Geoscience Reference
In-Depth Information
whos
reveals that the data are in a unsigned 16-bit format
uint16
, i.e., the maximum
range of the data is from 0 to 2
16
=65,536.
I1 7771x7611 118290162 uint16
I2 7771x7611 118290162 uint16
I3 7771x7611 118290162 uint16
For quantitative analyses these digital number (DN) values need to be
converted to radiance and rel ectance values, which is beyond the scope of
the topic. h e radiance is the power density scattered from the earth in a
particular direction and has the units of watts per square meter per steradian
(Wm
-2
sr
-1
) (Richards 2013). h e radiance values need to be corrected for
atmospheric and topographic ef ects to obtain earth surface rel ectance
percentages. h e Landsat 8 Handbook provides the necessary information
on these conversions:
https://landsat.usgs.gov/Landsat8_Using_Product.php
We will instead use the Landsat 8 data to create an RGB composite of bands
4, 3, and 2 to be used for i eldwork. Since the image has a relatively low
level of contrast, we use
adapthisteq
to perform a contrast-limited adaptive
histogram equalization (CLAHE) (Zuiderveld 1994). Unlike
histeq
used in
the previous section, the
adapthisteq
algorithm works on small regions (or
tiles) of the image, rather than on the entire image. h e neighboring tiles are
then combined using bilinear interpolation to eliminate edge ef ects.
I1 = adapthisteq(I1,'ClipLimit',0.1,'Distribution','Rayleigh');
I2 = adapthisteq(I2,'ClipLimit',0.1,'Distribution','Rayleigh');
I3 = adapthisteq(I3,'ClipLimit',0.1,'Distribution','Rayleigh');
Using
ClipLimit
with a real scalar between 0 and 1 limits the contrast
enhancement, while higher numbers result in increased contrast; the default
value is 0.01. h e
Distribution
parameter sets the desired histogram shape
for the tiles by specifying a distribution type, such as
Uniform
,
Rayleigh
, or
Exponential
. Using a
ClipLimit
of 0.1 and a
Rayleigh
distribution yields good
results. h e three bands are concatenated to a 24-bit RGB images using
cat
.
I = cat(3,I1,I2,I3);
We only display that section of the image containing the Chew Bahir Basin
(using axes limits) and hide the coordinate axes. We scale the images to 10%
of the original size to i t the computer screen.
axes('XLim',[3000 5000],'YLim',[1000 4000],'Visible','Off'), hold on
