Journal articles on the topic 'Lidar surface reflectance'
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Lu, Xiaomei, Yongxiang Hu, Yuekui Yang, Mark Vaughan, Zhaoyan Liu, Sharon Rodier, William Hunt, Kathy Powell, Patricia Lucker, and Charles Trepte. "Laser pulse bidirectional reflectance from CALIPSO mission." Atmospheric Measurement Techniques 11, no. 6 (June 8, 2018): 3281–96. http://dx.doi.org/10.5194/amt-11-3281-2018.
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Abstract. This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30 m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF–albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers.
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Li, Xiaolu, and Yu Liang. "Remote measurement of surface roughness, surface reflectance, and body reflectance with LiDAR." Applied Optics 54, no. 30 (October 15, 2015): 8904. http://dx.doi.org/10.1364/ao.54.008904.
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Roncat, A., N. Pfeifer, and C. Briese. "ASSESSMENT OF BOTTOM-OF-ATMOSPHERE REFLECTANCE IN LIDAR DATA AS REFERENCE FOR HYPERSPECTRAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W4 (September 13, 2017): 131–37. http://dx.doi.org/10.5194/isprs-annals-iv-2-w4-131-2017.
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While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a) make use of full-waveform information and (b) operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA), i.e. the target surface. <br><br> With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI) requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s) radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. <br><br> This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.
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Li, Zhigang, Christian Lemmerz, Ulrike Paffrath, Oliver Reitebuch, and Benjamin Witschas. "Airborne Doppler Lidar Investigation of Sea Surface Reflectance at a 355-nm Ultraviolet Wavelength." Journal of Atmospheric and Oceanic Technology 27, no. 4 (April 1, 2010): 693–704. http://dx.doi.org/10.1175/2009jtecha1302.1.
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Abstract The analysis of the sea surface reflectance for different incidence angles based on observations of an airborne Doppler lidar at an ultraviolet wavelength of 355 nm is described. The results were compared to sea surface reflectance models, including the contribution from whitecaps, specular reflection, and the subsurface volume backscattering. The observations show the expected effect of the wind stress on the sea surface reflectance and allow new insights into the significant contribution from subsurface reflectance for large incidence angles. While most of the observations and model results were obtained for isotropic reflectance, first results on anisotropic reflectance are also provided. The results from this study are relevant to future spaceborne wind lidar instruments, for example, the Atmospheric Dynamics Mission (ADM)-Aeolus, which could use the sea surface reflectance for the calibration of intensity and wind.
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Amediek, A., A. Fix, G. Ehret, J. Caron, and Y. Durand. "Airborne lidar reflectance measurements at 1.57 μm in support of the A-SCOPE mission for atmospheric CO<sub>2</sub>." Atmospheric Measurement Techniques Discussions 2, no. 3 (June 24, 2009): 1487–536. http://dx.doi.org/10.5194/amtd-2-1487-2009.
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Abstract. The characteristics of the lidar reflectance of the Earth's surface is an important issue for the IPDA lidar technique (integrated path differential absorption lidar) which is the proposed method for the spaceborne measurement of atmospheric carbon dioxide within the framework of ESA's A-SCOPE project. Both, the absolute reflectance of the ground and its variations have an impact on the measurement sensitivity. The first aspect influences the instrument's signal to noise ratio, the second one can lead to retrieval errors, if the ground reflectance changes are strong on small scales. The investigation of the latter is the main purpose of this study. Airborne measurements of the lidar ground reflectance at 1.57 μm wavelength were performed in Central and Western Europe, including many typical land surface coverages as well as the open sea. The analyses of the data show, that the lidar ground reflectance is highly variable on a wide range of spatial scales. However, by means of the assumption of laser footprints on the order of several tens of meters, as planned for spaceborne systems, and by means of an averaging of the data it was shown, that this specific retrieval error is compatible with the sensitivity requirements of spaceborne CO2 measurements.
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Amediek, A., A. Fix, G. Ehret, J. Caron, and Y. Durand. "Airborne lidar reflectance measurements at 1.57 μm in support of the A-SCOPE mission for atmospheric CO<sub>2</sub>." Atmospheric Measurement Techniques 2, no. 2 (November 26, 2009): 755–72. http://dx.doi.org/10.5194/amt-2-755-2009.
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Abstract. The characteristics of the lidar reflectance of the Earth's surface is an important issue for the IPDA lidar technique (integrated path differential absorption lidar) which is the proposed method for the spaceborne measurement of atmospheric carbon dioxide within the framework of ESA's A-SCOPE project. Both, the absolute reflectance of the ground and its variations have an impact on the measurement sensitivity. The first aspect influences the instrument's signal to noise ratio, the second one can lead to retrieval errors, if the ground reflectance changes are strong on small scales. The investigation of the latter is the main purpose of this study. Airborne measurements of the lidar ground reflectance at 1.57 μm wavelength were performed in Central and Western Europe, including many typical land surface coverages as well as the open sea. The analyses of the data show, that the lidar ground reflectance is highly variable on a wide range of spatial scales. However, by means of the assumption of laser footprints in the order of several tens of meters, as planned for spaceborne systems, and by means of an averaging of the data it was shown, that this specific retrieval error is well below 1 ppm (CO2 column mixing ratio), and so compatible with the sensitivity requirements of spaceborne CO2 measurements. Several approaches for upscaling the data in terms of the consideration of larger laser footprints, compared to the one used here, are shown and discussed. Furthermore, the collected data are compared to MODIS ground reflectance data.
