**Preface to "Advances in Mobile Mapping Technologies"**

Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.

In order to address these topics, we edited the Special Issue Advances in Mobile Mapping Technologies for the *Remote Sensing* journal. This book contains the published articles of this Special Issue and is aimed at those in academia and industry alike. Specifically, it consists of works introducing a new mobile mapping dataset ('Paris CARLA 3D'), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We wish to thank all the authors who contributed to this collection.

> **Ville Lehtola, Andreas N ¨uchter, Fran¸cois Goulette** *Editors*
