Landsat raster file I/O
An open-source Python package for simple loading of Landsat imagery as NumPy arrays. When downloading Landsat imagery from USGS Earth Explorer, the datasets contain many bands (.tif files) and a few metadata files (.txt and .xml files). espatools is built to parse the .xml metadata file to read all of the bands for that dataset and provide a convenient and intuitive means of accessing that metadata along side the raw data in a Python environment. espatools can be found on GitHub and PyPI.
The package heavily uses properties for the creation of strongly typed objects in a consistent, declarative way.
This package implements a way to convert these datasets to a PyVista dataset (vtkImageData).
PVGeo has implemented an interface for espatools to read Landsat imagery via XML metadata files. Check out PVGeo’s Landsat Reader for more details.
espatools is available from PyPI
$ pip install espatools
We think espatools is easy to use; give it a try and let us know what you think as this is just the alpha-release!
First, checkout this Jupyter Notebook for a demonstration of some simple plotting after reading Landsat imagery in a Python environment.
And take a look at the .to_pyvista() method on RasterSet objects to have a 3D dataset of the imagery in PyVista/VTK
Then take a look at the Landsat Reader in PVGeo’s documentation where espatools has an interface for direct use in ParaView.
Example False Color
import espatools import matplotlib.pyplot as plt # Create the reader to manage I/O reader = espatools.RasterSetReader(filename='metadata.xml') # Perform the read and yield a raster set raster = reader.read() # Get an RGB color scheme color = raster.get_rgb('false_a') # Now plot the false color image plt.imshow(color)
The results of the above code yield the following false color image:
You can also view the dataset in 3D using PyVista:
mesh = raster.to_pyvista() mesh.plot(scalars='false_a', rgb=True, cpos='xy')
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