The IGAPS Photometric Catalogue

Key properties

  • Isaac Newton Telescope (⌀ 2.5m)
  • La Palma, Canary Islands
  • Wide Field Camera (0.3 deg2)
  • Four 2048 x 4100 pixel CCD's
  • 0.33 arcsec / pixel
  • Filters: i, Hα, r, g and URGO
  • Saturation: 12 (i), 12.5 (Hα), 13 (r and g), 12 (URGO)
  • Depth: 20 (i), 20 (Hα), 21 (r), 22 (g) and 21 (URGO)
  • Median seeing: 1.1 arcsec
  • Survey area: 1850 deg2
  • Footprint: |b| < 5°, l = 30-215°
  • Observing period: 2003 - 2018
  • Reference: Monguio et al. 2020

This IGAPS release supersedes IPHAS Data Release 2 (DR2, 219 million unique sources) and is the first release of UVEX data, taking the total number of unique sources up to 295 million. Past practice is continued in that the default magnitude system is the Vega system but additional catalogue columns give their AB equivalents. The i, Hα, r and g photometry has passed through a process of uniform calibration, using the overlapping Pan-STARRS r, i and g data as reference.

For each source, the catalogue provides magnitudes measured using a series of circular apertures, along with coordinates, morphology information, and quality warning flags. This page details how the data may be accessed, points to a table detailing the column definitions, comments on how to optimise data quality , and finally provides a FAQ which addresses common caveats.

Online queries

The easiest way to retrieve data from the catalogue is to use the Vizier data portal, which hosts a full copy of the catalogue and allows excerpts from the catalogue to be downloaded in various formats, including html, ascii and fits. To use this service, please head to the Vizier IGAPS page at:

http://vizier.u-strasbg.fr/viz-bin/VizieR?-source=V/165&-to=3

You can also query the Vizier service in an automated fashion using their conesearch API. For example, to download and save all the sources located within a 0.1° radius around (RA, Dec) = (324°, 58°), you can use the following Python script:

from astropy.vo.client.conesearch import conesearch
search = conesearch(center=(324.0, 58.0),
                    radius=0.1,
                    verb=3,
                    catalog_db="http://vizier.u-strasbg.fr/viz-bin/votable/-A?-source=V/165&-out.all&")
search.to_table().write('igaps-data.fits', format='fits')

Note that the script above requires the AstroPy package to be installed.

Downloading a full copy

The catalogue is also made available for download as a series of binary FITS tables, each covering a 5x5 deg2 area of the survey. You may download all these tiles to a local directory using the following wget command:

wget -c -r -np -nH --cut-dirs=3 --accept=fits.gz http://www.star.ucl.ac.uk/IGAPS/data/catalogue/full/

Be aware that the full size of the gzipped catalogue is 98 GB (unzipped this becomes 256 GB).

You may also download individual 5x5 deg2 tiles using the links provided in the table below:

