ner_tags: O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O B-Wavelength O O O O B-Wavelength O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject B-Citation I-Citation I-Citation O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O B-Wavelength B-Wavelength O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O B-Wavelength O B-Wavelength I-Wavelength O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O B-Survey I-Survey I-Survey I-Survey B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O B-Survey O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O
tokens: of the star formation rate (SFR) density of the universe with time and stellar mass (e.g. Brinchmann et al. 2004 ; Bauer et al. 2005 ; Feulner et al. 2005 ; Noeske et al. 2007 ; Zheng et al. 2007 ; Chen et al. 2009 ). The Hα, [O ii ] , ultraviolet–optical spectral energy distribution fitting and infrared photometry are commonly used to estimate the SFR at different redshifts. Two major conclusions of these studies are as follows: (1) the comoving SFR density of the universe has declined by an order of magnitude since z ∼ 2 (Hopkins et al. 2006 ); (2) the SFR per unit stellar mass (SSFR) depends on both stellar mass and redshift, with massive galaxies forming most of their stars earlier than less massive systems (Heavens et al. 2004 ; Thomas et al. 2005 ). To fully understand galaxy formation and evolution, it is important to understand both how the population as a whole evolves and how SFR within individual galaxies evolves. A first step is looking at how SFR is distributed spatially in galaxies as a function of their physical parameters, such as stellar mass and environment. However, this is not an easy task, especially for high- z galaxies given their small angular size and faintness. The radial distribution of star formation in local galaxies has been analysed in individual galaxies (e.g. NGC 1566; Comte Duquennoy 1982 ) and samples of tens to hundreds of galaxies using narrow-band imaging centred on Hα which traces the ionizing photons produced by massive stars. Ryder Dopita ( 1994 ) studied the relative scalelengths of Hα, V -, and I -band emission in 34 S0-Sm galaxies, finding that the line emission had a larger scalelength than the continuum. James, Bretherton Knapen ( 2009 ) compared the Hα and R -band light profiles of 313 S0a-Im field galaxies, finding that the major central Hα deficit (relative to the continuum) happens in barred galaxies, particularly in early-type and hence high-mass barred galaxies (see also Nair Abraham 2010 ; Hakobyan et al. 2014 ). Statistical studies of larger volumes have so far been lacking due to the decrease in spatial resolution with distance, and the necessity of using multiple narrow-band filters to accommodate the redshifting of the Hα line. Sloan Digital Sky Survey (SDSS) provides the largest galaxy sample of photometry and spectra so far. It is a great data base to study all kinds of properties of local galaxies. Ge et al. ( 2012 ) select double-peaked narrow emission-line galaxy sample from SDSS DR7 and study their properties. However, due to the 3 arcsec diameter fibre, it is hard to derive any spatial information about the galaxies directly from the spectra. In this paper, we make the first attempt of getting spatial information from the structures of Hα emission lines in SDSS spectra. As we know, the Hα profile depends on the strength of emission at a given velocity, which is determined by the rotating curve and the Hα surface brightness distribution in a rotating disc. Thus, through comparing