Experimental demonstration of Vehicle-borne Near Infrared Three-Dimensional Ghost Imaging LiDAR

Author(s):  
Xiaodong Mei ◽  
Chenglong Wang ◽  
Long Pan ◽  
Pengwei Wang ◽  
Wenlin Gong ◽  
...  
2018 ◽  
Vol 10 (5) ◽  
pp. 732 ◽  
Author(s):  
Chenglong Wang ◽  
Xiaodong Mei ◽  
Long Pan ◽  
Pengwei Wang ◽  
Wang Li ◽  
...  

2015 ◽  
Vol 6 (1) ◽  
pp. 19-29 ◽  
Author(s):  
G. Bitelli ◽  
P. Conte ◽  
T. Csoknyai ◽  
E. Mandanici

The management of an urban context in a Smart City perspective requires the development of innovative projects, with new applications in multidisciplinary research areas. They can be related to many aspects of city life and urban management: fuel consumption monitoring, energy efficiency issues, environment, social organization, traffic, urban transformations, etc. Geomatics, the modern discipline of gathering, storing, processing, and delivering digital spatially referenced information, can play a fundamental role in many of these areas, providing new efficient and productive methods for a precise mapping of different phenomena by traditional cartographic representation or by new methods of data visualization and manipulation (e.g. three-dimensional modelling, data fusion, etc.). The technologies involved are based on airborne or satellite remote sensing (in visible, near infrared, thermal bands), laser scanning, digital photogrammetry, satellite positioning and, first of all, appropriate sensor integration (online or offline). The aim of this work is to present and analyse some new opportunities offered by Geomatics technologies for a Smart City management, with a specific interest towards the energy sector related to buildings. Reducing consumption and CO2 emissions is a primary objective to be pursued for a sustainable development and, in this direction, an accurate knowledge of energy consumptions and waste for heating of single houses, blocks or districts is needed. A synoptic information regarding a city or a portion of a city can be acquired through sensors on board of airplanes or satellite platforms, operating in the thermal band. A problem to be investigated at the scale A problem to be investigated at the scale of the whole urban context is the Urban Heat Island (UHI), a phenomenon known and studied in the last decades. UHI is related not only to sensible heat released by anthropic activities, but also to land use variations and evapotranspiration reduction. The availability of thermal satellite sensors is fundamental to carry out multi-temporal studies in order to evaluate the dynamic behaviour of the UHI for a city. Working with a greater detail, districts or single buildings can be analysed by specifically designed airborne surveys. The activity has been recently carried out in the EnergyCity project, developed in the framework of the Central Europe programme established by UE. As demonstrated by the project, such data can be successfully integrated in a GIS storing all relevant data about buildings and energy supply, in order to create a powerful geospatial database for a Decision Support System assisting to reduce energy losses and CO2 emissions. Today, aerial thermal mapping could be furthermore integrated by terrestrial 3D surveys realized with Mobile Mapping Systems through multisensor platforms comprising thermal camera/s, laser scanning, GPS, inertial systems, etc. In this way the product can be a true 3D thermal model with good geometric properties, enlarging the possibilities in respect to conventional qualitative 2D images with simple colour palettes. Finally, some applications in the energy sector could benefit from the availability of a true 3D City Model, where the buildings are carefully described through three-dimensional elements. The processing of airborne LiDAR datasets for automated and semi-automated extraction of 3D buildings can provide such new generation of 3D city models.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shanshan Chen ◽  
Zhiguang Liu ◽  
Huifeng Du ◽  
Chengchun Tang ◽  
Chang-Yin Ji ◽  
...  