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Cremons, Daniel R., Xiaoli Sun, James B. Abshire, and Erwan Mazarico. "Small PN-Code Lidar for Asteroid and Comet Missions—Receiver Processing and Performance Simulations." Remote Sensing 13, no. 12 (June 10, 2021): 2282. http://dx.doi.org/10.3390/rs13122282.
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Space missions to study small solar system bodies, such as asteroids and comet cores, are enhanced by lidar that can provide global mapping and serve as navigation sensors for landing and surface sampling. A small swath-mapping lidar using a fiber laser modulated by pseudo-noise (PN) codes is well-suited to small space missions and can provide contiguous measurements of surface topography with <10 cm precision. Here, we report the design and simulation of receiver signal processing of such a lidar using the small all-range lidar (SALi) as a design example. We simulated its performance in measuring the lidar range and surface reflectance by using instrument and target parameters, noise sources, and the receiver correlation processing method under various conditions. In single-beam Reconnaissance mode, the simulation predicted a maximum range of 440 km under sunlit conditions with a range precision as small as 8 cm. In its multi-pixel Mapping mode, the lidar can provide measurements out to 110 km with range precision of 5 cm. The effects of Doppler shift were quantified. From these results, we discuss the need for Doppler compensation via the receiver clock rate. We also describe a novel reflectance measurement method using active laser control, which allows the receiver to use simple comparators for analog-to-digital conversion. This method was simulated with surface reflectance values from 4% to 36% resulting in an RMS precision of 3% and a bias of 1% of the surface reflectance. We also performed an orbital ranging simulation using a shape model of 101955 Bennu for target surface elevation. The range residuals showed a sub-mm bias with a standard deviation of 5 cm. We implemented the receiver processor design on a Xilinx Ultrascale field-programmable gate array (FPGA). It was able to process received signals and retrieve accurate ranges at a single-channel measurement rate of 3050 Hz with a latency of 1.07 ms.
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Li Zhigang, 李志刚, Oliver Reitebuch Oliver Reitebuch, and 刘智深 Liu Zhishen. "Analysis of Sea Surface Reflectance from Airborne Lidar Experimental Measurement." Acta Optica Sinica 31, s1 (2011): s100505. http://dx.doi.org/10.3788/aos201131.s100505.
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Roncat, A., C. Briese, and N. Pfeifer. "A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 705–10. http://dx.doi.org/10.5194/isprs-archives-xli-b7-705-2016.
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In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a “single-wavelength reflectometer” to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.
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Roncat, A., C. Briese, and N. Pfeifer. "A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 705–10. http://dx.doi.org/10.5194/isprsarchives-xli-b7-705-2016.
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In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a “single-wavelength reflectometer” to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.
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Cole, Benjamin H., Ping Yang, Bryan A. Baum, Jerome Riedi, Laurent C.-Labonnote, Francois Thieuleux, and Steven Platnick. "Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures." Journal of Applied Meteorology and Climatology 52, no. 1 (January 2013): 186–96. http://dx.doi.org/10.1175/jamc-d-12-097.1.
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AbstractInsufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations of ice clouds used in downstream applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 ice microphysical model presumes a mixture of various ice crystal shapes with smooth facets, except for the compact aggregate of columns for which a severely rough condition is assumed. When compared with Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of nine different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding–doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multiangular observations. These results are consistent with previous studies that have used polarized reflection data. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.
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Lenain, Luc, Nicholas M. Statom, and W. Kendall Melville. "Airborne Measurements of Surface Wind and Slope Statistics over the Ocean." Journal of Physical Oceanography 49, no. 11 (November 2019): 2799–814. http://dx.doi.org/10.1175/jpo-d-19-0098.1.
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AbstractAs reported in 1954, more than a half century ago, C. Cox and W. Munk developed an empirical model of the slope distribution of ocean surface waves that has been widely used ever since to model the optical properties of the sea surface and is of particular importance to the satellite remote sensing community. In that work, the reflectance of sunlight was photographed from a Boeing B-17G bomber and was then analyzed. In this paper, surface slope statistics are investigated from airborne scanning topographic lidar data collected during a series of field experiments off the coast of California and in the Gulf of Mexico, over a broad range of environmental conditions, with wind speeds ranging from approximately 2 to 13 m s−1. Unlike the reflectance-based approach of Cox and Munk, the slope distribution is computed by counting laser glints produced by specular reflections as the lidar is scanned over the surface of the ocean. We find good agreement with their measurements for the mean-square slope and with more recent (2006) results from Bréon and Henriot that were based on satellite remote sensing. Significant discrepancies for the higher-order statistics are found and discussed. We also demonstrate here that airborne scanning lidar technology offers a viable means of remotely estimating surface wind speed and momentum flux.
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Hu, Deyong, Manqing Liu, Yufei Di, Chen Yu, and Yichen Wang. "USRT: A Solar Radiative Transfer Model Dedicated to Estimating Urban 3D Surface Reflectance." Urban Science 4, no. 4 (November 27, 2020): 66. http://dx.doi.org/10.3390/urbansci4040066.
