Table information for 'gaia_dem.epn_core'

General

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

Resource Description: GAIA-DEM
GAIA-DEM is a database of Differential Emission Measure (DEM) maps. The DEM is a measure of the thermal structure of the coronal plasma, representing the quantity of light emitting plasma along the line of sight, at different temperatures. In GAIA-DEM, the DEM is modelled by a specific function of temperature, namely a Gaussian of the logarithm of electron temperature. GAIA-DEM maps are then maps of the DEM maximum temperature, of the DEM integral (total Emission Measure), and DEM width (in temperature). These maps are obtained by inversion from the SDO/AIA EUV images in 6 coronal channels (9.4, 13.1, 17.1, 19.3, 21.1, and 33.5 nm). In addition, maps of the χ² for the inversion are provided.
GAIA-DEM is available from a specific interface at http://medoc-dem.ias.u-psud.fr, as well as part of the generic MEDOC interface which is currently located at https://idoc-medoc.ias.u-psud.fr. These interfaces are based on the CNES SiTools2 framework. GAIA-DEM is also available from IDL and Python scripts, using a specialization of the generic SiTools2 IDL and Python clients developed by MEDOC.

For a list of all services and tables belonging to this table's resource, see Information on resource 'SDO GAIA-DEM'

Resource Reference URL: https://idoc-medoc.ias.u-psud.fr

Citing this table

@MISC{vo:gaia_dem_epn_cor,
  year=2018,
  title={{SDO} {GAIA}-{DEM}},
  author={{IDOC}: Integrated Data and Operating Center},
  url={https://idoc-dachs.ias.u-psud.fr/tableinfo/gaia_dem.epn_core},
  howpublished={{VO} resource provided by the {IDOC}: Integrated Data and Operating Center}
}

Columns

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Columns that are parts of indices are marked like this.

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, traverses…

  pf -- photometric profile

  scalar or vectorial measurements along 1 angular dimension, e.g., phase or polarization curves, phase functions, emission-phase function sequences… typically associated to variations in illumination angle parameters.

  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… It is good practice to describe the type of data included in the catalogue using a hash-separated-list (e.g., a table of spectra should be described by ca#sp, so that it will respond to a query for spectra).

  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.

  sv -- spatial vector

  vector information associated to localization, such as spatial footprints or a GIS-related element. This could contain a kml or geojson file (STC-S strings are provided though the s_region parameter, though). This includes maps of vectors, e.g., wind maps.

  ev -- event

  individual events, typically formatted in VOEvent. Characteristics are provided via the event_* parameters.

• Note et_cal

  CODMAC levels are:

  1 -- raw

  2 -- edited

  3 -- calibrated

  4 -- resampled

  5 -- derived

  6 -- ancillary

Copyright and such: This research has been made at MEDOC