AbstractKirigami, with facile and automated fashion of three-dimensional (3D) transformations, offers an unconventional approach for realizing cutting-edge optical nano-electromechanical systems. Here, we demonstrate an on-chip and electromechanically reconfigurable nano-kirigami with optical functionalities. The nano-electromechanical system is built on an Au/SiO2/Si substrate and operated via attractive electrostatic forces between the top gold nanostructure and bottom silicon substrate. Large-range nano-kirigami like 3D deformations are clearly observed and reversibly engineered, with scalable pitch size down to 0.975 μm. Broadband nonresonant and narrowband resonant optical reconfigurations are achieved at visible and near-infrared wavelengths, respectively, with a high modulation contrast up to 494%. On-chip modulation of optical helicity is further demonstrated in submicron nano-kirigami at near-infrared wavelengths. Such small-size and high-contrast reconfigurable optical nano-kirigami provides advanced methodologies and platforms for versatile on-chip manipulation of light at nanoscale.


Author(s):  
Jun-Li Xu ◽  
Cecilia Riccioli ◽  
Ana Herrero-Langreo ◽  
Aoife Gowen

Deep learning (DL) has recently achieved considerable successes in a wide range of applications, such as speech recognition, machine translation and visual recognition. This tutorial provides guidelines and useful strategies to apply DL techniques to address pixel-wise classification of spectral images. A one-dimensional convolutional neural network (1-D CNN) is used to extract features from the spectral domain, which are subsequently used for classification. In contrast to conventional classification methods for spectral images that examine primarily the spectral context, a three-dimensional (3-D) CNN is applied to simultaneously extract spatial and spectral features to enhance classificationaccuracy. This tutorial paper explains, in a stepwise manner, how to develop 1-D CNN and 3-D CNN models to discriminate spectral imaging data in a food authenticity context. The example image data provided consists of three varieties of puffed cereals imaged in the NIR range (943–1643 nm). The tutorial is presented in the MATLAB environment and scripts and dataset used are provided. Starting from spectral image pre-processing (background removal and spectral pre-treatment), the typical steps encountered in development of CNN models are presented. The example dataset provided demonstrates that deep learning approaches can increase classification accuracy compared to conventional approaches, increasing the accuracy of the model tested on an independent image from 92.33 % using partial least squares-discriminant analysis to 99.4 % using 3-CNN model at pixel level. The paper concludes with a discussion on the challenges and suggestions in the application of DL techniques for spectral image classification.


2018 ◽  
Vol 616 ◽  
pp. A120 ◽  
Author(s):  
Aleksandr V. Mosenkov ◽  
Flor Allaert ◽  
Maarten Baes ◽  
Simone Bianchi ◽  
Peter Camps ◽  
...  

We present results of the detailed dust energy balance study for the seven large edge-on galaxies in the HEROES sample using three-dimensional (3D) radiative transfer (RT) modelling. Based on available optical and near-infrared (NIR) observations of the HEROES galaxies, we derive the 3D distribution of stars and dust in these galaxies. For the sake of uniformity, we apply the same technique to retrieve galaxy properties for the entire sample: we use a stellar model consisting of a Sérsic bulge and three double-exponential discs (a superthin disc for a young stellar population and thin and thick discs for old populations). For the dust component, we adopt a double-exponential disc with the new THEMIS dust-grain model. We fit oligochromatic RT models to the optical and NIR images with the fitting algorithm FITSKIRT and run panchromatic simulations with the SKIRT code at wavelengths ranging from ultraviolet to submillimeter. We confirm the previously stated dust energy balance problem in galaxies: for the HEROES galaxies, the dust emission derived from our RT calculations underestimates the real observations by a factor 1.5–4 for all galaxies except NGC 973 and NGC 5907 (apparently, the latter galaxy has a more complex geometry than we used). The comparison between our RT simulations and the observations at mid-infrared–submillimetre wavelengths shows that most of our galaxies exhibit complex dust morphologies (possible spiral arms, star-forming regions, more extended dust structure in the radial and vertical directions). We suggest that, in agreement with results from the literature, the large- and small-scale structure is the most probable explanation for the dust energy balance problem.


2012 ◽  
Vol 51 (26) ◽  
pp. 8875-8882 ◽  
Author(s):  
Méabh Nic An tSaoir ◽  
Daniel Luis Abreu Fernandes ◽  
Jacinto Sá ◽  
Kuniyuki Kitagawa ◽  
Christopher Hardacre ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document