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Urban 3D surface reflectance is a critical parameter for the modeling of surface biophysical processes. It is of great significance to enhance the accuracy of reflectance in urban areas. Based on the urban solar radiative transfer (USRT) model, this study presents a methodology for estimating urban reflectance using the sky view factor (SVF) derived from airborne LiDAR data. Then, the USRT model was used to retrieve urban 3D surface reflectance from Landsat 8 data over the typical area of Beijing. The reflectance from USRT model was compared with the estimated value obtained from the model without considering the impact of morphological characteristics of the urban underlying surface (flat model). The results showed that the urban sample reflectance estimated by the USRT model was close to the sample reflectance of the suburban underlying surface which was less affected by morphological characteristics. The research summaries are as follows: (1) The definite physical meaning is presented in the USRT model, and can be applied to estimate the physical parameters of the urban underlying surface. (2) The reflectance from the USRT model is slightly larger than the reflectance derived from the flat model, which indicates that the accuracy of urban 3D surface reflectance is improved by the USRT model. (3) The effects of the SVF and building reflectance are different. The SVF presents a strong sensitivity to the estimation of the urban 3D surface reflectance, and the variations of building reflectance setting have little impact on urban reflectance, which is characterized by low sensitivity. Generally, the methodology of estimating urban reflectance proposed in this study can better clarify the impact mechanism of urban geometry on the radiative transfer processes and further promote the application and development of urban quantitative remote sensing.
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Lawrence, J. P., R. J. Leigh, and P. S. Monks. "The impact of surface reflectance variability on total column differential absorption LiDAR measurements of atmospheric CO<sub>2</sub>." Atmospheric Measurement Techniques Discussions 3, no. 1 (January 11, 2010): 147–84. http://dx.doi.org/10.5194/amtd-3-147-2010.
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Abstract. The remote sensing technique, total column differential absorption LiDAR (TC-DIAL) has been proposed in a number of feasibility studies as a suitable method for making total column measurements of atmospheric CO2 from space. Among the sources of error associated with TC-DIAL retrievals from space is an undefined modulation of the received signals resulting from the variability in the Earth's surface reflectance between the LiDAR pulses. This source of uncertainty is investigated from a satellite perspective by the application of a computer model for spaceborne TC-DIAL instruments. The simulations are carried out over Europe and South America using modified MODIS surface reflectance maps and a DIAL configuration similar to that suggested for the proposed ESA A-SCOPE mission. A positive bias of 0.01 ppmv in both continental test sets is observed using 10 Hz pulse repetition frequency and 200 km integration distance. This bias is a consequence of non-linearity in the DIAL equation, and in particular regions such as the Alps and over certain coastlines it contributes to positive errors of between 0.05 and 0.16 ppmv for 200 and 50 km integration distances. These retrieval errors are defined as lower bound estimates owing to the likely resolution difference between the surface reflectance data and the expected surface heterogeneity observed by a DIAL instrument.
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Zhang, Z., Z. Zeng, and J. Boehm. "INVESTIGATION OF THE RADIOMETRIC BEHAVIOUR OF A LOW-COST AUTOMOTIVE LIDAR SENSOR." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 777–83. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-777-2023.
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Abstract. Terrestrial LiDAR is an established method for 3D data acquisition in close-range applications. A new category of low-cost LiDAR sensors for autonomous driving has become available with similar specifications. However, these new sensors lack the guarantee of survey-grade performance. Initial experiments have broadly confirmed the specification of one such low-cost sensor but have also raised issues with the radiometric behaviour. This study investigates through practical experiments how the intensity information of the Livox-Mid40 laser scanner is influenced by time, reflectance, distance and angle of incidence. The quantitative analysis of the experiments shows an expected relationship between surface reflectance and recorded intensity. However, the result indicate that intensity can significantly influence the distance measurement at very close ranges.
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Nolin, Anne, and Eugene Mar. "Arctic Sea Ice Surface Roughness Estimated from Multi-Angular Reflectance Satellite Imagery." Remote Sensing 11, no. 1 (December 29, 2018): 50. http://dx.doi.org/10.3390/rs11010050.
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Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer meltponds, and affects ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values were nearly identical for areas with a roughness < 20 cm, but for rougher regions, the MISR-estimated roughness had a narrower range of values than the ATM data. The algorithm was able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-estimated roughness data have a variance about half that of ATM roughness data.
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Lancaster, Redgie S., James D. Spinhirne, and Stephen P. Palm. "Laser pulse reflectance of the ocean surface from the GLAS satellite lidar." Geophysical Research Letters 32, no. 22 (September 16, 2005): n/a. http://dx.doi.org/10.1029/2005gl023732.
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Pang, Yong, and Zengyuan Li. "SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 747–49. http://dx.doi.org/10.5194/isprs-archives-xli-b8-747-2016.
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Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.
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Pang, Yong, and Zengyuan Li. "SUBTROPICAL FOREST BIOMASS ESTIMATION USING AIRBORNE LiDAR AND HYPERSPECTRAL DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 747–49. http://dx.doi.org/10.5194/isprsarchives-xli-b8-747-2016.
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Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF’s (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.
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Nath, Bibhash, and Wenge Ni-Meister. "The Interplay between Canopy Structure and Topography and Its Impacts on Seasonal Variations in Surface Reflectance Patterns in the Boreal Region of Alaska—Implications for Surface Radiation Budget." Remote Sensing 13, no. 16 (August 6, 2021): 3108. http://dx.doi.org/10.3390/rs13163108.
