# Copyright (c) 2015-2022 Satpy developers
#
# This file is part of satpy.
#
# satpy is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# satpy is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# satpy. If not, see <http://www.gnu.org/licenses/>.
"""Composite classes for spectral adjustments."""
import logging
from satpy.composites import GenericCompositor
from satpy.dataset import combine_metadata
LOG = logging.getLogger(__name__)
[docs]
class SpectralBlender(GenericCompositor):
"""Construct new channel by blending contributions from a set of channels.
This class can be used to compute weighted average of different channels.
Primarily it's used to correct the green band of AHI and FCI in order to
allow for proper true color imagery.
Below is an example used to generate a corrected green channel for AHI using a weighted average from
three channels, with 63% contribution from the native green channel (B02), 29% from the red channel (B03)
and 8% from the near-infrared channel (B04)::
corrected_green:
compositor: !!python/name:satpy.composites.spectral.SpectralBlender
fractions: [0.63, 0.29, 0.08]
prerequisites:
- name: B02
modifiers: [sunz_corrected, rayleigh_corrected]
- name: B03
modifiers: [sunz_corrected, rayleigh_corrected]
- name: B04
modifiers: [sunz_corrected, rayleigh_corrected]
standard_name: toa_bidirectional_reflectance
Other examples can be found in the``ahi.yaml`` composite file in the satpy distribution.
"""
def __init__(self, *args, fractions=(), **kwargs):
"""Set default keyword argument values."""
self.fractions = fractions
super().__init__(*args, **kwargs)
def __call__(self, projectables, optional_datasets=None, **attrs):
"""Blend channels in projectables using the weights in self.fractions."""
if len(self.fractions) != len(projectables):
raise ValueError("fractions and projectables must have the same length.")
projectables = self.match_data_arrays(projectables)
new_channel = sum(fraction * value for fraction, value in zip(self.fractions, projectables))
new_channel.attrs = combine_metadata(*projectables)
return super().__call__((new_channel,), **attrs)
[docs]
class HybridGreen(SpectralBlender):
"""Corrector of the FCI or AHI green band.
The green band in FCI and AHI (and other bands centered at 0.51 microns) deliberately
misses the chlorophyll spectral reflectance local maximum at 0.55 microns
in order to focus on aerosol and ash rather than on vegetation. This
affects true colour RGBs, because vegetation looks brown rather than green
and barren surface types typically gets a reddish hue.
To correct for this the hybrid green approach proposed by Miller et al. (2016, :doi:`10.1175/BAMS-D-15-00154.2`)
is used. The basic idea is to include some contribution also from the 0.86 micron
channel, which is known for its sensitivity to vegetation. The formula used for this is::
hybrid_green = (1 - F) * R(0.51) + F * R(0.86)
where F is a constant value, that is set to 0.15 by default in Satpy.
For example, the HybridGreen compositor can be used as follows to construct a hybrid green channel for
AHI, with 15% contibution from the near-infrared 0.85 µm band (B04) and the remaining 85% from the native
green 0.51 µm band (B02)::
hybrid_green:
compositor: !!python/name:satpy.composites.spectral.HybridGreen
fraction: 0.15
prerequisites:
- name: B02
modifiers: [sunz_corrected, rayleigh_corrected]
- name: B04
modifiers: [sunz_corrected, rayleigh_corrected]
standard_name: toa_bidirectional_reflectance
Other examples can be found in the ``ahi.yaml`` and ``ami.yaml`` composite
files in the satpy distribution.
"""
def __init__(self, *args, fraction=0.15, **kwargs):
"""Set default keyword argument values."""
fractions = (1 - fraction, fraction)
super().__init__(fractions=fractions, *args, **kwargs)
[docs]
class NDVIHybridGreen(SpectralBlender):
"""Construct a NDVI-weighted hybrid green channel.
This green band correction follows the same approach as the HybridGreen compositor, but with a dynamic blend
factor `f` that depends on the pixel-level Normalized Differece Vegetation Index (NDVI). The higher the NDVI, the
smaller the contribution from the nir channel will be, following a liner (default) or non-linear relationship
between the two ranges `[ndvi_min, ndvi_max]` and `limits`.
