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Technology --- Contamination (Technology) --- Equipment Contamination. --- Environmental Pollution. --- Risk Management. --- Safety Management. --- Hazard Analysis and Critical Control Points. --- Material Safety Data Sheets. --- Contamination --- Technologie --- Salles blanches --- Risk assessment. --- prévention. --- Évaluation du risque. --- mesures de sécurité.

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Handbook for Laboratory Safety provides insights into what you should expect when you enter a laboratory, along with how to behave in these specialized work environments. It is a practical book that can be used as a general introduction to laboratory safety, but also works as a resource for employees or students who do laboratory work. Students could carry this book in their backpack, whereas university/institute/company laboratories could place the book in every laboratory as a reference. This book is also ideally suited for essential courses for students, (new) employees or laboratory technicians who are starting their work in a laboratory environment.

Laboratories --- Chemical laboratories --- Safety measures. --- Laboratory facilities --- Research buildings --- Science laboratories --- Scientific laboratories --- Science rooms and equipment --- Laboratories. --- Laboratory Chemicals. --- Chemical Safety. --- Hazard Analysis and Critical Control Points --- Chemical Safety Measures --- Chemical Safety Measure --- Measure, Chemical Safety --- Measures, Chemical Safety --- Safety Measure, Chemical --- Safety Measures, Chemical --- Safety, Chemical --- Chemicals, Laboratory --- Clinical Laboratory Services --- Laboratory --- Medical laboratories. --- Laboratory Chemicals --- Chemical Safety --- Safety

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The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites.The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained.More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products.This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry.

Technology: general issues --- unmanned aerial vehicle --- urban LULC --- GEOBIA --- multiscale classification --- unmanned aircraft system (UAS) --- deep learning --- super-resolution (SR) --- convolutional neural network (CNN) --- generative adversarial network (GAN) --- structure-from-motion --- photogrammetry --- remote sensing --- UAV --- 3D-model --- surveying --- vertical wall --- snow --- remotely piloted aircraft systems --- structure from motion --- lidar --- forests --- orthophotography --- construction planning --- sustainable construction --- urbanism --- BIM --- building maintenance --- unmanned aerial vehicle (UAV) --- structure-from-motion (SfM) --- ground control points (GCP) --- accuracy assessment --- point clouds --- corridor mapping --- UAV photogrammetry --- terrain modeling --- vegetation removal --- unmanned aerial vehicles --- power lines --- image-based reconstruction --- 3D reconstruction --- unmanned aerial systems --- time series --- accuracy --- reproducibility --- orthomosaic --- validation --- drone --- GNSS RTK --- precision --- elevation --- multispectral imaging --- vegetation indices --- nutritional analysis --- correlation --- optimal harvest time --- UAV images --- monoscopic mapping --- stereoscopic plotting --- image overlap --- optimal image selection --- n/a

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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.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. 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, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.

LiDAR --- RetinaNet --- inception --- Mobile Laser Scanning --- point clouds --- data fusion --- Lidar --- point cloud density --- point cloud coverage --- mobile mapping systems --- 3D simulation --- Pandar64 --- Ouster OS-1-64 --- mobile laser scanning --- lever arm --- boresight angles --- plane-based calibration field --- configuration analysis --- accuracy --- controllability --- evaluation --- control points --- TLS reference point clouds --- visual–inertial odometry --- Helmert variance component estimation --- line feature matching method --- correlation coefficient --- point and line features --- mobile mapping --- manhole cover --- point cloud --- F-CNN --- transfer learning --- CAM localization --- loop closure detection --- visual SLAM --- semantic topology graph --- graph matching --- CNN features --- deep learning --- view planning --- imaging network design --- building 3D modelling --- path planning --- V-SLAM --- real-time --- guidance --- embedded-systems --- 3D surveying --- exposure control --- photogrammetry --- parking statistics --- vehicle detection --- robot operating system --- 3D camera --- RGB-D --- performance evaluation --- convolutional neural networks --- smart city --- georeferencing --- MSS --- IEKF --- DSIEKF --- geometrical constraints --- 6-DoF --- DTM --- 3D city model --- dataset --- laser scanning --- 3D mapping --- synthetic --- outdoor --- semantic --- scene completion

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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.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. 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, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.

Technology: general issues --- History of engineering & technology --- LiDAR --- RetinaNet --- inception --- Mobile Laser Scanning --- point clouds --- data fusion --- Lidar --- point cloud density --- point cloud coverage --- mobile mapping systems --- 3D simulation --- Pandar64 --- Ouster OS-1-64 --- mobile laser scanning --- lever arm --- boresight angles --- plane-based calibration field --- configuration analysis --- accuracy --- controllability --- evaluation --- control points --- TLS reference point clouds --- visual–inertial odometry --- Helmert variance component estimation --- line feature matching method --- correlation coefficient --- point and line features --- mobile mapping --- manhole cover --- point cloud --- F-CNN --- transfer learning --- CAM localization --- loop closure detection --- visual SLAM --- semantic topology graph --- graph matching --- CNN features --- deep learning --- view planning --- imaging network design --- building 3D modelling --- path planning --- V-SLAM --- real-time --- guidance --- embedded-systems --- 3D surveying --- exposure control --- photogrammetry --- parking statistics --- vehicle detection --- robot operating system --- 3D camera --- RGB-D --- performance evaluation --- convolutional neural networks --- smart city --- georeferencing --- MSS --- IEKF --- DSIEKF --- geometrical constraints --- 6-DoF --- DTM --- 3D city model --- dataset --- laser scanning --- 3D mapping --- synthetic --- outdoor --- semantic --- scene completion --- LiDAR --- RetinaNet --- inception --- Mobile Laser Scanning --- point clouds --- data fusion --- Lidar --- point cloud density --- point cloud coverage --- mobile mapping systems --- 3D simulation --- Pandar64 --- Ouster OS-1-64 --- mobile laser scanning --- lever arm --- boresight angles --- plane-based calibration field --- configuration analysis --- accuracy --- controllability --- evaluation --- control points --- TLS reference point clouds --- visual–inertial odometry --- Helmert variance component estimation --- line feature matching method --- correlation coefficient --- point and line features --- mobile mapping --- manhole cover --- point cloud --- F-CNN --- transfer learning --- CAM localization --- loop closure detection --- visual SLAM --- semantic topology graph --- graph matching --- CNN features --- deep learning --- view planning --- imaging network design --- building 3D modelling --- path planning --- V-SLAM --- real-time --- guidance --- embedded-systems --- 3D surveying --- exposure control --- photogrammetry --- parking statistics --- vehicle detection --- robot operating system --- 3D camera --- RGB-D --- performance evaluation --- convolutional neural networks --- smart city --- georeferencing --- MSS --- IEKF --- DSIEKF --- geometrical constraints --- 6-DoF --- DTM --- 3D city model --- dataset --- laser scanning --- 3D mapping --- synthetic --- outdoor --- semantic --- scene completion