Gal. Lon. b < 0° b > 0°
l < 30° igaps-dr1-025a.fits.gz (0.3 GB) igaps-dr1-025b.fits.gz (0.2 GB)
30° ≤ l < 35° igaps-dr1-030a.fits.gz (4.0 GB) igaps-dr1-030b.fits.gz (3.8 GB)
35° ≤ l < 40° igaps-dr1-035a.fits.gz (3.2 GB) igaps-dr1-035b.fits.gz (1.5 GB)
40° ≤ l < 45° igaps-dr1-040a.fits.gz (2.6 GB) igaps-dr1-040b.fits.gz (2.8 GB)
45° ≤ l < 50° igaps-dr1-045a.fits.gz (2.8 GB) igaps-dr1-045b.fits.gz (3.5 GB)
50° ≤ l < 55° igaps-dr1-050a.fits.gz (3.2 GB) igaps-dr1-050b.fits.gz (2.5 GB)
55° ≤ l < 60° igaps-dr1-055a.fits.gz (3.2 GB) igaps-dr1-055b.fits.gz (3.2 GB)
60° ≤ l < 65° igaps-dr1-060a.fits.gz (2.1 GB) igaps-dr1-060b.fits.gz (3.9 GB)
65° ≤ l < 70° igaps-dr1-065a.fits.gz (1.7 GB) igaps-dr1-065b.fits.gz (3.7 GB)
70° ≤ l < 75° igaps-dr1-070a.fits.gz (1.5 GB) igaps-dr1-070b.fits.gz (2.9 GB)
75° ≤ l < 80° igaps-dr1-075a.fits.gz (1.3 GB) igaps-dr1-075b.fits.gz (1.6 GB)
80° ≤ l < 85° igaps-dr1-080a.fits.gz (1.2 GB) igaps-dr1-080b.fits.gz (0.9 GB)
85° ≤ l < 90° igaps-dr1-085a.fits.gz (1.9 GB) igaps-dr1-085b.fits.gz (1.4 GB)
90° ≤ l < 95° igaps-dr1-090a.fits.gz (1.6 GB) igaps-dr1-090b.fits.gz (0.9 GB)
95° ≤ l < 100° igaps-dr1-095a.fits.gz (1.6 GB) igaps-dr1-095b.fits.gz (1.5 GB)
100° ≤ l < 105° igaps-dr1-100a.fits.gz (1.6 GB) igaps-dr1-100b.fits.gz (1.4 GB)
105° ≤ l < 110° igaps-dr1-105a.fits.gz (1.4 GB) igaps-dr1-105b.fits.gz (1.0 GB)
110° ≤ l < 115° igaps-dr1-110a.fits.gz (0.9 GB) igaps-dr1-110b.fits.gz (0.9 GB)
115° ≤ l < 120° igaps-dr1-115a.fits.gz (1.1 GB) igaps-dr1-115b.fits.gz (1.0 GB)
120° ≤ l < 125° igaps-dr1-120a.fits.gz (1.2 GB) igaps-dr1-120b.fits.gz (0.9 GB)
125° ≤ l < 130° igaps-dr1-125a.fits.gz (1.1 GB) igaps-dr1-125b.fits.gz (1.0 GB)
130° ≤ l < 135° igaps-dr1-130a.fits.gz (0.9 GB) igaps-dr1-130b.fits.gz (1.0 GB)
135° ≤ l < 140° igaps-dr1-135a.fits.gz (0.8 GB) igaps-dr1-135b.fits.gz (0.8 GB)
140° ≤ l < 145° igaps-dr1-140a.fits.gz (0.6 GB) igaps-dr1-140b.fits.gz (0.6 GB)
145° ≤ l < 150° igaps-dr1-145a.fits.gz (0.6 GB) igaps-dr1-145b.fits.gz (0.7 GB)
150° ≤ l < 155° igaps-dr1-150a.fits.gz (0.6 GB) igaps-dr1-150b.fits.gz (0.6 GB)
155° ≤ l < 160° igaps-dr1-155a.fits.gz (0.6 GB) igaps-dr1-155b.fits.gz (0.7 GB)
160° ≤ l < 165° igaps-dr1-160a.fits.gz (0.7 GB) igaps-dr1-160b.fits.gz (0.7 GB)
165° ≤ l < 170° igaps-dr1-165a.fits.gz (0.6 GB) igaps-dr1-165b.fits.gz (0.8 GB)
170° ≤ l < 175° igaps-dr1-170a.fits.gz (0.6 GB) igaps-dr1-170b.fits.gz (0.6 GB)
175° ≤ l < 180° igaps-dr1-175a.fits.gz (0.6 GB) igaps-dr1-175b.fits.gz (0.7 GB)
180° ≤ l < 185° igaps-dr1-180a.fits.gz (0.6 GB) igaps-dr1-180b.fits.gz (0.7 GB)
185° ≤ l < 190° igaps-dr1-185a.fits.gz (0.6 GB) igaps-dr1-185b.fits.gz (0.7 GB)
190° ≤ l < 195° igaps-dr1-190a.fits.gz (0.6 GB) igaps-dr1-190b.fits.gz (0.7 GB)
195° ≤ l < 200° igaps-dr1-195a.fits.gz (0.7 GB) igaps-dr1-195b.fits.gz (0.7 GB)
200° ≤ l < 205° igaps-dr1-200a.fits.gz (0.8 GB) igaps-dr1-200b.fits.gz (0.7 GB)
205° ≤ l < 210° igaps-dr1-205a.fits.gz (0.6 GB) igaps-dr1-205b.fits.gz (0.6 GB)
210° ≤ l < 215° igaps-dr1-210a.fits.gz (0.7 GB) igaps-dr1-210b.fits.gz (0.5 GB)
215° ≤ l igaps-dr1-215a.fits.gz (67 MB) igaps-dr1-215b.fits.gz (43 MB)

