cap image and NDVI image is observed, that the most of the area of healthy vegetation is located in the east part of Manipuri Valley which extended from north to south.


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