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Forests play an essential role in maintaining the Earth’s overall energy balance. The variability in forest canopy structure, topography, and underneath vegetation background conditions create uncertainty in modeling solar radiation at the Earth’s surface, particularly for boreal regions in high latitude. The purpose of this study is to analyze seasonal variation in visible, near-infrared, and shortwave infrared reflectance with respect to land cover classes, canopy structures, and topography in a boreal region of Alaska. We accomplished this investigation by fusing Landsat 8 images and LiDAR-derived canopy structural data and multivariate statistical analysis. Our study shows that canopy structure and topography interplay and influence reflectance spectra in a complex way, particularly during the snow season. We observed that deciduous trees, also tall with greater rugosity, are more dominant on the southern slope than on the northern slope. Taller trees are typically seen in higher elevations regardless of vegetation types. Surface reflectance in all studied wavelengths shows similar relationships with canopy cover, height, and rugosity, mainly due to close connections between these parameters. Visible and near-infrared reflectance decreases with canopy cover, tree height, and rugosity, especially for the evergreen forest. Deciduous forest shows more considerable variability of surface reflectance in all studied wavelengths, particularly in March, mainly due to the mixing effect of snow and vegetation. The multivariate statistical analysis demonstrates a significant tree shadow effect on surface reflectance for evergreen forests. However, the topographic shadow effect is prominent for deciduous forests during the winter season. These results provide great insight into understanding the role of vegetation structure and topography in surface radiation budget in the boreal region.
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Fuentes, Ignacio, Richard Scalzo, and R. Willem Vervoort. "Volume and uncertainty estimates of on-farm reservoirs using surface reflectance and LiDAR data." Environmental Modelling & Software 143 (September 2021): 105095. http://dx.doi.org/10.1016/j.envsoft.2021.105095.
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Dillon, James, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds. "Mapping surface hoar from near-infrared texture in a laboratory." Cryosphere 18, no. 5 (May 24, 2024): 2557–82. http://dx.doi.org/10.5194/tc-18-2557-2024.
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Abstract. Surface hoar crystals are snow grains that form when water vapor deposits on the snow surface. Once buried, surface hoar creates a weak layer in the snowpack that can later cause large avalanches to occur. The formation and persistence of surface hoar are highly spatiotemporally variable, making its detection difficult. Remote-sensing technology capable of detecting the presence and spatial distribution of surface hoar would be beneficial for avalanche forecasting, but this capability has yet to be developed. Here, we hypothesize that near-infrared (NIR) texture, defined as the spatial variability of reflectance magnitude, may produce an optical signature unique to surface hoar due to the distinct shape and orientation of the grains. We tested this hypothesis by performing reflectance experiments in a controlled cold laboratory environment to evaluate the potential and accuracy of surface hoar mapping from NIR texture using a near-infrared hyperspectral imager (NIR-HSI) and a lidar operating at 1064 nm. We analyzed 41 snow samples, three of which were surface hoar and 38 of which consisted of other grain morphologies. When using NIR-HSI under direct and diffuse illumination, we found that surface hoar displayed higher NIR texture relative to all other grain shapes across numerous spectral bands and a wide range of spatial resolutions (0.5–50 mm). Due to the large number of spectral- and spatial-resolution combinations, we conducted a detailed samplewise case study at 1324 nm spectral and 10 mm spatial resolution. The case study resulted in the median texture of surface hoar being 1.3 to 8.6 times greater than that of the 38 other samples under direct and diffuse illumination (p < 0.05 in all cases). Using lidar, surface hoar also exhibited significantly increased NIR texture in 30 out of 38 samples, but only at select (5–25 mm) spatial resolutions. Leveraging these results, we propose a simple binary classification algorithm to map the extent of surface hoar on a pixelwise basis using both the NIR-HSI and lidar instruments. The NIR-HSI under direct and diffuse illumination performed best, with a median accuracy of 96.91 % and 97.37 %, respectively. Conversely, the median classification accuracy achieved with lidar was only 66.99 %. Further, to assess the repeatability of our method and demonstrate its mapping capacity, we ran the algorithm on a new sample with mixed microstructures, with an accuracy of 99.61 % and 96.15 % achieved using NIR-HSI under direct and diffuse illumination, respectively. As NIR-HSI detectors become increasingly available, our findings demonstrate the potential of a new tool for avalanche forecasters to remotely assess the spatiotemporal variability of surface hoar, which would improve avalanche forecasts and potentially save lives.
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Mao, Jianping, Anand Ramanathan, James B. Abshire, Stephan R. Kawa, Haris Riris, Graham R. Allan, Michael Rodriguez, et al. "Measurement of atmospheric CO<sub>2</sub> column concentrations to cloud tops with a pulsed multi-wavelength airborne lidar." Atmospheric Measurement Techniques 11, no. 1 (January 10, 2018): 127–40. http://dx.doi.org/10.5194/amt-11-127-2018.
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Abstract. We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was ∼ 5 % for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 µs wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90 % of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.
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Menzies, Robert T., David M. Tratt, and William H. Hunt. "Lidar In-space Technology Experiment measurements of sea surface directional reflectance and the link to surface wind speed." Applied Optics 37, no. 24 (August 20, 1998): 5550. http://dx.doi.org/10.1364/ao.37.005550.
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Bates, Jordan Steven, Carsten Montzka, Marius Schmidt, and François Jonard. "Estimating Canopy Density Parameters Time-Series for Winter Wheat Using UAS Mounted LiDAR." Remote Sensing 13, no. 4 (February 15, 2021): 710. http://dx.doi.org/10.3390/rs13040710.
