Principal Component Analysis (PCA) on LANDSAT-8 imagery
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.
Citar como
ABHILASH SINGH (2024). 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. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxEtiquetas
Agradecimientos
Inspirado por: Principal Component Analysis (PCA) on images in MATLAB (GUI)
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Descubra Live Editor
Cree scripts con código, salida y texto formateado en un documento ejecutable.
PCA on LANDSAT8 imagery
Versión | Publicado | Notas de la versión | |
---|---|---|---|
1.0.0 |