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Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 14564

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Special Issue Editor

Dr. Pasqualino Gaudio

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Guest Editor

Department of Industrial Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
Interests: laser sensors for application and diagnostics in environmental science; detection and identification of chemical/biological agents in CBRNe events; diagnostics for Fusion Reactors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues，

Laser-based remote sensing techniques are very promising methodologies. They have become important, sometimes primary, devices in industrial, urban, environmental, safety, and security applications. Concerning the safety and security field, remote sensing monitoring plays a crucial role in providing fast and preventive alarms in the case of intentional (terrorism, war, etc.) or accidental (natural, accident) diffusions of dangerous substances, such chemicals or pathogens. Moreover, remote sensing approaches may avoid people working directly in threatening areas and it may help understand the dangers and to take appropriate countermeasures.

Pollution monitoring is also fundamental to preserve and guarantee a good quality of life, especially in industrial and high-traffic urban areas.

Although many remote laser-based techniques have been developed, such as Lidar, Dial, Laser-Induced Fluorescence (LIF), and Laser-Induced Breakdown Spectroscopy (LIBS), these instruments are usually large, heavy, and expensive, leading to underutilization of these devices. Moreover, these techniques usually require complicated data analysis, since they work in very variable and unpredictable environments.

This Special Issue refers to any research in the field of laser-based remote sensing applied to environmental, safety, and security fields. It will accept both original research and review articles about not only the techniques, but also innovative experimental apparatus or devices, and new data analysis techniques.

Dr. Pasqualino Gaudio
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

remote sensing
Lidar
Dial
LIBS
optical techniques for environmental science
standoff detection of chemical and biological agents
laser-based detection systems
laser identification chemical and biological agent

Published Papers (5 papers)

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Research

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20 pages, 6727 KiB

Open AccessArticle

Study of the Vertical Structure of the Coastal Boundary Layer Integrating Surface Measurements and Ground-Based Remote Sensing

by Teresa Lo Feudo, Claudia Roberta Calidonna, Elenio Avolio and Anna Maria Sempreviva

Sensors 2020, 20(22), 6516; https://doi.org/10.3390/s20226516 - 14 Nov 2020

Cited by 10 | Viewed by 1826

Abstract

The understanding of the atmospheric processes in coastal areas requires the availability of quality datasets describing the vertical and horizontal spatial structure of the Atmospheric Boundary Layer (ABL) on either side of the coastline. High-resolution Numerical Weather Prediction (NWP) models can provide this information and the main ingredients for good simulations are: an accurate description of the coastline and a correct subgrid process parametrization permitting coastline discontinuities to be caught. To provide an as comprehensive as possible dataset on Mediterranean coastal area, an intensive experimental campaign was realized at a near-shore Italian site, using optical and acoustic ground-based remote sensing and surface instruments, under different weather characteristic and stability conditions; the campaign is also fully simulated by a NWP model. Integrating information from instruments responding to different atmospheric properties allowed for an explanation of the development of various patterns in the vertical structure of the atmosphere. Wind LiDAR measurements provided information of the internal boundary layer from the value of maximum height reached by the wind profile; a height between 80 and 130 m is often detected as an interface between two different layers. The NWP model was able to simulate the vertical wind profiles and the eight of the ABL. Full article

(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques)

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16 pages, 5897 KiB

Open AccessArticle

Vision-Based Safety-Related Sensors in Low Visibility by Fog

by Bong Keun Kim and Yasushi Sumi

Sensors 2020, 20(10), 2812; https://doi.org/10.3390/s20102812 - 15 May 2020

Cited by 6 | Viewed by 2962

Abstract

Mobile service robots are expanding their use to outdoor areas affected by various weather conditions, but the outdoor environment directly affects the functional safety of robots implemented by vision-based safety-related sensors (SRSs). Therefore, this paper aims to set the fog as the environmental condition of the robot and to understand the relationship between the quantified value of the environmental conditions and the functional safety performance of the robot. To this end, the safety functions of the robot built using SRS and the requirements for the outdoor environment affecting them are described first. The method of controlling visibility for evaluating the safety function of SRS is described through the measurement and control of visibility, a quantitative means of expressing the concentration of fog, and wavelength analysis of various SRS light sources. Finally, object recognition experiments using vision-based SRS for robots are conducted at low visibility. Through this, it is verified that the proposed method is a specific and effective method for verifying the functional safety of the robot using the vision-based SRS, for low visibility environmental requirements. Full article

