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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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As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions. Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms. In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events. The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data.
mobile mapping system --- RRI model --- high-water marks --- inundation --- Northern Kyushu floods --- point clouds --- flood mapping --- temporary flooded vegetation (TFV) --- Sentinel-1 --- time series data --- Synthetic Aperture Radar (SAR) --- sentinel-1 --- SAR --- flood --- image classification --- clustering --- monsoon --- Philippines --- LiDAR --- geometric parameters --- levee stability --- overtopping --- Pearl River Delta --- CYGNSS --- flood detection --- Sistan and Baluchestan --- GNSS-R --- flood monitoring --- ALOS 2 --- multi-sensor integration --- multi-temporal inundation analysis --- Zambesi-Shire river basin --- image processing --- hydrology --- synthetic aperture radar --- n/a
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Each year, disasters such as storms, floods, fires, volcanoes, earthquakes, and epidemics cause thousands of casualties and tremendous damage to property around the world, displacing tens of thousands of people from their homes and destroying their livelihoods. The majority of these casualties and property loss could be prevented if better information were available regarding the onset and course of such disasters. Several remote sensing technologies, such as meteorological and Earth observation satellites, communication satellites, and satellite-based positioning, supported by geoinformation technologies, offer the potential to contribute to improved prediction and monitoring of potential hazards, risk mitigation, and disaster management which, in turn, would lead to sharp reductions in losses to life and property. This book explores most of the scientific issues related to spatially supported disaster management and its integration with geographical information system technologies in different disaster examples and scales. Dealing with disasters over space and time represents a long-lasting theme, now approached by means of innovative techniques and modelling approaches. Several priorities for actions are outlined toward preventing new and reduce existing disaster risks, including understanding disaster risk, strengthening disaster risk governance for management of disaster risk, investing in disaster reduction for resilience, and enhancing disaster preparedness for effective response. This book presents ideas to address the challenges facing different components of spatial patterns related to ecological processes, and the published articles extended versions of selected presentations from the Gi4DM Conference in 2019 in Prague.
mapping impact --- tidal flood --- hydrodynamic model --- solar salt farming --- drone --- computer vision --- point clouds --- machine learning --- CNN --- GAN --- first responder --- RECONASS --- INACHUS --- multi-hazard --- susceptibility mapping --- developing urban settlements --- landslide --- flood --- logistic regression --- Mamdani fuzzy algorithm --- M-AHP --- cartographic symbols --- map symbology --- crisis map --- comparative analysis --- taxonomy --- graphic design --- availability --- promulgation --- sharing --- standardisation --- Black sea --- sea level change --- tide gauge --- satellite altimetry --- GNSS --- post-fire management --- forest regeneration --- fire severity mapping --- multispectral imagery --- Sentinel-2A --- unmanned aerial vehicles --- Parrot SEQUOIA --- climate change --- fuzzy logic --- GIS, household --- Index method --- sea level rise --- vulnerability --- n/a
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Mobile Mapping technologies have seen a rapid growth of research activity and interest in the last years, due to the increased demand of accurate, dense and geo-referenced 3D data. Their main characteristic is the ability of acquiring 3D information of large areas dynamically. This versatility has expanded their application fields from the civil engineering to a broader range (industry, emergency response, cultural heritage...), which is constantly widening. This increased number of needs, some of them specially challenging, is pushing the Scientific Community, as well as companies, towards the development of innovative solutions, ranging from new hardware / open source software approaches and integration with other devices, up to the adoption of artificial intelligence methods for the automatic extraction of salient features and quality assessment for performance verification The aim of the present book is to cover the most relevant topics and trends in Mobile Mapping Technology, and also to introduce the new tendencies of this new paradigm of geospatial science.