The full list of the 174 catalogue columns and their definitions is available as an appendix in the catalogue paper. This is reproduced as a cut-out pdf here.

Like its predecessor, IPHAS DR2, this catalogue release includes a range of user-friendly quality warning flags. These are necessary because the catalogue includes any source detected at a signal-to-noise ratio of just 5 or better in any band. Many applications will require a combination of quality criteria to be applied to exclude low-significance, saturated, or confused photometry. The choice of quality criteria inevitably tensions completeness against reliability, and must depend on the user's needs.

The new catalogue discontinues the "a10" and "a10point" columns of IPHAS DR2, because of the added complexity of incorporating the UVEX bands. However every band detection continues to be accompanied by a set of flags and measures designed to assist informed selection.

Use of the errbits column

The errbits column (and errbits2 for the second detection) is the one column that provides an overview of source detection quality. The entry for each source is a number that increases according to the severity of the total accumulation of flagged problems. This means that objects - for which there are no flagged problems in any band - return an errbits value of 0. The table below identifies the numerical value attached to each class of problem. Note that when a source is affected by more than one issue, the final errbits value in the catalogue will be the sum of the associated counts: for example a source showing blending in one (or more) bands that is also close to a bright star will have errbits = 3 (= 2+1).

Because errbits is sensitive to issues picked up in any band detection, a limitation on its use is that it becomes 'pessimistic' for applications where the quality of detection in a subset of filters is the only concern. For example, the user relying on errbits to select good r, i and Hα detections will omit sources falling on the g-filter blemish (rendering errbits > 16), even when r, i and Hα are clear of problems. In such cases, the optimal selection will be based on testing a basket of individual-filter flags and/or measurements.

Errbits count Meaning of count
1 A bright star is nearby and may affect photometry quality. Will be more of an issue for relatively faint sources.
2 In one or more bands the pipeline encountered blending with a neighbouring source.
4 Source close to or on a linear artefact (satellite trail or saturation spike)
8 Saturation flag raised for one or more bands
16 In the g band, the source is in the outer masked zone
64 Vignetting affects one or more bands
128 In the g band the source is in the inner masked zone
256 The source PSF is truncated in one or more bands
32768 Bad pixels are located within the source PSF in one or more bands

This large file contains an interim processing of VPHAS+ data, aimed at supporting WEAVE survey target selection. It covers Galactic longitudes from 24 to north of the celestial equator (IGAPS overlap), down to an r magnitude of 19th.

WEAVE_vphas_data_rlt19.fits (1.2 GB)

Read the frequently asked questions below to learn more about the catalogue and its modes of use: (answers to be rewritten)

Does IGAPS provide variability information?

Both the IPHAS and UVEX surveys included exposures in the r band, with the result that there are usually two r band detections available per source, obtained a few years apart. Where the two primary r magnitudes reported in the catalogue are the same to within likely errors, it should be safe to assume that colours formed by combining IPHAS and UVEX filter magnitudes are sound. In many cases second detections are available. These will often (but not always) have been evaluated as lower in quality than the primary detections. In some circumstances, they can add more information about variability. However in many instances the secondary detection will be selected from the exposure set partnering the primary detection exposure set, with the result that the time difference between the primary and secondary IPHAS/UVEX detections will be about 5 minutes.

