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Merge pull request #239 from simonrp84/landsat_rsr
Update Landsat RSR reader, add support for Landsat-9 OLI+TIRS
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| #!/usr/bin/env python | ||
| # -*- coding: utf-8 -*- | ||
| # | ||
| # Copyright (c) 2017-2024 Pytroll developers | ||
| # | ||
| # | ||
| # This program 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. | ||
| # | ||
| # This program 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 this program. If not, see <http://www.gnu.org/licenses/>. | ||
|
|
||
| """Landsat-8/9 OLI/TIRS reader. | ||
| This reader generates spectral responses for OLI and TIRS instruments aboard Landsat-8 and -9. | ||
| We assume that the instruments are one combined instrument from the user perspective, called `oli_tirs` rather | ||
| than generating RSRs for the two instruments separately. | ||
| The original spectral response data can be found at the links below. | ||
| Landsat-8/OLI: | ||
| = https://landsat.gsfc.nasa.gov/wp-content/uploads/2014/09/Ball_BA_RSR.v1.2.xlsx | ||
| Landsat-9/OLI-2: | ||
| = https://landsat.gsfc.nasa.gov/wp-content/uploads/2024/03/L9_OLI2_Ball_BA_RSR.v2-1.xlsx | ||
| Landsat-8/TIRS: | ||
| = https://landsat.gsfc.nasa.gov/wp-content/uploads/2013/06/TIRS_Relative_Spectral_Responses.BA_.v1.xlsx | ||
| Landsat-9/TIRS-2: | ||
| = https://landsat.gsfc.nasa.gov/wp-content/uploads/2021-10/L9_TIRS2_Relative_Spectral_Responses.BA.v1.0.xlsx | ||
| """ | ||
|
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| import logging | ||
| from pathlib import Path | ||
|
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| import numpy as np | ||
| import pandas as pd | ||
|
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| from pyspectral.raw_reader import InstrumentRSR | ||
| from pyspectral.utils import convert2hdf5 as tohdf5 | ||
|
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| LOG = logging.getLogger(__name__) | ||
|
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| OLI_BAND_NAMES = {"B1": "CoastalAerosol", | ||
| "B2": "Blue", | ||
| "B3": "Green", | ||
| "B4": "Red", | ||
| "B5": "NIR", | ||
| "B6": "Cirrus", | ||
| "B7": "SWIR1", | ||
| "B8": "SWIR2", | ||
| "B9": "Pan"} | ||
|
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| TIRS_SHEETNAMES_L8 = {"B10": "TIRS BA RSR", | ||
| "B11": "TIRS BA RSR"} | ||
| TIRS_BAND_NAMES_L8 = {"B10": "TIRS1 10.8um band average", | ||
| "B11": "TIRS2 12.0um band average"} | ||
|
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| TIRS_SHEETNAMES_L9 = {"B10": "TIRS Band 10 BA RSR", | ||
| "B11": "TIRS Band 11 BA RSR"} | ||
| TIRS_BAND_NAMES_L9 = {"B10": "Band 10 Band=Average RSR", | ||
| "B11": "Band 11 Band-Average RSR"} | ||
|
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| class OliRSR(InstrumentRSR): | ||
| """Class for Landsat OLI RSR.""" | ||
|
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| def __init__(self, bandname, platform_name): | ||
| """Read the Landsat OLI relative spectral responses for all channels.""" | ||
| super(OliRSR, self).__init__(bandname, platform_name) | ||
| self.instrument = "oli_tirs" | ||
| self._get_options_from_config() | ||
| self.band = bandname | ||
| opts = self.options[f"{platform_name}-{self.instrument}"] | ||
| if bandname in OLI_BAND_NAMES: | ||
| self.path = Path(opts["path"]) / Path(opts["oli"]) | ||
| elif bandname in TIRS_BAND_NAMES_L8: | ||
| self.path = Path(opts["path"]) / Path(opts["tirs"]) | ||
| else: | ||
| raise ValueError(f"Unknown band name: {bandname}") | ||
|
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| LOG.debug(f"Filename: {self.path}") | ||
| if self.path.exists(): | ||
| self._load() | ||
| else: | ||
| raise IOError("Couldn't find an existing file for this band: " + | ||
| str(self.bandname)) | ||
|
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| def _load(self, scale=0.001): | ||
| """Load the Landsat OLI relative spectral responses.""" | ||
| if self.band in OLI_BAND_NAMES: | ||
| df = pd.read_excel(self.path, engine="openpyxl", sheet_name=OLI_BAND_NAMES[self.band]) | ||
| wvl = np.array(df["Wavelength"]) / 1000. | ||
| resp = np.array(df["BA RSR [watts]"]) | ||
| else: | ||
| if self.platform_name == "Landsat-8": | ||
| sheet_name = TIRS_SHEETNAMES_L8[self.band] | ||
| band_name = TIRS_BAND_NAMES_L8[self.band] | ||
| elif self.platform_name == "Landsat-9": | ||
| sheet_name = TIRS_SHEETNAMES_L9[self.band] | ||
| band_name = TIRS_BAND_NAMES_L9[self.band] | ||
| else: | ||
| raise ValueError(f"Unknown platform: {self.platform_name}") | ||
| df = pd.read_excel(self.path, engine="openpyxl", sheet_name=sheet_name) | ||
|
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| wvl = np.array(df["wavelength [um]"]) / 1000. | ||
| resp = np.array(df[band_name]) | ||
|
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| # Cut unneeded points | ||
| pts = np.argwhere(resp > 0.002) | ||
| wvl = np.squeeze(wvl[pts]) | ||
| resp = np.squeeze(resp[pts]) | ||
|
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| self.rsr = {"wavelength": wvl, | ||
| "response": resp} | ||
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| if __name__ == "__main__": | ||
| bands = sorted(OLI_BAND_NAMES.keys()) + sorted(TIRS_BAND_NAMES_L8.keys()) | ||
| for platform_name in ["Landsat-8", "Landsat-9"]: | ||
| tohdf5(OliRSR, platform_name, bands) |
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