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We present a catalog of $\sim$52,000 extragalactic HII regions and their spectroscopic properties obtained using Integral Field Spectroscopy (IFS) from MUSE observations. The sample analyzed in this study contains 678 galaxies within the nearby Universe (0.004 < z < 0.06) covering different morphological types and a wide range of stellar masses (6 < log(M$_{*}$/M$_{\odot}$) < 13). Each galaxy was analyzed using the Pipe3D and pyHIIextractor codes to obtain information of the ionized gas and underlying stellar populations. Specifically, the fluxes, equivalent widths, velocities and velocity dispersions of 30 emission lines covering the wavelength range between $\lambda$4750A to $\lambda$9300A, were extracted and were used to estimate luminosity weighted ages and metallicities of the underlying stellar populations from each HII region (of the original sample we detect HII regions in 539 galaxies). In addition, we introduce and apply a novel method and independent of any intrinsic physical property to estimate and decontaminate the contribution of the diffuse ionized gas. Using the final catalog, we explore the dependence of properties of the HII regions on different local and global galaxy parameters: (i) Hubble type, (ii) stellar mass, (iii) galactocentric distance, and (iv) the age and metallicity of the underlying/neighbour stellar populations. We confirm known relations between properties of the HII regions and the underlying stellar populations (in particular with the age) uncovered using data of lower spatial and spectral resolution. Furthermore, we describe the existence of two main families of diffuse ionized gas different for galaxies host or not of HII region, Comment: Submitted for publishing in MNRAS, 2O pages, 13 figures

Using the largest sample of galaxies observed with an optical integral field unit (IFU, the SDSS-IV MaNGA survey, $\sim$10000 targets), we derive the radial distribution of the physical properties obtained from the stellar continuum and the ionized-gas emission lines. Given the large sample, we are able to explore the impact of the total stellar mass and morphology by averaging those radial distributions for different bins of both global properties. We use a piece-wise analysis to characterize the slopes of the gradients from those properties at different galactocentric distances. In general we find that most of the properties -- derived from both the stellar continuum and the ionized gas emission lines -- exhibit a negative gradient with a secondary impact by global properties such as the total stellar mass or morphology. Our results confirm the intimate interplay between the properties of the stellar component and those of the ionized gas at local (kpc) scales in order to set the observed gradients. Furthermore, the resemblance of the gradients for similar global properties (in particular for the stellar parameters) indicates statistical similar histories of star formation and chemical enrichment with an initial radial gas distribution following the potential of the galaxy., Comment: 58 pages. 59 Figures. Submitted to the RMxAA

We present a new code named pyHIIextractor, which detects and extracts the main features (positions and radii) of clumpy ionized regions, i.e. candidate HII regions, using H{\alpha} emission line images. Our code is optimized to be used on the dataproducts provided by the Pipe3D pipeline (or dataproducts with such a format), applied to high spatial resolution Integral Field Spectroscopy data (like that provided by the AMUSING++ compilation, using MUSE). The code provides the properties of both the underlying stellar population and the emission lines for each detected H ii candidate. Furthermore, the code delivers a novel estimation of the diffuse ionized gas (DIG) component, independent of its physical properties, which enables a decontamination of the properties of the HII regions from the DIG. Using simulated data, mimicking the expected observations of spiral galaxies, we characterise pyHIIextractor and its ability to extract the main properties of the H ii regions (and the DIG), including the line fluxes, ratios and equivalent widths. Finally, we compare our code with other such tools adopted in the literature, which have been developed or used for similar purposes: pyhIIexplorer, SourceExtractor, HIIphot, and astrodendro. We conclude that pyHIIextractor exceeds the performance of previous tools in aspects such as the number of recovered regions and the distribution of sizes and fluxes (an improvement that is especially noticeable for the faintest and smallest regions). pyHIIextractor is therefore an optimals tool to detect candidate HII regions, offering an accurate estimation of their properties and a good decontamination of the DIG component., Comment: Submitted for publishing in RASTI, 26 pages, 14 figures