satellite imagery.py

from glob import glob

import earthpy as et
import earthpy.spatial as es
import earthpy.plot as ep

import rasterio as rio
from rasterio.plot import plotting_extent
from rasterio.plot import show
from rasterio.plot import reshape_as_raster, reshape_as_image

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import ListedColormap

import plotly.graph_objects as go

np.seterr(divide='ignore', invalid='ignore')
S_sentinel_bands = glob("/content/drive/MyDrive/Satellite_data/sundarbans_data/*B?*.tiff")
S_sentinel_bands.sort()


l = []
for i in S_sentinel_bands:
  with rio.open(i, 'r') as f:
    l.append(f.read(1))
arr_st = np.stack(l)
ep.plot_bands(arr_st, cmap = 'gist_earth', figsize = (20, 12), cols = 6, cbar = False)
plt.show()


rgb = ep.plot_rgb(arr_st, 
                  rgb=(3,2,1), 
                  figsize=(10, 16), 
                  # title='RGB Composite Image'
                  )

plt.show()


ep.plot_rgb(
    arr_st,
    rgb=(3, 2, 1),
    stretch=True,
    str_clip=0.2,
    figsize=(10, 16),
    # title="RGB Composite Image with Stretch Applied",
)

plt.show()


colors = ['tomato', 'navy', 'MediumSpringGreen', 'lightblue', 'orange', 'blue',
          'maroon', 'purple', 'yellow', 'olive', 'brown', 'cyan']

ep.hist(arr_st, 
         colors = colors,
        title=[f'Band-{i}' for i in range(1, 13)], 
        cols=3, 
        alpha=0.5, 
        figsize = (12, 10)
        )

plt.show()


ndvi = es.normalized_diff(arr_st[7], arr_st[3])
ep.plot_bands(ndvi, cmap="RdYlGn", cols=1, vmin=-1, vmax=1, figsize=(10, 14))
plt.show()