Principal Component Analysis (PCA) on LANDSAT-8 imagery

Applying PCA on the composite LANDSAT-8 satellite imagery.

https://www.abhilashsingh.net/?source=pca_landsat8

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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.

Cite As

ABHILASH SINGH (2026). Principal Component Analysis (PCA) on LANDSAT-8 imagery (https://au.mathworks.com/matlabcentral/fileexchange/88582-principal-component-analysis-pca-on-landsat-8-imagery), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.0