Principle and Physics of the LiDAR Measurement

Chazette, Patrick; Totems, Julien; Hespel, Laurent; Bailly, Jean-Stéphane

doi:10.1016/b978-1-78548-102-4.50005-3

Cited by 25 publications

(11 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wound measurement plays a central role in the successful management of advanced wounds. The regular assessment of wound size can predict healing and provides information that can guide treatment decisions [ 1 , 5 ]. The current methods used for wound size measurement in clinical settings are centered on simple ruler-based techniques or wound tracing.…”

Section: Discussionmentioning

confidence: 99%

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Song,

Kim,

Kwon

et al. 2023

JCM

View full text Add to dashboard Cite

The accurate assessment of wound size is a critical step in advanced wound care management. This study aims to introduce and validate a Light Detection and Ranging (LiDAR) technique for measuring wound size. Twenty-eight wounds treated from December 2022 to April 2023 at the Chungnam National University Hospital were analyzed. All the wounds were measured using three techniques: conventional ruler methods, the LiDAR technique, and ImageJ analysis. Correlation analysis, linear regression, and Bland–Altman plot analysis were performed to validate the accuracy of the novel method. The measurement results (mean ± standard deviation) obtained using the ruler method, LiDAR technique, and ImageJ analysis were 112.99 ± 110.07 cm2, 73.59 ± 72.97 cm2, and 74.29 ± 72.15 cm2, respectively. The Pearson correlation coefficient was higher for the LiDAR application (0.995) than for the conventional ruler methods (mean difference, −5.0000 cm2), as was the degree of agreement (mean difference, 38.6933 cm2). Wound size measurement using LiDAR is a simple and reliable method that will enable practitioners to conveniently assess wounds with a flattened and irregular shape with higher accuracy. However, non-flattened wounds cannot be assessed owing to the technical limitations of LiDAR.

show abstract

Section: Discussionmentioning

confidence: 99%

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Song,

Kim,

Kwon

et al. 2023

JCM

View full text Add to dashboard Cite

show abstract

“…These waves are then reflected off the target and detected by the receiving system. The data obtained are subsequently processed to produce parameter information, including distance [58]. LiDAR sensors have been utilized in crop row detection to provide highly accurate and detailed 3D maps of crop canopies [59].…”

Section: Lidar Sensorsmentioning

confidence: 99%

Row Detection BASED Navigation and Guidance for Agricultural Robots and Autonomous Vehicles in Row-Crop Fields: Methods and Applications

et al. 2023

View full text Add to dashboard Cite

Crop row detection is one of the foundational and pivotal technologies of agricultural robots and autonomous vehicles for navigation, guidance, path planning, and automated farming in row crop fields. However, due to a complex and dynamic agricultural environment, crop row detection remains a challenging task. The surrounding background, such as weeds, trees, and stones, can interfere with crop appearance and increase the difficulty of detection. The detection accuracy of crop rows is also impacted by different growth stages, environmental conditions, curves, and occlusion. Therefore, appropriate sensors and multiple adaptable models are required to achieve high-precision crop row detection. This paper presents a comprehensive review of the methods and applications related to crop row detection for agricultural machinery navigation. Particular attention has been paid to the sensors and systems used for crop row detection to improve their perception and detection capabilities. The advantages and disadvantages of current mainstream crop row detection methods, including various traditional methods and deep learning frameworks, are also discussed and summarized. Additionally, the applications for different crop row detection tasks, including irrigation, harvesting, weeding, and spraying, in various agricultural scenarios, such as dryland, the paddy field, orchard, and greenhouse, are reported.

show abstract

“…The ALiAS lidar was flown onboard the ATR-42 (Figure 1) of SAFIRE off the east coast of Barbados. Developed at LSCE following a precursor instrument (Chazette et al, 2007;Chazette, 2016), ALiAS is based on a frequency-tripled Nd:YAG laser (ULTRA-100) manufactured by Lumibird/QUANTEL emitting at the wavelength of 355 nm, thus satisfying 10 eye safety requirements at the output window. The UV pulse energy is 30 mJ and the pulse repetition rate is 20 Hz.…”

Section: Lidar Characteristicsmentioning

confidence: 99%

Trade-wind clouds and aerosols characterized by airborne horizontal lidar measurements during the EUREC<sup>4</sup>A field campaign

Chazette¹,

Totems²,

Baron³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. From 23 January to 13 February 2020, twenty ATR-42 flights were conducted over the tropical Atlantic, off the coast of Barbados (−58°30' W 13°30' N), to characterize the trade-wind clouds generated by shallow convection. These flights were conducted as part of the international EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign. One of the objectives of these flights was to characterize the trade-wind cumuli at their base for a range of meteorological conditions, convective mesoscale organizations and times of the day, with the help of sidewards staring remote sensing (lidar and radar). This paper presents the datasets associated with horizontal lidar measurements. The lidar sampled clouds from a lateral window of the aircraft over a range of about 8 km, with a horizontal resolution of 15 to 30 m, over a rectangle pattern of 20 km by 130 km. The measurements made it possible to characterize the size distribution of clouds near their base, and the presence of dust-like aerosols within and above the marine boundary layer. This paper presents the measurements and the different levels of data processing, ranging from raw level 1 data (https://doi.org/10.25326/57; Chazette et al., 2020c) to level 2 and 3 processed data that include an horizontal cloud mask (https://doi.org/10.25326/58; Chazette et al., 2020b) and aerosol extinction coefficients (https://doi.org/10.25326/59; Chazette et al., 2020a). An intermediate level, companion to the level 1 data (level 1.5), is also available for calibrated and geolocalized data ( https://doi.org/10.25326/57; Chazette et al., 2020c).

show abstract

Principle and Physics of the LiDAR Measurement

Cited by 25 publications

References 34 publications

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Row Detection BASED Navigation and Guidance for Agricultural Robots and Autonomous Vehicles in Row-Crop Fields: Methods and Applications

Trade-wind clouds and aerosols characterized by airborne horizontal lidar measurements during the EUREC<sup>4</sup>A field campaign

Contact Info

Product

Resources

About

Principle and Physics of the LiDAR Measurement

Cited by 25 publications

References 34 publications

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Smartphone-Based LiDAR Application for Easy and Accurate Wound Size Measurement

Row Detection BASED Navigation and Guidance for Agricultural Robots and Autonomous Vehicles in Row-Crop Fields: Methods and Applications

Trade-wind clouds and aerosols characterized by airborne horizontal lidar measurements during the EUREC&lt;sup&gt;4&lt;/sup&gt;A field campaign

Contact Info

Product

Resources

About

Trade-wind clouds and aerosols characterized by airborne horizontal lidar measurements during the EUREC<sup>4</sup>A field campaign