LRF --- smartphone --- unmanned vehicle --- sensor fusion --- 2D laser scanner --- semantic enrichment --- Vitis vinifera --- indoor scenes --- terrestrial laser scanning --- vine size --- quadric fitting --- multi-group-step L-M optimization --- grammar --- MLS --- indoor topological localization --- trajectory fusion --- second order hidden Markov model --- room type tagging --- fingerprinting --- restoration --- laser scanning --- map management --- Lidar localization system --- point clouds --- binary vocabulary --- self-calibration --- 3D processing --- cultural heritage --- encoder --- category matching --- indoor mapping --- convolutional neural network (CNN) --- tunnel cross section --- visual positioning --- enhanced RANSAC --- segmentation-based feature extraction --- image retrieval --- handheld --- crowdsourcing trajectory --- visual landmark sequence --- indoor localization --- mobile mapping --- rapid relocation --- sensors configurations --- precision agriculture --- 3D digitalization --- mobile laser scanning --- robust statistical analysis --- plant vigor --- motion estimation --- visual simultaneous localization and mapping --- dynamic environment --- Bayesian inference --- automated database construction --- portable mobile mapping system --- SLAM --- small-scale vocabulary --- ORB-SLAM2 --- LiDAR --- IMMS --- point cloud --- optical sensors --- tunnel central axis --- constrained nonlinear least-squares problem --- 3D point clouds --- wearable mobile laser system --- geometric features --- 2D laser range-finder --- RGB-D camera --- OctoMap
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Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research.
Research & information: general --- street view --- remote sensing --- urban environmental elements --- ensemble learning --- green view --- sky view --- building view --- SHAP --- convolutional neural network --- water body extraction --- GaoFen-1 --- multiple scales --- deep learning --- Line Simplification --- Douglas-Peucker Algorithm --- Monotonic Chain --- Dichotomy --- vegetation --- partial correlation analysis --- trend prediction --- the source region of the Yellow River --- revetment --- damage signature --- dense point clouds --- unmanned aerial vehicle (UAV) --- gradient operator --- OpenStreetMap (OSM) --- road network density --- urban economy --- regression analysis --- spatial metric --- pre-hospital emergency --- spatiotemporal demand --- GPS data --- seasonal clustering --- short-term forecast --- tourism flow forecast --- optimization algorithm --- Random Forest --- landslide hazard risk --- integrated multisource dataset --- field sample rasterization --- weight assignment --- urban forest --- forest biomass --- biomass distribution --- geographic detector --- poverty probability --- random forest --- nighttime lights --- spatiotemporal characteristics --- geographic information systems --- land cover --- land dynamics --- regional studies --- sustainable planning --- ultra-peripheral territories --- fire station --- fire risk evaluation --- parcel-pickup lockers --- site-suitability analysis --- GIS-based --- bivariate logistic regression model --- suitability classification --- n/a
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This book includes 13 papers published in Special Issue ("Visual and Camera Sensors") of the journal Sensors. The goal of this Special Issue was to invite high-quality, state-of-the-art research papers dealing with challenging issues in visual and camera sensors.
self-assembly device --- 3D point clouds --- accuracy analysis --- VSLAM-photogrammetric algorithm --- portable mobile mapping system --- low-cost device --- BIM --- camera calibration --- DLT --- PnP --- weighted DLT --- uncertainty --- covariance --- robustness --- visual-inertial --- semi-direct SLAM --- multi-sensor fusion --- side-rear-view monitoring system --- automatic online calibration --- Hough-space --- unmanned aerial vehicle --- autonomous landing --- deep-learning-based motion deblurring and marker detection --- network slimming --- pruning model --- convolutional neural network --- convolutional filter --- classification --- multimodal human recognition --- blur image restoration --- DeblurGAN --- CNN --- facial expression recognition system --- computer vision --- multi-scale featured local binary pattern --- unsharp masking --- machine learning --- lens distortion --- DoF-dependent --- distortion partition --- vision measurement --- pathological site classification --- in vivo endoscopy --- computer-aided diagnosis --- artificial intelligence --- ensemble learning --- convolutional auto-encoders --- local image patch --- point pair feature --- plank recognition --- robotic grasping --- flying object detection --- drone --- image processing --- camera networks --- open-pit mine slope monitoring --- optimum deployment --- close range photogrammetry --- three-dimensional reconstruction --- OCD4M
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The Special Issue collects papers showing the progress made in key areas of photogrammetry and remote sensing such as modern and/or forthcoming sensors, improvements in data processing strategies and assessment of their reliability, application of innovations as proof of the contribution offered in the observation of the natural and built environment with better understanding of phenomena at required spatial scale.