(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques)

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10 pages, 354 KiB

Open AccessArticle

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

by Lea Fellner, Marian Kraus, Florian Gebert, Arne Walter and Frank Duschek

Sensors 2020, 20(9), 2524; https://doi.org/10.3390/s20092524 - 29 Apr 2020

Cited by 7 | Viewed by 3079

Abstract

Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%. Full article

(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques)

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12 pages, 3730 KiB

Open AccessArticle

High Repetition Rate Mid-Infrared Differential Absorption Lidar for Atmospheric Pollution Detection

by Yu Gong, Lingbing Bu, Bin Yang and Farhan Mustafa

Sensors 2020, 20(8), 2211; https://doi.org/10.3390/s20082211 - 14 Apr 2020

Cited by 34 | Viewed by 3725

Abstract

Developments in mid-infrared Differential Absorption Lidar (DIAL), for gas remote sensing, have received a significant amount of research in recent years. In this paper, a high repetition rate tunable mid-infrared DIAL, mounted on a mobile platform, has been built for long range remote detection of gas plumes. The lidar uses a solid-state tunable optical parametric oscillator laser, which can emit laser pulse with repetition rate of 500 Hz and between the band from 2.5 μm to 4 μm. A monitoring channel has been used to record the laser energy in real-time and correct signals. Convolution correction technology has also been incorporated to choose the laser wavelengths. Taking NO₂ and SO₂ as examples, lidar system calibration experiment and open field observation experiment have been carried out. The observation results show that the minimum detection sensitivity of NO₂ and SO₂ can reach 0.07 mg/m³, and 0.31 mg/m³, respectively. The effective temporal resolution can reach second level for the high repetition rate of the laser, which demonstrates that the system can be used for the real-time remote sensing of atmospheric pollution gas. Full article

(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques)

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Other

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11 pages, 2337 KiB

Open AccessLetter

Adaptive Quasi-Unsupervised Detection of Smoke Plume by LiDAR

by Riccardo Rossi, Michela Gelfusa, Andrea Malizia and Pasqualino Gaudio

Sensors 2020, 20(22), 6602; https://doi.org/10.3390/s20226602 - 18 Nov 2020

Cited by 4 | Viewed by 2435

Abstract

The early detection of fire is one of the possible applications of LiDAR techniques. The smoke generated by a fire is mainly compounded of CO₂, H₂O, particulate, and other combustion products, which involve the local variation of the scattering of the electromagnetic wave at specific wavelengths. The increases of the backscattering coefficient are transduced in peaks on the signal of the backscattering power recorded by the LiDAR system, located exactly where the smoke plume is, allowing not only the detection of a fire but also its localization. The signal processing of the LiDAR signals is critical in the determination of the performances of the fire detection. It is important that the sensitivity of the apparatus is high enough but also that the number of false alarms is small, in order to avoid the trigger of useless and expensive countermeasures. In this work, a new analysis method, based on an adaptive quasi-unsupervised approach was used to ensure that the algorithm is continuously updated to the boundary conditions of the system, such as the weather and experimental apparatus issues. The method has been tested on an experimental campaign of 227 pulses and the performances have been analyzed in terms of sensitivity and specificity. Full article

(This article belongs to the Special Issue Laser Based Remote Sensors for Environmental Science: Apparatus, Measurements and Analysis Techniques)

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