Spectral response functions¶

A spectral response function (SRF) dataset provides tabulated values of the spectral response of a radiometric instrument. Eradiate’s built-in SRF datasets are managed by the data store (see Data guide introduction for details).

Format¶

Format xarray.Dataset (in-memory), NetCDF (storage)
Dimensions
- w: radiation wavelength
Coordinates (all dimension coordinates; when relevant, units are required and specified in the units metadata field)
- w float [length]
Data variables (when relevant, units are required and specified in the units metadata field)
- srf (w): spectral response function [dimensionless]
- srf_u (w): uncertainty on the srf data variable [dimensionless]

Naming convention¶

SRF data files are usually named {platform}-{instrument}-{band}.nc where:

platform identifies the platform (e.g. satellite’s name);
instrument identifies the instrument onboard the platform;
band specifies the spectral band.

For example, the spectral response function data set of the SLSTR instrument onboard Sentinel-3B and in the spectral band 5 has the identifier sentinel_3b-slstr-5.

Dataset index¶

Important

The following datasets are processed to minimize the amount of computation performed for parts of the spectrum that will result in a low contribution to the final measure. All data are also padded with a leading and trailing zero.

The default data processing method, which keeps the total integral of the SRF equal to at least 99.9% of that in the raw data, might still yield a dataset with long tails with values close to zero with a very low contribution to the final result. The data is regularly revisited and optimized based on feedback from the development team and users. We strongly advise users to visualize the SRF data before using them to make sure that the data are processed to their liking. If necessary, Eradiate ships an SRF processing toolbox (see Filter a spectral response function).

Raw data are also available, using a -raw suffix to the dataset ID (e.g. sentinel_3b-slstr-5-raw).

`sentinel_2a-msi`¶

`sentinel_2b-msi`¶

`sentinel_3a-olci`¶

`sentinel_3a-slstr`¶

`sentinel_3b-olci`¶

`sentinel_3b-slstr`¶

Spectral response functions¶

Format¶

Naming convention¶

Dataset index¶

`sentinel_2a-msi`¶

`sentinel_2b-msi`¶

`sentinel_3a-olci`¶

`sentinel_3a-slstr`¶

`sentinel_3b-olci`¶

`sentinel_3b-slstr`¶

`aqua-modis`¶

`terra-modis`¶

`jpss1-viirs`¶

`npp-viirs`¶

`metop_a-avhrr`¶

`metop_b-avhrr`¶

`metop_c-avhrr`¶

`metop_sg-metimage`¶

`msg1-seviri`¶

`msg2-seviri`¶

`msg3-seviri`¶

`msg4-seviri`¶

`mtg_i-fci`¶

`mtg_i-li`¶

`parasol-polder`¶

`proba_v-vegetation_left`¶

`proba_v-vegetation_center`¶

`proba_v-vegetation_right`¶

Spectral response functions¶

Format¶

Naming convention¶

Dataset index¶

sentinel_2a-msi¶

sentinel_2b-msi¶

sentinel_3a-olci¶

sentinel_3a-slstr¶

sentinel_3b-olci¶

sentinel_3b-slstr¶

aqua-modis¶

terra-modis¶

jpss1-viirs¶

npp-viirs¶

metop_a-avhrr¶

metop_b-avhrr¶

metop_c-avhrr¶

metop_sg-metimage¶

msg1-seviri¶

msg2-seviri¶

msg3-seviri¶

msg4-seviri¶

mtg_i-fci¶

mtg_i-li¶

parasol-polder¶

proba_v-vegetation_left¶

proba_v-vegetation_center¶

proba_v-vegetation_right¶

`sentinel_2a-msi`¶

`sentinel_2b-msi`¶

`sentinel_3a-olci`¶

`sentinel_3a-slstr`¶

`sentinel_3b-olci`¶

`sentinel_3b-slstr`¶

`aqua-modis`¶

`terra-modis`¶

`jpss1-viirs`¶

`npp-viirs`¶

`metop_a-avhrr`¶

`metop_b-avhrr`¶

`metop_c-avhrr`¶

`metop_sg-metimage`¶

`msg1-seviri`¶

`msg2-seviri`¶

`msg3-seviri`¶

`msg4-seviri`¶

`mtg_i-fci`¶

`mtg_i-li`¶

`parasol-polder`¶

`proba_v-vegetation_left`¶

`proba_v-vegetation_center`¶

`proba_v-vegetation_right`¶