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High Power 1.5 μm Broad Area Laser Diodes Wavelength Stabilized by Surface Gratings
摘要： Wavelength stabilization against temperature variation of high-power broad area 1.5-μm InGaAsP/InP laser diodes is demonstrated by employing surface gratings. The development targets application in eye-safe automotive LIDAR systems, which would bene?t from deploying narrowband receiver ?lters to block ambient solar radiation for improved signal-to-noise ratio. The surface grating is monolithically integrated on the laser chip using nanoimprint lithography. The peak power of the lasers exceeded 6 W in pulsed mode, for an FWHM spectral width of 0.3 nm and a peak wavelength drift of only 0.1 nm/°C. The wavelength shift with temperature is reduced by ?ve times compared to broad area high-power Fabry–Perot laser diodes typically employed in LIDAR systems.
关键词： high power,distributed Bragg re?ector,LIDAR,Diode lasers
更新于2025-11-28 14:24:03
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[IEEE 2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) - Nara (2018.9.11-2018.9.14)] 2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) - Development of a Person-Searching Algorithm Using an Omnidirectional Camera and LiDAR for the Tsukuba Challenge
摘要： In this paper, we propose a method to detect the direction of a specific color person and a signboard using an omnidirectional camera and a 3D-LiDAR. For the person searching, we used a combination of an omnidirectional camera and a 3D-LiDAR. The omnidirectional camera was used to detect the direction of the specific color person and the signboard. The 3D-LiDAR was used to detect the distance to the person and the signboard. We conducted experiments in indoor and outdoor environments. The experimental results show that the proposed method can detect the direction of the specific color person and the signboard.
关键词： omnidirectional camera,person searching,signboard detection,3D-LiDAR,specific color detection
更新于2025-09-23 15:23:52
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Wintertime Local Wind Dynamics from Scanning Doppler Lidar and Air Quality in the Arve River Valley
摘要： Air quality issues are frequent in urbanized valleys, particularly in wintertime when a temperature inversion forms and the air within the valley is stably stratified over several days. In addition to pollutant sources, local winds can have a significant impact on the spatial distribution and temporal evolution of pollutant concentrations. They can be very complex and difficult to represent in numerical weather prediction models, particularly under stable conditions. Better knowledge of these local winds from observations is also a prerequisite to improving air quality prediction capability. This paper analyses local winds during the Passy-2015 field experiment that took place in a section of the Arve river valley, near Chamonix–Mont-Blanc. This location is one of the worst places in France regarding air quality. The wind analysis, which is mainly based on scanning Doppler lidar data sampling a persistent temperature inversion episode, reveals features consistent with the higher pollutant concentrations observed in this section of the valley as well as their spatial heterogeneities. In particular, an elevated down-valley jet is observed at night in the northern half of the valley, which, combined with a weak daytime up-valley wind, leads to very poor ventilation of the lowest layers. A northeast–southwest gradient in ventilation is observed on a daily-average, and is consistent with the PM10 heterogeneities observed within the valley.
关键词： scanning Doppler wind lidar,Passy-2015 field experiment,cold air pool,local wind dynamics,air quality,alpine valley
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Simulation Based Approach to Estimating the Three Dimensional Structure of the Harvard Forest with Multi-Modal Remote Sensing
摘要： Tracking carbon as it enters and exits each stage of the carbon cycle is necessary to help build understanding of the cycle's mechanics and its effect on climate. Satellite and airplane-based remote sensing technologies have shown promising results in aiding in human understanding of our planet, including vegetative areas. The Harvard Forest has been studied in various ways over the course of the last century. In particular, synthetic aperture radar, LiDAR, and passive optical sensors have each been used to study the Harvard Forest. Employing a form of data fusion, we present an approach to estimate a forest stand's mean canopy height and biomass for each component tree species while employing minimal ground measurements. We present an approach where a database of simulated forest stands is generated containing both homogeneous stands and heterogeneous stands with up to four tree species present in a given stand. Each simulated stand is compared to an input stand on a number of criteria and a figure of similarity is calculated. In the case that a simulated stand isn't found with a figure of similarity below a set threshold, an iterative process is employed to modify the most similar stand to improve the factor of similarity by modifying the stand's species composition, tree densities, heights, and biomasses. A simulated stand, either pre-existing or developed dynamically will be considered a reasonable representation of the physical forest stand and the 3-D structure of the simulated stand will be reported as an estimate for that of the physical forest stand. This method relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We have previously investigated the ability of our method to differentiate between coniferous and deciduous trees in the same forest stand. We propose to extend this to a maximum of four different tree species, and to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.
关键词： Harvard Forest,Forest Parameter Estimation,IfSAR,Heterogeneous Forests,SAR,LiDAR
更新于2025-09-23 15:23:52
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Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry
摘要： We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.