Multi-epoch data for a source can also be obtained by querying the image database, or by mining the full set of field-by-field catalogues. Some fields were repeated many times to bring the overall data quality up to survey standard. These alternate resources allow essentially all the observations collected to be accessed.

Why are some stars classified as galaxies or noise?

The morphological classification values (e.g. iClass, haClass) are determined by comparing the point spread function (PSF) of a source against the mean shape of the PSF measured across the CCD. Where 0 is returned as the morphological class, caution is needed as it indicates noise-like properties. This is not so common.

It is much more common for stars to be incorrectly flagged as extended objects (class +1) because the PSF deviates from the mean for a different reason. For example, this may affect stars which are (i) very faint, (ii) have a nearby neighbour, (iii) are located in a nebulous region, or (iv) fall near the edge of the focal plane. The band-merged morphological information, mergedClass, provides a shortcut to identifying objects that are uniformly classified as star-like (-1), or galaxy-like (+1), or noise (0). A mergedClass value of 99 implies a mix of morphological classes across the different bands. When in doubt and when it matters, we recommend by-eye inspection of the relevant images.

How do I obtain photometry for extended sources?

The photometry in the catalogue is derived on the assumption that the source in aperture is a point source, which involves correction for the flux in the tail of the PSF that is otherwise lost outside of the reasonably small aperture applied to each source. To enable the analysis of diffuse sources, our website provides access to the pipeline-processed imaging data. In many cases (not all), these have been updated to include IGAPS re-calibrated zeropoints (header keyword PHOTZP). The information required to convert the image data into fluxes is provided at www.igapsimages.org/images.

How do I access the image data for a source?

Images may be downloaded directly from our server. In brief, each image is uniquely identified by the combination of its run number and CCD number, which are encoded within the detection identifiers (catalogue columns iDetectionID, haDetectionID etc). For example, the r-band image for a source with rDetectionID equal to "570144-1-9999" (#run-#ccd-#source) is located at:

http://www.igapsimages.org/data/images/r570/r570144-1.fits.fz

For more documentation on image access, please visit www.igapsimages.org/images.

How accurate is the astrometry?

The astrometric solution for IGAPS has been placed in the Gaia DR2 reference frame. This is a change relative to IPHAS DR2 where the reference used was 2MASS. The Root Mean Square (RMS) residuals of the astrometric fits in g, r, i and H&\lpha; are generally We warn however that the residuals of individual stars, e.g. near CCD corners,can occasionally exceed 0.5 arcsec, even when the RMS is below 0.1 arcsec.

What software was used to produce the catalogue?

The images were pipeline-processed by the Cambridge Astronomy Survey Unit using the CASUTOOLS software package. Next, the single-band detection tables produced in Cambridge were homogeneously re-calibrated and band-merged by members of the IPHAS team using a custom-built Python package, which is available on GitHub in the spirit of reproducibility.

How do I reference IGAPS and this catalogue in my papers?

Publications arising from IGAPS image data should cite and acknowledge the survey and the data release, according to mode of use. The primary reference for defining IPHAS is Drew et al 2005 [bibtex]. For UVEX, the reference is Groot et al 2009 [bibtex]. The reference for the IGAPS catalogue is Monguio et al 2020 [bibtex].

Here is text that can be used in acknowledgment sections of papers:

This paper makes use of data obtained as part of the INT Galactic Plane Surveys (IGAPS, www.igapsimages.org) carried out at the Isaac Newton Telescope (INT). The INT is operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. All IGAPS data were processed by the Cambridge Astronomical Survey Unit, at the Institute of Astronomy in Cambridge. The IGAPS catalogue was assembled using the high-performance computing cluster available at the Centre for Astrophysics Research, University of Hertfordshire.