Usage¶

Start by downloading Sentinel-2 Level-2A or Level-1C product in SAFE format (e.g. from Copernicus Open Access Hub and unzip. Open Python prompt in s2lx environment and import classes from s2lx:

>>> from s2lx import *

Open SAFE data:

>>> s = SAFE('/path/to/safename.SAFE/MTD_MSIL2A.xml')

You can preview whole scene:

>>> s.preview()

Clip region of interest (note that bounds are defined in coordinate system of scene) and store in S2 collection:

>>> bounds = (440000, 5093000, 494000, 5123000)  # (minx, miny, maxx, maxy)
>>> d = s.clip(bounds, name='My Region')

To see the list of bands:

>>> d.bands
['b11', 'b12', 'b2', 'b3', 'b4', 'b5', 'b6', 'b7', 'b8']

Individual bands could ba accessed as properties:

>>> d.b4.show()

You can use Composite class to create RGB composite:

>>> rgb = Composite(d.b4, d.b3, d.b2, name='True Color')
>>> rgb.show()

or:

>>> rgb = Composite(d.b12, d.b11, d.b8, name='False Color')
>>> rgb.show()

Bands and composites could be saved to GeoTIFF with save method:

>>> d.b4.save('b4.tif')
>>> rgb.save('truecolor.tif')

Bands support simple mathematical operations (addition, subtraction, division, multiplication)

>>> alt = Composite(d.b11/d.b12, d.b4/d.b2, d.b4/d.b11, name='Alterations')
>>> alt.show()

Bands could be filtered (check s2lx.s2filters for possible filters):

>>> medfilter = median_filter(radius=4)
>>> b12f = d.b12.apply(medfilter)

You can do PCA analysis using S2.pca method:

>>> p = d.pca()

To create RGB composite from first three principal components:

>>> pca = Composite(p.pc0, p.pc1, p.pc4, name='PCA')
>>> pca.show()

You can use also PCA to filter your data, i.,e. use only few PC to reconstruct dataset. Here we remove last four (from 9) components with lowest explained variance and reconstruct all bands:

>>> r = d.restored_pca(remove=(5,6,7,8))
>>> altr = Composite(r.b11/r.b12, r.b4/r.b2, r.b4/r.b11, name='Alterations filtered')
>>> altr.show()