Quick Start

For a quickstart, let’s see how to pre-process a Landsat-8 OLI multispectral imagery so a huge number of vegetation indices can be calculated and visualized.

Import the functions.

from raster4ml.preprocessing import stack_bands
from raster4ml.features import VegetationIndices
from raster4ml.plotting import Map

  1. Stacking bands

    stack_bands(image_paths=['Band_1.tif', 'Band_2.tif', 'Band_3.tif',
                         'Band_4.tif', 'Band_5.tif', 'Band_6.tif'],
            out_file='Stack.tif')

  2. Vegetation index calculation

    VI = VegetationIndices(image_path='Landsat8.tif',
                       wavelengths=[442.96, 482.04, 561.41, 654.59, 864.67, 1608.86, 2200.73])
VI.calculate(out_dir='vegetation_indices')

  1. Dynamic visualization in Jupyter Notebook

    m = Map()
m.add_raster(image_path='Landsat8.tif', bands=[4, 3, 2])
    Map output