Principal Component Analysis (PCA) on LANDSAT-8 imagery
Updated Wed, 10 Mar 2021 12:11:41 +0000
Step's that we have followed;
1. Create a composite of bands. In our case, we have created a
composite of 11 bands of LANDSAT-8 images (Dated: 26-12-2020).
2. Convert each band into a column vector.
We will get an array of size n x p. Where p=11 in our case.
3. Standardise the data and apply PCA.
4. Reconstruct the original data.
ABHILASH SINGH (2023). Principal Component Analysis (PCA) on LANDSAT-8 imagery (https://www.mathworks.com/matlabcentral/fileexchange/88582-principal-component-analysis-pca-on-landsat-8-imagery), MATLAB Central File Exchange. Retrieved .
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Inspired by: Principal Component Analysis (PCA) on images in MATLAB (GUI)
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