INDICES FOR INFORMATION EXTRACTION
FROM SATELLITE IMAGERY
Mirza Muhammad Waqar
Contact:
mirza.waqar@ist.edu.pk
+92-21-34650765-79 EXT:2257
RG610
Course: Introduction to RS & DIP
Outlines
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Introduction
Band Ratio
Normalized Difference Vegetation Index (NDVI)
Normalized Difference Water Index (NDWI)
Normalized Difference Snow Index (NDSI)
Normalized Difference Built-up Area Index (NDBI)
Vegetation Condition Index (VCI)
Mean Referenced Vegetation Condition Index (MVCI)
NDVI Change Ratio to Previous Year
Introduction
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Indices are used to enhance a particular single feature on
image.
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Different indices are used to enhance different features on
image, like enhancement of vegetation, water , snow etc.
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Indices discussed in my lecture are
1. NDVI (Normalized Difference Vegetation Index)
2. NDWI (Normalized Difference Water Index)
3. NBI (Normalized Built-up Index)
4. NDSI (Normalized Difference Snow Index)
Band ratio
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Aerial images commonly exhibit illumination differences
produced by
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Shadows
Differing surface slope angles
Slope directions.
Because of these effects, the brightness of each surface
material can vary from place to place in the image.
Although these variations help us to visualize the threedimensional shape of the landscape, they hamper our
ability to recognize materials with similar spectral
properties.
We can remove these effects, and accentuate the spectral
differences between materials, by computing a ratio image
using two spectral bands.
Example of Band ratio
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A ratio of near infrared (NIR) and red bands
(TM4 / TM3)
This ratio is useful in mapping vegetation and vegetation
condition.
Note:- Simple band ratio have some problems like sensor
noise amplification and range/distortion of the calculated
values.
NDVI (Normalized Difference Vegetation Index)
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A variant method of the simple ratio calculation that avoids
problems in band ratio.
Corresponding cell values in the two bands are first subtracted,
and this difference is then “normalized” by dividing by the sum
of two brightness values.
The normalization tends to reduce artifacts related to sensor
noise, and most illumination effects still are removed.
The most widely used example is the Normalized Difference
Vegetation Index (NDVI), which is
(NIR – RED)/(NIR + RED). Or
(Band4 – Band3)/(Band4 + Band3)
NDVI (Normalized Difference Vegetation Index)
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NDWI (Normalized Difference Water Index)
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NDWI is used to enhance water index in a
given image.
Formula for normalized difference water
index is
(GREEN – NIR)/(GREEN + NIR).
Or
(Band4 – Band5)/(Band4 + Band5).
NDWI (Normalized Difference Water Index)
NDSI (Normalized Difference Snow Index)
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NDSI is used to enhance snow index in a
given image.
Formula for normalized difference water
index is
(BLUE – NIR)/(BLUE + NIR).
Or
(Band2 – Band5)/(Band2 + Band5).
NDBI (Normalized Difference built-up Index)
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NDBI is used to enhance built-up index in a
given image.
Formula for normalized difference built-up
index is
(Band5 – Band4)/(Band5 + Band4).
NDBI (Normalized Difference built-up Index)
Vegetation Condition Index
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VCIj is the image of vegetation condition index values for date j;
NDVIj is the image of NDVI values for date j;
NDVImax and NDVImin are images of maximum and minimum NDVI
values from all images within the data set;
VCI assesses changes in the NDVI signal through time due
to weather conditions, reducing the influence of
‘geographic’ (Kogan, 1990) or ‘ecosystem’ (Kogan, 1995c)
variables i.e. climate, soils, vegetation type and topography.
Mean Referenced Vegetation Condition Index (MVCI)
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Let NDVIm(x, y), NDVImax(x, y) and NDVImin(x, y) be the
mean, maximum and minimum of the time series NDVI at
location (x, y) across entire time span.
Let NDVIi(x, y) be the current NDVI. Then a measure of
vegetation condition can be defined by the NDVI percent
change ratio to the historical NDVI time series mean
NDVIm(x, y) as following:
NDVI Change Ratio to Previous Year
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Let NDVIi(x, y) be the current year NDVI value at
location (x, y), and NDVIi-1(x, y) be the previous
year NDVI. The current year NDVI ratio to the
previous year value is given by
Questions & Discussion