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Monitoring of canopy density with related metrics such as leaf area index (LAI) makes a significant contribution to understanding and predicting processes in the soil–plant–atmosphere system and to indicating crop health and potential yield for farm management. Remote sensing methods using optical sensors that rely on spectral reflectance to calculate LAI have become more mainstream due to easy entry and availability. Methods with vegetation indices (VI) based on multispectral reflectance data essentially measure the green area index (GAI) or response to chlorophyll content of the canopy surface and not the entire aboveground biomass that may be present from non-green elements that are key to fully assessing the carbon budget. Methods with light detection and ranging (LiDAR) have started to emerge using gap fraction (GF) to estimate the plant area index (PAI) based on canopy density. These LiDAR methods have the main advantage of being sensitive to both green and non-green plant elements. They have primarily been applied to forest cover with manned airborne LiDAR systems (ALS) and have yet to be used extensively with crops such as winter wheat using LiDAR on unmanned aircraft systems (UAS). This study contributes to a better understanding of the potential of LiDAR as a tool to estimate canopy structure in precision farming. The LiDAR method proved to have a high to moderate correlation in spatial variation to the multispectral method. The LiDAR-derived PAI values closely resemble the SunScan Ceptometer GAI ground measurements taken early in the growing season before major stages of senescence. Later in the growing season, when the canopy density was at its highest, a possible overestimation may have occurred. This was most likely due to the chosen flight parameters not providing the best depictions of canopy density with consideration of the LiDAR’s perspective, as the ground-based destructive measurements provided lower values of PAI. Additionally, a distinction between total LiDAR-derived PAI, multispectral-derived GAI, and brown area index (BAI) is made to show how the active and passive optical sensor methods used in this study can complement each other throughout the growing season.
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Abshire, James B., Anand K. Ramanathan, Haris Riris, Graham R. Allan, Xiaoli Sun, William E. Hasselbrack, Jianping Mao, et al. "Airborne measurements of CO<sub>2</sub> column concentrations made with a pulsed IPDA lidar using a multiple-wavelength-locked laser and HgCdTe APD detector." Atmospheric Measurement Techniques 11, no. 4 (April 10, 2018): 2001–25. http://dx.doi.org/10.5194/amt-11-2001-2018.
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Abstract. Here we report on measurements made with an improved CO2 Sounder lidar during the ASCENDS 2014 and 2016 airborne campaigns. The changes made to the 2011 version of the lidar included incorporating a rapidly wavelength-tunable, step-locked seed laser in the transmitter, using a much more sensitive HgCdTe APD detector and using an analog digitizer with faster readout time in the receiver. We also improved the lidar's calibration approach and the XCO2 retrieval algorithm. The 2014 and 2016 flights were made over several types of topographic surfaces from 3 to 12 km aircraft altitudes in the continental US. The results are compared to the XCO2 values computed from an airborne in situ sensor during spiral-down maneuvers. The 2014 results show significantly better performance and include measurement of horizontal gradients in XCO2 made over the Midwestern US that agree with chemistry transport models. The results from the 2016 airborne lidar retrievals show precisions of ∼ 0.7 parts per million (ppm) with 1 s averaging over desert surfaces, which is an improvement of about 8 times compared to similar measurements made in 2011. Measurements in 2016 were also made over fresh snow surfaces that have lower surface reflectance at the laser wavelengths. The results from both campaigns showed that the mean values of XCO2 retrieved from the lidar consistently agreed with those based on the in situ sensor to within 1 ppm. The improved precision and accuracy demonstrated in the 2014 and 2016 flights should benefit future airborne science campaigns and advance the technique's readiness for a space-based instrument.
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Gardi, Alessandro, Roberto Sabatini, and Subramanian Ramasamy. "Bistatic LIDAR System for the Characterisation of Aviation-Related Pollutant Column Densities." Applied Mechanics and Materials 629 (October 2014): 257–62. http://dx.doi.org/10.4028/www.scientific.net/amm.629.257.
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In this paper, we investigate an innovative application of Light Detection and Ranging (LIDAR) technology for the aviation-related pollutant measurements. The proposed measurement technique is conceived for high-resolution characterisation in space and time domains of aviation-related pollutant gases. The system performs Integral Path Differential Absorption (IPDA) measurement in a bistatic LIDAR measurement setup. The airborne component consists of a tuneable Near Infrared (NIR) laser emitter installed on an Unmanned Aircraft (UA) and the ground subsystem is composed by a target reference surface (calibrated for reflectance) and a differential transmittance measuring device based on a NIR Camera calibrated for radiance. The specific system implementation for Carbon Dioxide (CO2) measurement is discussed. A preliminary assessment of the error figures associated with the proposed system layout is performed.
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Tian Wenxin, 田汶鑫, 陈育伟 Chen Yuwei, 唐伶俐 Tang Lingli, 李子扬 Li Ziyang, 邱实 Qiu Shi, 吴昊昊 Wu Haohao, 张慧静 Zhang Huijing, et al. "高光谱激光雷达后向散射强度的粗糙表面二向反射模型." Infrared and Laser Engineering 52, no. 10 (2023): 20230108. http://dx.doi.org/10.3788/irla20230108.
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Saylam, Kutalmis, Alejandra Briseno, Aaron R. Averett, and John R. Andrews. "Analysis of Depths Derived by Airborne Lidar and Satellite Imaging to Support Bathymetric Mapping Efforts with Varying Environmental Conditions: Lower Laguna Madre, Gulf of Mexico." Remote Sensing 15, no. 24 (December 16, 2023): 5754. http://dx.doi.org/10.3390/rs15245754.
