Result for 3ADBBA488C0ABDCF23C451EAE4A8E3E06DBCB2E5

Query result

Key Value
FileName./usr/share/doc/python3-pyspectral/changelog.Debian.gz
FileSize696
MD57F8F0C97EC14A975FF9986ABA925EEE6
SHA-13ADBBA488C0ABDCF23C451EAE4A8E3E06DBCB2E5
SHA-256549D5FAE8421CAC8A34A0CBF78FF001559DA32484ED01228708946260F5CD5B1
SSDEEP12:X8DFKmNsaCO8f5RbiQqmFkyoutXOwf/37jV3RpKuoCnnoEs:X8DFKmNsaNo5Fk9YzrZ3ziCnoEs
TLSHT1BD0188D94C91F1420C6CCDEDA0F2530F03580DEA44DED9681E4E2AC31995403D7C641B
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize172096
MD5638515C3A05034D18DD0E5D428B3E7CA
PackageDescriptionReading and manipulaing satellite sensor spectral responses Reading and manipulaing satellite sensor spectral responses and the solar spectrum, to perform various corrections to VIS and NIR band data. . Given a passive sensor on a meteorological satellite PySpectral provides the relative spectral response (rsr) function(s) and offer 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pyspectral
PackageSectionpython
PackageVersion0.9.5+ds-1
SHA-1987C45577B9C254F644BB75981518844F9EE34B3
SHA-256AEA8177DBE8D3E880C1D06CFB50F4F27362C8EF7316E2EB41985F429DF5A773E
Key Value
FileSize3523364
MD5CB1911294AF0C65ECDD594BBF502BF2C
PackageDescriptionReading and manipulaing satellite sensor spectral responses - documentation Reading and manipulaing satellite sensor spectral responses and the solar spectrum, to perform various corrections to VIS and NIR band data. . Given a passive sensor on a meteorological satellite PySpectral provides the relative spectral response (rsr) function(s) and offer 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. . This package includes the PySpectral documentation in HTML format.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pyspectral-doc
PackageSectiondoc
PackageVersion0.9.5+ds-1
SHA-1F61CB72C7D632608CE97620655AF2224E0181A21
SHA-256567BE85DFAC42219A15E6A697CD8A6B88E08B0B344564A51AF08ECA88B18C07C