Table information for 'das2meudon.epn_core'

General

This table is available for ADQL queries and through the TAP endpoint.

Resource Description: Das2 Server Meudon database.

For a list of all services and tables belonging to this table's resource, see Information on resource 'Das2 Server Meudon Database'

Citing this table

@MISC{vo:das2meudon_epn_core,
  year=2017,
  title={Das2 Server Meudon Database},
  author={Baptiste Cecconi},
  url={http://voparis-cdpp.obspm.fr/tableinfo/das2meudon.epn_core},
  howpublished={{VO} resource provided by the {PADC} {TAP} Server on voparis-cdpp.obspm.fr}
}

Fields

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Columns that are parts of indices are marked like this.

Other

VOResource

VO nerds may sometimes need VOResource XML for this table.

Notes

• Note et_prod

  The following values are defined for this field:

  im -- image

  associated scalar fields with two spatial axes, e.g., images with multiple color planes like from multichannel or filter cameras. Preview images (e.g. map with axis and caption) also belong here. Conversely, all vectorial 2D fields are described as catalogue (see below).

  ma -- map

  scalar field/rasters with two spatial axes covering a large area and projected either on the sky or on a planetary body, associated to a Projection parameter (with a short enumerated list of possible values). This is mostly intended to identify complete coverages that can be used as reference basemaps

  sp-- spectrum

  measurements organized primarily along a spectral axis, e.g., radiance spectra. This includes spectral aggregates (series of related spectra with non-connected spectral ranges, e.g., from several channels of the same instrument

  ds -- dynamic_spectrum

  consecutive spectral measurements through time, organized as a time series. This typically implies successive spectra of the same target or field of view.

  sc -- spectral_cube

  sets of spectral measurements with 1 or 2 D spatial coverage, e.g., imaging spectroscopy. The choice between Image and spectral_cube is related to the characteristics of the instrument (which dimension is most resolved and which dimensions are acquired simultaneously). The choice between dynamic_spectrum and spectral_cube is related to the uniformity of the field of view.

  pr -- profile

  scalar or vectorial measurements along 1 spatial dimension, e.g., atmospheric profiles, atmospheric paths, sub-surface profiles…

  vo -- volume

  other measurements with 3 spatial dimensions, e.g., internal or atmospheric structures, including shells/shape models (3D surfaces).

  mo -- movie

  sets of chronological 2 D spatial measurements.

  cu -- cube

  multidimensional data with 3 or more axes, e.g., all that is not described by other 3 D data types such as spectral cubes or volume. This is mostly intended to accommodate unusual data with multiple dimensions.

  ts -- time_series

  measurements organized primarily as a function of time (with exception of dynamical spectra and movies, i.e. usually a scalar quantity). Typical examples of time series include space-borne dust detector measurements, daily or seasonal curves measured at a given location (e.g., a lander), and light curves.

  ca -- catalog

  applies to a single granule providing a list of events, a catalog of object parameters, a list of features… Spatial vectors (e.g., vector information from a GIS, spatial footprints…) belong here. This is relevant, e. g., for collections of vectorial elements (e.g., crater lists or ROI definitions) which can be handled directly in a specialized environment such as a GIS. This includes maps of vectors, e.g., wind maps.

  ci -- catalogue_item

  applies when the service itself provides a catalogue, with entries described as individual granules. The service can be, e.g., a list of asteroid properties or spectral lines. Catalogue_item can be limited to scalar quantities (including strings), and possibly to a single element. This organization allows the user to search inside the catalogue from the TAP query interface.

• Note et_cal

  CODMAC levels are:

  1 -- raw

  2 -- edited

  3 -- calibrated

  4 -- resampled

  5 -- derived

  6 -- ancillary

Copyright and such: For any data re-use or publication authors must acknowledge support from the University of Iowa, from LESIA (Observatoire de Paris-CNRS) and CNRS. The Cassini/Kronos website (http://lesia.obspm.fr/kronos) must also be cited, as well as this server, developed with support of Europlanet-H2020-RI/VESPA.
The Europlanet H2020 Research Infrastructure project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654208.

Prior to any publication, we recommend to contact the Cassini/Kronos team at LESIA.


This data is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.