Source code for satpy.composites.spectral

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"""Composite classes for spectral adjustments."""

import logging
import warnings

import dask.array as da

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 stength 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}.") ndvi_input = self.match_data_arrays([projectables[1], projectables[2]]) ndvi = (ndvi_input[1] - ndvi_input[0]) / (ndvi_input[1] + ndvi_input[0]) ndvi.data = da.where(ndvi > self.ndvi_min, ndvi, self.ndvi_min) ndvi.data = da.where(ndvi < self.ndvi_max, ndvi, 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
[docs] class GreenCorrector(SpectralBlender): """Previous class used to blend channels for green band corrections. This method has been refactored to make it more generic. The replacement class is 'SpectralBlender' which computes a weighted average based on N number of channels and N number of corresponding weights/fractions. A new class called 'HybridGreen' has been created, which performs a correction of green bands centered at 0.51 microns following Miller et al. (2016, :doi:`10.1175/BAMS-D-15-00154.2`) in order to improve true color imagery. """ def __init__(self, *args, fractions=(0.85, 0.15), **kwargs): """Set default keyword argument values.""" warnings.warn( "'GreenCorrector' is deprecated, use 'SpectralBlender' instead, or 'HybridGreen' for hybrid green" " correction following Miller et al. (2016).", UserWarning, stacklevel=2 ) super().__init__(fractions=fractions, *args, **kwargs)