关键词： bathymetry,full waveform,wavelet transformation,LiDAR
更新于2025-09-23 15:23:52
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Ground based hyperspectral imaging for extensive mango yield estimation
摘要： Fruit yield estimation in orchard blocks is an important objective in the context of precision agriculture, as it makes it easier for the farmer to plan ahead and efficiently use resources. Nevertheless, its implementation is labour-intensive and involves the manual counting of the fruit present in the trees. While colour (RGB) has been widely shown to be successful and arguably sufficient for yield estimation in orchards, hyperspectral imaging (HSI) shows promise for more nuanced tasks such as disease detection, cultivar classification and fruit maturity estimation. Therefore, it is important to ask how appropriate is HSI for the task of yield estimation, with a view to performing all of these tasks with just one sensor. This paper presents a novel mango yield estimation pipeline using ground based line-scan HSI acquired from an unmanned ground vehicle. Hyperspectral images were collected on a commercial mango orchard block in December 2017 and pre-processed for illumination compensation. After tree delimitation and mango pixel identification, an optimisation process was carried out to obtain the best models for fruit counting, using mango counts obtained by manually counting the fruit on-tree, and using state-of-the-art RGB techniques for yield estimation. Models were validated and tested on hundreds of trees, and subsequently mapped. In testing, determination coefficients reached values of up to 0.75 against field counts (predicting 18 trees) and 0.83 against RGB mango counts (predicting 216 trees). These results suggest that line-scan HSI can be used to accurately estimate yield in orchards, especially in scenarios in which this technology is already chosen for the determination of other traits.
关键词： Field robotics,Computer vision,Lidar,Hyperspectral,Fruit counting
更新于2025-09-23 15:23:52
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Evaluation of methods for gravity wave extraction from middle-atmospheric lidar temperature measurements
摘要： This study evaluates commonly used methods of extracting gravity-wave-induced temperature perturbations from lidar measurements. The spectral response of these methods is characterized with the help of a synthetic data set with known temperature perturbations added to a realistic background temperature profile. The simulations are carried out with the background temperature being either constant or varying in time to evaluate the sensitivity to temperature perturbations not caused by gravity waves. The different methods are applied to lidar measurements over New Zealand, and the performance of the algorithms is evaluated. We find that the Butterworth filter performs best if gravity waves over a wide range of periods are to be extracted from lidar temperature measurements. The running mean method gives good results if only gravity waves with short periods are to be analyzed.
关键词： running mean,sliding polynomial fit,lidar,extraction methods,temperature perturbations,spectral response,gravity waves,Butterworth filter
更新于2025-09-23 15:23:52
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Recentering the rural: Lidar and articulated landscapes among the Maya
摘要： The concept of the 'rural' may, for the ancient Maya, need 'recentering,' an acknowledgement that 'rurality' as a lifeway insu?ciently describes the integrated landscapes with high pedestrian 'vagility' that were dominated by dynastic centers. Large-scale lidar captures reveal special-purpose facilities for defense, surveillance, possible chocolate plantations under close supervision, orderly if defensible landscapes, agricultural works of landesque scope, and overall regional articulations with variable intensity of settlement. If there were 'rural' zones, they existed in coordination with centers. There was no exclusive dichotomy between inner and outer zones nor were there distinct populations, one acutely centered, the other dispersed. A conurban pattern applies to the evidence, with multiple, overlapping foci, gradients of drop-o?, complex interactions over time, and a continuous use-surface.
关键词： Landscape control,Conurbation,Redefining rurality,Lidar technology,Maya,Pedestrian vagility
更新于2025-09-23 15:23:52
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Study of the effects of phytoplankton morphology and vertical profile on lidar attenuated backscatter and depolarization ratio
摘要： Propagation of a lidar beam in a coupled atmosphere-ocean model consisting of multiple atmospheric and upper oceanic layers and a rough ocean surface is studied by using a vectorized Monte Carlo radiative transfer solver optimized specifically for lidar-based remote sensing applications. The effects of assumed phytoplankton morphology variations and its vertical distribution on the lidar attenuated backscatter and depolarization ratio are studied. In this study, a phytoplankton particle is assumed to be a sphere, a sphere with a core, or a randomly distorted hexahedron with or without a core. The single-scattering properties of the nonspherical/inhomogeneous particles are computed using appropriate state-of-the-art light-scattering computational capabilities. Vertical variation of the phytoplankton distribution is derived explicitly using a PAR (photosynthetically active radiation) limited carbon biomass balance equation that is subsequently coupled with the Monte Carlo solver.
关键词： Radiative transfer,Lidar,Ocean optics,Monte Carlo,Phytoplankton,Net primary production,Remote sensing
更新于2025-09-23 15:23:52
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Methods for LiDAR-based estimation of extensive grassland biomass
摘要： Biomass estimation derived from Terrestrial Laser Scanning (TLS) is already an established technique in forestry, whereas TLS measurements are less well investigated for use in grassland ecosystems. Detailed information provided by survey systems can enhance management strategies and support timely measures. Field measurements were made in the “UNESCO biosphere reserve Rh?n” in Central Germany with a TLS station (Leica P30). Four methods for estimating biomass from 3d point clouds have been applied to the data, which were Canopy Surface Height (CSH), Sum of Voxel, Mean of 3d-grid Heights, and Convex-Hull. The optimum set of model specific parameters to increase model stability and performance was identified. The methods were compared in terms of model performance and calculation speed. For each method the effect of the number of scans used for each point cloud was assessed. The best fit for fresh biomass determination was achieved with a mean CSH value derived from the top 5% of all CSH values (adj. R2 0.72). In all cases, models for dry biomass estimation had less explanatory power than those for fresh biomass. CSH models based on point clouds, which were merged from two opposite scans, achieved the highest average accuracy both for fresh and dry biomass (adj. R2 0.73 and 0.58 respectively).
关键词： Biomass,TLS,Point cloud,Grassland,LiDAR
更新于2025-09-23 15:23:52