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Development and Application for Laser Spectroscopies

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 7945

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Special Issue Editors

Dr. Valeria Spizzichino

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Guest Editor

Enea (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) - Diagnostics and Metrology Laboratory (FSN-TECFIS-DIM), Via Enrico Fermi, 45, 00044 Frascati, RM, Italy
Interests: development and application of laser spectroscopies; laser induced fluorescence; laser induced breakdown spectroscopy; Raman spectroscopy; reflectance and colorimetry; light-matter interaction; diagnostics; cultural heritage health status; environmental monitoring
Special Issues, Collections and Topics in MDPI journals

Dr. Luca Di Liberto

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Guest Editor

Institute of Atmospheric Sciences and Climate - National Research Council of Italy (CNR-ISAC), Via Fosso del Cavaliere, 100 00133 Rome, Italy
Interests: development and application of remote sensing techniques; LIDAR; laser Induced fluorescence, laser altimetry; environmental monitoring; climate Change; light-matter interaction

Special Issue Information

Dear Colleagues,

In recent decades, remote sensing based on laser techniques has increased in importance and number of applications in many fields, from Earth observation to security applications. Therefore, we are proposing this Special Issue to present the state-of-the-art and new trends in laser spectroscopic techniques applied in stand-off sensing from proximity to remote sensing, highlighting peculiarities and complementarities. Authors are invited to submit reviews or provide up-to-date and critical overviews of state-of-the-art and original research articles dealing with:

Design and development of innovative prototypes and sensors;
Application of remote sensing techniques based on laser spectroscopies and methods;
Combination and comparison of laser techniques with other remote sensing systems;
Data processing and interpretation, data fusion.
Moreover, topics include but are not limited to:
Earth observation (ocean, atmosphere, cryosphere, bathymetry, geodesy, etc.);
Environmental monitoring (aerosol, gases, clouds, etc.);
Security and forensics;
Cultural heritage diagnostics and 3D reconstruction.

Dr. Valeria Spizzichino
Dr. Luca Di Liberto
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Remote Sensing 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 2700 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

laser spectroscopies
emission spectroscopies
absorption spectroscopies
scattering
fluorescence
Raman
LIDAR
nuclear, atomic, and molecular spectroscopies
chemometrics
cavity ring-down spectroscopy
ultra-fast laser spectroscopies (pico-nano seconds)
enviromental sensing (ocean–atmospehere–land)

Published Papers (4 papers)

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Research

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21 pages, 6146 KiB

Open AccessArticle

Remote Measurements of Industrial CO₂ Emissions Using a Ground-Based Differential Absorption Lidar in the 2 µm Wavelength Region

by Neil Howes, Fabrizio Innocenti, Andrew Finlayson, Chris Dimopoulos, Rod Robinson and Tom Gardiner

Remote Sens. 2023, 15(22), 5403; https://doi.org/10.3390/rs15225403 - 17 Nov 2023

Viewed by 1252

Abstract

Carbon dioxide (CO₂) is a known greenhouse gas and one of the largest contributors to global warming in the Earth’s atmosphere. The remote detection and measurement of CO₂ from industrial emissions are not routinely carried out and are typically calculated from the fuel combusted or measured directly within ducted vents. However, these methods are not applicable for the quantification of fugitive emissions of CO₂. This work presents the results of remote measurement of CO₂ emissions using the differential absorption lidar (DIAL) technique at a wavelength of ~2 µm. The results from the DIAL measurements compare well with simultaneous in-stack measurements, these datasets were plotted against each other and can be described by a linear regression of y (t/h) = 1.04 x − 0.02, suggesting any bias in the DIAL data is likely small. Moreover, using the definition outlined in EN 15267-3 a lower detection limit of 0.12 t/h was estimated for the 2 µm wavelength DIAL data, this is three orders of magnitude lower than the corresponding CO₂ detection limit measured by NPL in the 1.5 µm wavelength region. Thus, this paper demonstrates the feasibility of high-resolution, ground-based DIAL measurements for quantifying industrial CO₂ emissions. Full article

(This article belongs to the Special Issue Development and Application for Laser Spectroscopies)

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19 pages, 7606 KiB

Open AccessArticle

Improvements of Fire Fuels Attributes Maps by Integrating Field Inventories, Low Density ALS, and Satellite Data in Complex Mediterranean Forests

by Roberto Crespo Calvo, Mª Ángeles Varo Martínez, Francisco Ruiz Gómez, Antonio Jesús Ariza Salamanca and Rafael M. Navarro-Cerrillo

