This reader uses espatools to read Landsat imagery via an XML metadata file. Espatools is an open-source Python package for simple loading of Landsat imagery as NumPy arrays and we have built an easy to use interface to load any Landsat imagery directly into ParaView with an ability to choose predefined color schemes!
LandsatReader in PVGeo is meant for direct use in ParaView and we would not recommend using
LandsatReader in a standalone Python environment as
espatools has a much simpler API. If you’d like to see the code docs for this reader, then: Take a look at
LandsatReader‘s code docs here.
Download any Landsat data from USGS’ Earth Explorer and open the XML file adjacent to the data files using PVGeo’s Landsat Reader in ParaView.
For this example, we downloaded Landsat 8 imagery over Golden & Boulder, Colorado. This raster set is from Path 34 Row 32 during June 27, 2018. The demonstrated dataset comes as a
.tar.gz compressed dataset which contains 10 bands (
.tif files) and a few metadata 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. Using PVGeo in ParaView, you can select File->Open… and select the
.xml metadata file and PVGeo will know to use the
LandsatReader to read all of the bands.
Select your bands¶
Go ahead and load up all the data! If you only want a few bands, then select them from the checklist like the image below:
Select your bands using the checkboxes. We usually load all of the bands but if you want to conserve memory and have faster file reads, definitely only select the bands you desire.
After loading you can select any of the bands as data arrays to display in the Render View. Here is an example of Band 3 from our sample dataset: