Benne Holwerda is an associate professor at the University of Louisville, and is a leading expert in astronomical source catalogues and object characterization. He has worked on several projects that involve galaxy morphology classification and characterization; the Spitzer Survey of Spiral Structure in Galaxies, the Galaxy and Mass Assembly survey and the GHOSTS survey which explore extremes of low surface brightness. He authored the application of galaxy morphometrics on HI images.
B. W. Holwerda's Galaxy Morphology is an excellent introduction to the quantitative methods that have been used and is geared to the era of large image databases and the sophisticated programs needed to analyse them. These databases cover a wide range of redshifts and morphology, from X-rays to radio waves. To analyse properly such material, it is essential to have effective ways of quantifying characteristics such as angular size, integrated brightness, and other aspects of galaxy structure. Astronomers have long sought ways of replacing visual morphological classes with quantitative representations that can be used to determine scaling relations and to evaluate the accuracy of models of galaxy structure and evolution. Parameters such as the Sersic index and nonparametric approaches such as the CAS system can be effective for quantitative morphology but still have limitations. The interplay between visual and quantitative classifications led to the idea of using machine-learning methods to classify galaxies. Holwerda covers all of these topics and much more. The book is suitable for a course on galaxies and is written for extragalactic astronomy students ""at any level"". Each chapter is accompanied by a 'Jupyter notebook' assignment and has a useful list of articles for further reading. Ron Buta, The Observatory, October 2022