Remote Sens. 2023, 15(8), 2023; https://doi.org/10.3390/rs15082023 - 11 Apr 2023

Viewed by 1734

Abstract

One of the most determining factors in forest fire behaviour is to characterize forest fuel attributes. We investigated a complex Mediterranean forest type—mountainous Abies pinsapo–Pinus–Quercus–Juniperus with distinct structures, such as broadleaf and needleleaf forests—to integrate field data, low density Airborne Laser Scanning (ALS), and multispectral satellite data for estimating forest fuel attributes. The three-step procedure consisted of: (i) estimating three key forest fuel attributes (biomass, structural complexity and hygroscopicity), (ii) proposing a synthetic index that encompasses the three attributes to quantify the potential capacity for fire propagation, and (iii) generating a cartograph of potential propagation capacity. Our main findings showed that Biomass–ALS calibration models performed well for Abies pinsapo (R² = 0.69), Juniperus spp. (R² = 0.70), Pinus halepensis (R² = 0.59), Pinus spp. mixed (R² = 0.80), and Pinus spp.–Juniperus spp. (R² = 0.59) forests. The highest values of biomass were obtained for Pinus halepensis forests (190.43 Mg ha⁻¹). The structural complexity of forest fuels was assessed by calculating the LiDAR Height Diversity Index (LHDI) with regard to the distribution and vertical diversity of the vegetation with the highest values of LHDI, which corresponded to Pinus spp.–evergreen (2.56), Quercus suber (2.54), and Pinus mixed (2.49) forests, with the minimum being obtained for Juniperus (1.37) and shrubs (1.11). High values of the Fuel Desiccation Index (IDM) were obtained for those areas dominated by shrubs (−396.71). Potential Behaviour Biomass Index (ICB) values were high or very high for 11.86% of the area and low or very low for 77.07%. The Potential Behaviour Structural Complexity Index (ICE) was high or very high for 37.23% of the area, and low or very low for 46.35%, and the Potential Behaviour Fuel Desiccation Index (ICD) was opposite to the ICB and ICE, with high or very high values for areas with low biomass and low structural complexity. Potential Fire Behaviour Index (ICP) values were high or very high for 38.25% of the area, and low or very low values for 45.96%. High or very high values of ICP were related to Pinus halepensis and Pinus pinaster forests. Remote sensing has been applied to improve fuel attribute characterisation and cartography, highlighting the utility of integrating multispectral and ALS data to estimate those attributes that are more closely related to the spatial organisation of vegetation. Full article

(This article belongs to the Special Issue Development and Application for Laser Spectroscopies)

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21 pages, 9050 KiB

Open AccessArticle

A Novel Real-Time Edge-Guided LiDAR Semantic Segmentation Network for Unstructured Environments

by Xiaoqing Yin, Xu Li, Peizhou Ni, Qimin Xu and Dong Kong

Remote Sens. 2023, 15(4), 1093; https://doi.org/10.3390/rs15041093 - 16 Feb 2023

Cited by 4 | Viewed by 2189

Abstract

LiDAR-based semantic segmentation, particularly for unstructured environments, plays a crucial role in environment perception and driving decisions for unmanned ground vehicles. Unfortunately, chaotic unstructured environments, especially the high-proportion drivable areas and large-area static obstacles therein, inevitably suffer from the problem of blurred class edges. Existing published works are prone to inaccurate edge segmentation and have difficulties dealing with the above challenge. To this end, this paper proposes a real-time edge-guided LiDAR semantic segmentation network for unstructured environments. First, the main branch is a lightweight architecture that extracts multi-level point cloud semantic features; Second, the edge segmentation module is designed to extract high-resolution edge features using cascaded edge attention blocks, and the accuracy of extracted edge features and the consistency between predicted edge and semantic segmentation results are ensured by additional supervision; Third, the edge guided fusion module fuses edge features and main branch features in a multi-scale manner and recalibrates the channel feature using channel attention, realizing the edge guidance to semantic segmentation and further improving the segmentation accuracy and adaptability of the model. Experimental results on the SemanticKITTI dataset, the Rellis-3D dataset, and on our test dataset demonstrate the effectiveness and real-time performance of the proposed network in different unstructured environments. Especially, the network has state-of-the-art performance in segmentation of drivable areas and large-area static obstacles in unstructured environments. Full article

(This article belongs to the Special Issue Development and Application for Laser Spectroscopies)

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Review

Jump to: Research

20 pages, 5896 KiB

Open AccessReview

Recent Advances in Light-Induced Thermoelastic Spectroscopy for Gas Sensing: A Review

by Yufeng Pan, Jinbiao Zhao, Ping Lu, Chaotan Sima and Deming Liu

Remote Sens. 2023, 15(1), 69; https://doi.org/10.3390/rs15010069 - 23 Dec 2022

Cited by 7 | Viewed by 2107

Abstract

Light-induced thermoelastic spectroscopy (LITES) is a promising optical approach for gas sensing, which uses a quartz tuning fork (QTF) as a photothermal detector, instead of a commercial photodetector. Since the QTF has the advantages of low cost, small size, high resonance frequency, high-quality factor (Q-factor), and a wide spectral response range, and the LITES sensor has received extensive attention and obtained great development. This review paper summarizes and discusses the advances of the QTF-based, state-of-the-art LITES gas sensing technique in recent years and presents the development prospects of LITES sensor in the future. Full article

(This article belongs to the Special Issue Development and Application for Laser Spectroscopies)

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