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Reading and manipulaing satellite sensor spectral responses and the solar spectrum, to perfom various corrections to VIS and NIR band data

Project description

Pyspectral

Build status Anaconda-Server Badge Build status Coverage Status PyPI version

Given a passive sensor on a meteorological satellite Pyspectral provides the relative spectral response (rsr) function(s) and offer you some basic operations like convolution with the solar spectrum to derive the in band solar flux, for instance. The focus is on imaging sensors like AVHRR, VIIRS, MODIS, ABI, AHI, OLCI and SEVIRI. But more sensors are included and if others are needed they can be easily added. With Pyspectral it is possible to derive the reflective and emissive parts of the signal observed in any NIR band around 3-4 microns where both passive terrestrial emission and solar backscatter mix the information received by the satellite. Furthermore Pyspectral allows correcting true color imagery for the background (climatological) atmospheric signal due to Rayleigh scattering of molecules, absorption by atmospheric gases and aerosols, and Mie scattering of aerosols.

Adam Dybbroe May 2021, Norrkoping, Sweden

License

Copyright 2013 Pyspectral developers

Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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