VHR tri-stereo satellite imagery --- digital elevation model --- isolated objects --- dense image matching --- change detection --- natural disasters --- deep learning --- threshold selection --- optical flow estimation --- Structure from Motion (SfM) --- 3D reconstruction --- noise estimation --- point clouds --- roughness --- surface reconstruction --- mesh model --- visibility constraints --- volumetric methods --- dense point cloud --- multiple view stereo (MVS) --- dense image matching (DIM) --- photogrammetry --- computer vision --- Copernicus --- Sentinel-1 --- Sentinel-2 --- InSAR --- damage proxy map --- Beirut --- Lebanon --- explosion --- radiometric calibration --- modeling --- geometric error --- high-precision calibration --- n/a --- preprocessing --- enhancement --- point cloud --- image processing --- image histogram --- UAV --- camera calibration --- GNSS-assisted block orientation --- dome effect --- Monte Carlo simulation --- soil moisture content --- artificial neural network --- sample optimization --- synthetic aperture radar --- optical remote sensing image
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The energy transition is one of the key approaches in the effort to halt climate changes, and it has become even more essential in the light of the recent COVID-19 pandemic. Fostering the energy efficiency and the energy independence of the building sector is a focal aim to move towards a decarbonized society. In this context, building physics and building energy systems are fundamental disciplines based on applied physics applications in civil, architectural, and environmental engineering, including technical themes related to the planning of energy and the environment, diagnostic methods, and mitigating techniques. This Special Issue contains information on experimental studies in the following research topics: renewable energy sources, building energy analysis, rational use of energy, heat transmission, heating and cooling systems, thermofluid dynamics, smart energy systems, and energy service management in buildings.
LIDAR point clouds --- 3D urban model --- rooftop modeling --- segmentation --- reconstruction --- 3D building --- setting temperature of hot water --- solar cooling --- absorption chiller --- subcooled compression --- hybrid system --- 3D thermography --- thermal imaging --- laser scanning --- integration methodology --- extrinsic calibration --- decoupled acquisition --- heritage conservation --- green roof --- experimental investigation --- thermal performance --- measurements --- simulations --- India --- BIPV/BAPV --- BIPV-Glazing --- JNNSM --- MNRE --- Zero energy-building --- stolen heat --- energy efficiency --- heat metering --- heat accounting --- dynamic simulation --- social housing --- building simulation --- heat cost allocators --- thermostatic radiator valves --- marine renewables --- remote sensing --- offshore wind --- SWOT(strengths, weaknesses, opportunities and threats) analysis --- greenhouse modeling --- energy demand --- thermal screen --- shading screen --- smart rooftop technologies --- solar energy --- urban heat island --- building codes --- energy policies --- 3D roof city model --- urban landscapes
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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.
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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Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry.
unmanned aerial vehicles --- seedling detection --- forest regeneration --- reforestation --- establishment survey --- machine learning --- multispectral classification --- UAV photogrammetry --- forest modeling --- ancient trees measurement --- tree age prediction --- Mauritia flexuosa --- semantic segmentation --- end-to-end learning --- convolutional neural network --- forest inventory --- Unmanned Aerial Systems (UAS) --- structure from motion (SfM) --- Unmanned Aerial Vehicles (UAV) --- Photogrammetry --- Thematic Mapping --- Accuracy Assessment --- Reference Data --- Forest Sampling --- Remote Sensing --- Robinia pseudoacacia L. --- reproduction --- spreading --- short rotation coppice --- unmanned aerial system (UAS) --- object-based image analysis (OBIA) --- convolutional neural network (CNN) --- juniper woodlands --- ecohydrology --- remote sensing --- unmanned aerial systems --- central Oregon --- rangelands --- seedling stand inventorying --- photogrammetric point clouds --- hyperspectral imagery --- leaf-off --- leaf-on --- UAV --- multispectral image --- forest fire --- burn severity --- classification --- precision agriculture --- biomass evaluation --- image processing --- Castanea sativa --- unmanned aerial vehicles (UAV) --- precision forestry --- forestry applications --- RGB imagery
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