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In 2017, Bureau of Economic Geology (BEG) researchers at the University of Texas at Austin (UT Austin) conducted an airborne lidar survey campaign, collecting topographic and bathymetric data over Lower Laguna Madre, which is a shallow hypersaline lagoon in south Texas. Researchers acquired 60 hours of lidar data, covering an area of 1600 km2 with varying environmental conditions influencing water quality and surface heights. In the southernmost parts of the lagoon, in-situ measurements were collected from a boat to quantify turbidity, water transparency, and depths. Data analysis included processing of Sentinel-2 L1C satellite imagery pixel reflectance to classify locations with intermittent turbidity. Lidar measurements were compared to sonar recordings, and results revealed height differences of 5–25 cm where the lagoon was shallower than 3.35 m. Further, researchers analyzed satellite bathymetry at relatively transparent lagoon locations, and the results produced height agreement within 13 cm. The study concluded that bathymetric efforts with airborne lidar and optical satellite imaging have practical limitations and comparable results in large and dynamic shallow coastal estuaries, where in-situ measurements and tide adjustments are essential for height comparisons.
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Wang, Shupeng, Li Fang, Weishu Gong, Weihe Wang, and Shihao Tang. "Retrieval of Aerosol Optical Depth and FMF over East Asia from Directional Intensity and Polarization Measurements of PARASOL." Atmosphere 15, no. 1 (December 20, 2023): 6. http://dx.doi.org/10.3390/atmos15010006.
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The advantages of performing aerosol retrieval with multi-angle, multi-spectral photopolarimetric measurements over intensity-only measurements come from this technique’s sensitivity to aerosols’ microphysical properties, such as their particle size, shape, and complex refraction index. In this study, an extended LUT (Look Up Table) algorithm inherited from a previous work based on the assumption of surface reflectance spectral shape invariance is proposed and applied to PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) measurements to retrieve aerosols’ optical properties including aerosol optical depth (AOD) and aerosol fine-mode fraction (FMF). Case studies conducted over East China for different aerosol scenes are investigated. A comparison between the retrieved AOD regional distribution and the corresponding MODIS (Moderate-resolution Imaging Spectroradiometer) C6 AOD products shows similar spatial distributions in the Jing-Jin-Ji (Beijing–Tianjin–Hebei, China’s mega city cluster) region. The PARASOL AOD retrievals were compared against the AOD measurements of seven AERONET (Aerosol Robotic Network) stations in China to evaluate the performance of the retrieval algorithm. In the fine-particle-dominated regions, lower RMSEs were found at Beijing and Hefei urban stations (0.16 and 0.18, respectively) compared to those at other fine-particle-dominated AERONET stations, which can be attributed to the assumption of surface reflectance spectral shape invariance that has significant advantages in separating the contribution of surface and aerosol scattering in urban areas. For the FMF validation, an RMSE of 0.23, a correlation of 0.57, and a bias of −0.01 were found. These results show that the algorithm performs reasonably in distinguishing the contribution of fine and coarse particles.
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Knobelspiesse, Kirk, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, et al. "The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign." Earth System Science Data 12, no. 3 (September 14, 2020): 2183–208. http://dx.doi.org/10.5194/essd-12-2183-2020.
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Abstract. In the fall of 2017, an airborne field campaign was conducted from the NASA Armstrong Flight Research Center in Palmdale, California, to advance the remote sensing of aerosols and clouds with multi-angle polarimeters (MAP) and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign was jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEX airborne), and the Research Scanning Polarimeter (RSP). The remainder were lidars, including the Cloud Physics Lidar (CPL) and the High Spectral Resolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabled observation of a wide variety of scene types, including urban, desert, forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted, and pristine atmospheric conditions. Flights were performed in coordination with satellite overpasses and ground-based observations, including the Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sun photometers, and a surface reflectance spectrometer. ACEPOL is a resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. Data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion. They are freely available to the public. The DOI for the primary database is https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001 (ACEPOL Science Team, 2017), while for AirMSPI it is https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006 and https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006 (ACEPOL AirMSPI 75 Science Team, 2017a, b). GroundMSPI data are at https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009 (GroundMSPI Science Team, 2017). Table 3 lists further details of these archives. This paper describes ACEPOL for potential data users and also provides an outline of requirements for future field missions with similar objectives.
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Tian, Wenxin, Lingli Tang, Yuwei Chen, Ziyang Li, Jiajia Zhu, Changhui Jiang, Peilun Hu, et al. "Analysis and Radiometric Calibration for Backscatter Intensity of Hyperspectral LiDAR Caused by Incident Angle Effect." Sensors 21, no. 9 (April 23, 2021): 2960. http://dx.doi.org/10.3390/s21092960.
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Hyperspectral LiDAR (HSL) is a new remote sensing detection method with high spatial and spectral information detection ability. In the process of laser scanning, the laser echo intensity is affected by many factors. Therefore, it is necessary to calibrate the backscatter intensity data of HSL. Laser incidence angle is one of the important factors that affect the backscatter intensity of the target. This paper studied the radiometric calibration method of incidence angle effect for HSL. The reflectance of natural surfaces can be simulated as a combination of specular reflection and diffuse reflection. The linear combination of the Lambertian model and Beckmann model provides a comprehensive theory that can be applied to various surface conditions, from glossy to rough surfaces. Therefore, an adaptive threshold radiometric calibration method (Lambertian–Beckmann model) is proposed to solve the problem caused by the incident angle effect. The relationship between backscatter intensity and incident angle of HSL is studied by combining theory with experiments, and the model successfully quantifies the difference between diffuse and specular reflectance coefficients. Compared with the Lambertian model, the proposed model has higher calibration accuracy, and the average improvement rate to the samples in this study was 22.67%. Compared with the results before calibration with the incidence angle of less than 70°, the average improvement rate of the Lambertian–Beckmann model was 62.26%. Moreover, we also found that the green leaves have an obvious specular reflection effect near 650–720 nm, which might be related to the inner microstructure of chlorophyll. The Lambertian–Beckmann model was more helpful to the calibration of leaves in the visible wavelength range. This is a meaningful and a breakthrough exploration for HSL.