As an example, a new green channel using e.g. FCI data and the NDVIHybridGreen compositor can be defined like::
ndvi_hybrid_green:
compositor: !!python/name:satpy.composites.spectral.NDVIHybridGreen
ndvi_min: 0.0
ndvi_max: 1.0
limits: [0.15, 0.05]
strength: 1.0
prerequisites:
- name: vis_05
modifiers: [sunz_corrected, rayleigh_corrected]
- name: vis_06
modifiers: [sunz_corrected, rayleigh_corrected]
- name: vis_08
modifiers: [sunz_corrected ]
standard_name: toa_bidirectional_reflectance
In this example, pixels with NDVI=0.0 will be a weighted average with 15% contribution from the
near-infrared vis_08 channel and the remaining 85% from the native green vis_05 channel, whereas
pixels with NDVI=1.0 will be a weighted average with 5% contribution from the near-infrared
vis_08 channel and the remaining 95% from the native green vis_05 channel. For other values of
NDVI a linear interpolation between these values will be performed.
A strength larger or smaller than 1.0 will introduce a non-linear relationship between the two ranges
`[ndvi_min, ndvi_max]` and `limits`. Hence, a higher strength (> 1.0) will result in a slower transition
to higher/lower fractions at the NDVI extremes. Similarly, a lower strength (< 1.0) will result in a
faster transition to higher/lower fractions at the NDVI extremes.
"""
def __init__(self, *args, ndvi_min=0.0, ndvi_max=1.0, limits=(0.15, 0.05), strength=1.0, **kwargs):
"""Initialize class and set the NDVI limits, blending fraction limits and strength."""
if strength <= 0.0:
raise ValueError(f"Expected strength greater than 0.0, got {strength}.")
self.ndvi_min = ndvi_min
self.ndvi_max = ndvi_max
self.limits = limits
self.strength = strength
super().__init__(*args, **kwargs)
def __call__(self, projectables, optional_datasets=None, **attrs):
"""Construct the hybrid green channel weighted by NDVI."""
LOG.info(f"Applying NDVI-weighted hybrid-green correction with limits [{self.limits[0]}, "
f"{self.limits[1]}] and strength {self.strength}.")
projectables = self.match_data_arrays(projectables)
ndvi = (projectables[2] - projectables[1]) / (projectables[2] + projectables[1])
ndvi = ndvi.clip(self.ndvi_min, self.ndvi_max)
# Introduce non-linearity to ndvi for non-linear scaling to NIR blend fraction
if self.strength != 1.0: # self._apply_strength() has no effect if strength = 1.0 -> no non-linear behaviour
ndvi = self._apply_strength(ndvi)
# Compute pixel-level NIR blend fractions from ndvi
fraction = self._compute_blend_fraction(ndvi)
# Prepare input as required by parent class (SpectralBlender)
self.fractions = (1 - fraction, fraction)
return super().__call__([projectables[0], projectables[2]], **attrs)
[docs]
def _apply_strength(self, ndvi):
"""Introduce non-linearity by applying strength factor.
The method introduces non-linearity to the ndvi for a non-linear scaling from ndvi to blend fraction in
`_compute_blend_fraction`. This can be used for a slower or faster transision to higher/lower fractions
at the ndvi extremes. If strength equals 1.0, this operation has no effect on the ndvi.
"""
ndvi = ndvi ** self.strength / (ndvi ** self.strength + (1 - ndvi) ** self.strength)
return ndvi
[docs]
def _compute_blend_fraction(self, ndvi):
"""Compute pixel-level fraction of NIR signal to blend with native green signal.
This method linearly scales the input ndvi values to pixel-level blend fractions within the range
`[limits[0], limits[1]]` following this implementation <https://stats.stackexchange.com/a/281164>.
"""
fraction = (ndvi - self.ndvi_min) / (self.ndvi_max - self.ndvi_min) * (self.limits[1] - self.limits[0]) \
+ self.limits[0]
return fraction