Rasterio basic tutorial- Part I

import rasterio # import the main rasterio function import matplotlib # matplotlib is the primary python plotting and viz library import matplotlib.pyplot as plt # this bit of magic allows matplotlib to plot inline in a jupyter notebook %matplotlib inline import numpy as np from rasterio.plot import show

img='/work/LE70220491999322EDC01_stack.gtif' data=rasterio.open(img) print(data)

<open DatasetReader name='/work/LE70220491999322EDC01_stack.gtif' mode='r'>

bands=data.count print(bands)

rows, col=data.shape print(rows, col)

250 250

desc=data.descriptions meta=data.meta print(desc) print(meta)

('band 1 reflectance', 'band 2 reflectance', 'band 3 reflectance', 'band 4 reflectance', 'band 5 reflectance', 'band 7 reflectance', 'band 6 temperature', None)
{'driver': 'GTiff', 'dtype': 'int16', 'nodata': -9999.0, 'width': 250, 'height': 250, 'count': 8, 'crs': CRS.from_epsg(32615), 'transform': Affine(30.0, 0.0, 462405.0,
       0.0, -30.0, 1741815.0)}

driver=data.driver print(driver)

GTiff

prj=data.crs print(prj)

EPSG:32615

gt=data.transform print(gt)

| 30.00, 0.00, 462405.00|
| 0.00,-30.00, 1741815.00|
| 0.00, 0.00, 1.00|

nir=data.read(4) #open the 4th band of image which is near infrared nir.shape # check dimensions

datatype=data.dtypes # check bands data type print(datatype)

('int16', 'int16', 'int16', 'int16', 'int16', 'int16', 'int16', 'int16')

# display entire image full_img=data.read() full_img.shape # bands, rows, col

# plot image nir band show(nir, transform=data.transform, cmap='gray')

# we can also use matplotlib to show nir band plt.imshow(nir) plt.colorbar() plt.title('Overview - Band 4 {}'.format(nir.shape)) plt.xlabel('Column #') plt.ylabel('Row #')