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Becek, K., A. Borkowski, and Ç. Mekik. "A STUDY OF THE IMPACT OF INSOLATION ON REMOTE SENSING-BASED LANDCOVER AND LANDUSE DATA EXTRACTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 65–69. http://dx.doi.org/10.5194/isprs-archives-xli-b7-65-2016.
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We examined the dependency of the pixel reflectance of hyperspectral imaging spectrometer data (HISD) on a normalized total insolation index (NTII). The NTII was estimated using a light detection and ranging (LiDAR)-derived digital surface model (DSM). The NTII and the pixel reflectance were dependent, to various degrees, on the band considered, and on the properties of the objects. The findings could be used to improve land cover (LC)/land use (LU) classification, using indices constructed from the spectral bands of imaging spectrometer data (ISD). To study this possibility, we investigated the normalized difference vegetation index (NDVI) at various NTII levels. The results also suggest that the dependency of the pixel reflectance and NTII could be used to mitigate the shadows in ISD. This project was carried out using data provided by the Hyperspectral Image Analysis Group and the NSF-funded Centre for Airborne Laser Mapping (NCALM), University of Houston, for the purpose of organizing the 2013 Data Fusion Contest (IEEE 2014). This contest was organized by the IEEE GRSS Data Fusion Technical Committee.
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Becek, K., A. Borkowski, and Ç. Mekik. "A STUDY OF THE IMPACT OF INSOLATION ON REMOTE SENSING-BASED LANDCOVER AND LANDUSE DATA EXTRACTION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 65–69. http://dx.doi.org/10.5194/isprsarchives-xli-b7-65-2016.
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We examined the dependency of the pixel reflectance of hyperspectral imaging spectrometer data (HISD) on a normalized total insolation index (NTII). The NTII was estimated using a light detection and ranging (LiDAR)-derived digital surface model (DSM). The NTII and the pixel reflectance were dependent, to various degrees, on the band considered, and on the properties of the objects. The findings could be used to improve land cover (LC)/land use (LU) classification, using indices constructed from the spectral bands of imaging spectrometer data (ISD). To study this possibility, we investigated the normalized difference vegetation index (NDVI) at various NTII levels. The results also suggest that the dependency of the pixel reflectance and NTII could be used to mitigate the shadows in ISD. This project was carried out using data provided by the Hyperspectral Image Analysis Group and the NSF-funded Centre for Airborne Laser Mapping (NCALM), University of Houston, for the purpose of organizing the 2013 Data Fusion Contest (IEEE 2014). This contest was organized by the IEEE GRSS Data Fusion Technical Committee.
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Kiemle, C., M. Quatrevalet, G. Ehret, A. Amediek, A. Fix, and M. Wirth. "Sensitivity studies for a space-based methane lidar mission." Atmospheric Measurement Techniques Discussions 4, no. 3 (June 9, 2011): 3545–92. http://dx.doi.org/10.5194/amtd-4-3545-2011.
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Abstract. Methane is the third most important greenhouse gas in the atmosphere after water vapour and carbon dioxide. A major handicap to quantify the emissions at the Earth's surface in order to better understand biosphere-atmosphere exchange processes and potential climate feedbacks is the lack of accurate and global observations of methane. Space-based integrated path differential absorption (IPDA) lidar has potential to fill this gap, and a Methane Remote Lidar Mission (MERLIN) on a small satellite in Polar orbit was proposed by DLR and CNES in the frame of a German-French climate monitoring initiative. System simulations are used to identify key performance parameters and to find an advantageous instrument configuration, given the environmental, technological, and budget constraints. The sensitivity studies use representative averages of the atmospheric and surface state to estimate the measurement precision, i.e. the random uncertainty due to instrument noise. Key performance parameters for MERLIN are average laser power, telescope size, orbit height, surface reflectance, and detector noise. A modest-size lidar instrument with 0.45 W average laser power and 0.55 m telescope diameter on a 506 km orbit could provide 50-km averaged methane column measurement along the sub-satellite track with a precision of about 1 % over vegetation. The use of a methane absorption trough at 1.65 μm improves the near-surface measurement sensitivity and vastly relaxes the wavelength stability requirement that was identified as one of the major technological risks in the pre-phase A studies for A-SCOPE, a space-based IPDA lidar for carbon dioxide at the European Space Agency. Minimal humidity and temperature sensitivity at this wavelength position will enable accurate measurements in tropical wetlands, key regions with largely uncertain methane emissions. In contrast to actual passive remote sensors, measurements in Polar Regions will be possible and biases due to aerosol layers and thin ice clouds will be minimised.
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Kiemle, C., M. Quatrevalet, G. Ehret, A. Amediek, A. Fix, and M. Wirth. "Sensitivity studies for a space-based methane lidar mission." Atmospheric Measurement Techniques 4, no. 10 (October 18, 2011): 2195–211. http://dx.doi.org/10.5194/amt-4-2195-2011.
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Abstract. Methane is the third most important greenhouse gas in the atmosphere after water vapour and carbon dioxide. A major handicap to quantify the emissions at the Earth's surface in order to better understand biosphere-atmosphere exchange processes and potential climate feedbacks is the lack of accurate and global observations of methane. Space-based integrated path differential absorption (IPDA) lidar has potential to fill this gap, and a Methane Remote Lidar Mission (MERLIN) on a small satellite in polar orbit was proposed by DLR and CNES in the frame of a German-French climate monitoring initiative. System simulations are used to identify key performance parameters and to find an advantageous instrument configuration, given the environmental, technological, and budget constraints. The sensitivity studies use representative averages of the atmospheric and surface state to estimate the measurement precision, i.e. the random uncertainty due to instrument noise. Key performance parameters for MERLIN are average laser power, telescope size, orbit height, surface reflectance, and detector noise. A modest-size lidar instrument with 0.45 W average laser power and 0.55 m telescope diameter on a 506 km orbit could provide 50-km averaged methane column measurement along the sub-satellite track with a precision of about 1% over vegetation. The use of a methane absorption trough at 1.65 μm improves the near-surface measurement sensitivity and vastly relaxes the wavelength stability requirement that was identified as one of the major technological risks in the pre-phase A studies for A-SCOPE, a space-based IPDA lidar for carbon dioxide at the European Space Agency. Minimal humidity and temperature sensitivity at this wavelength position will enable accurate measurements in tropical wetlands, key regions with largely uncertain methane emissions. In contrast to actual passive remote sensors, measurements in Polar Regions will be possible and biases due to aerosol layers and thin ice clouds will be minimised.
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Cho, Hyoun-Myoung, Shaima L. Nasiri, Ping Yang, Istvan Laszlo, and Xuepeng “Tom” Zhao. "Detection of Optically Thin Mineral Dust Aerosol Layers over the Ocean Using MODIS." Journal of Atmospheric and Oceanic Technology 30, no. 5 (May 1, 2013): 896–916. http://dx.doi.org/10.1175/jtech-d-12-00079.1.
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Abstract Analyses show that several existing Moderate Resolution Imaging Spectroradiometer (MODIS) dust detection techniques, including an approach based on simple brightness temperature difference thresholds, the D-parameter method, and the multichannel image (MCI) algorithm, may be more effective for detection of highly concentrated dust plumes than for thin dust layers. Using the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud and aerosol classification as a reference, the sensitivities of six MODIS radiative parameters (including brightness temperature differences, and standard deviation and ratios of reflectances) to cloud, clear sky, and dust layers are examined in this paper. Reflectance ratios and the standard deviation of reflectances were confirmed to be useful in the discrimination of dust from cloud and underlying ocean surface, while brightness temperature differences alone were not sufficient to separate dust from cloud and clear sky over the ocean surface. Using a collocated MODIS and CALIPSO training dataset from 2008, visible and infrared MODIS radiative parameters from six latitude bands and four seasons were combined using linear and quadratic discriminant analyses to develop a new algorithm for the detection of optically thin dust over the ocean. The validation using collocated MODIS and CALIPSO data from 2009 shows that the present algorithm is effective in detecting thin dust layers having optical thicknesses between 0.1 and 2.0, but that it tends to misclassify optically thicker dust layers as clouds.
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Shi, Zheng, Tingyan Xing, Jie Guang, Yong Xue, and Yahui Che. "Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations." Remote Sensing 11, no. 8 (April 12, 2019): 891. http://dx.doi.org/10.3390/rs11080891.
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Aerosol properties over the Arctic snow-covered regions are sparsely provided by temporal and spatially limited in situ measurements or active Lidar observations. This introduces large uncertainties for the understanding of aerosol effects on Arctic climate change. In this paper, aerosol optical depth (AOD) is derived using the advanced along-track scanning radiometer (AATSR) instrument. The basic idea is to utilize the dual-viewing observation capability of AATSR to reduce the impacts of AOD uncertainties introduced by the absolute wavelength-dependent error on surface reflectance estimation. AOD is derived assuming that the satellite observed surface reflectance ratio can be well characterized by a snow bidirectional reflectance distribution function (BRDF) model with a certain correction direct from satellite top of the atmosphere (TOA) observation. The aerosol types include an Arctic haze aerosol obtained from campaign measurement and Arctic background aerosol (maritime aerosol) types. The proper aerosol type is selected during the iteration step based on the minimization residual. The algorithm has been used over Spitsbergen for the spring period (April–May) and the AOD spatial distribution indicates that the retrieval AOD can capture the Arctic haze event. The comparison with AERONET observations shows promising results, with a correlation coefficient R = 0.70. The time series analysis shows no systematical biases between AATSR retrieved AOD and AERONET observed ones.
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Yu, Hengwei, Long Wang, Jiqing Xu, and Patrick Yin Chiang. "A dToF Ranging Sensor with Accurate Photon Detector Measurements for LiDAR Applications." Sensors 23, no. 6 (March 10, 2023): 3011. http://dx.doi.org/10.3390/s23063011.
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Direct time-of-flight (dToF) ranging sensors based on single-photon avalanche diodes (SPADs) have been used as a prominent depth-sensing devices. Time-to-digital converters (TDCs) and histogram builders have become the standard for dToF sensors. However, one of the main current issues is the bin width of the histogram, which limits the accuracy of depth without TDC architecture modifications. SPAD-based light detection and ranging (LiDAR) systems require new methods to overcome their inherent drawbacks for accurate 3D ranging. In this work, we report an optimal matched filter to process the raw data of the histogram to obtain high-accuracy depth. This method is performed by feeding the raw data of the histogram into the different matched filters and using the Center-of-Mass (CoM) algorithm for depth extraction. Comparing the measurement results of different matched filters, the filter with the highest depth accuracy can be obtained. Finally, we implemented a dToF system-on-chip (SoC) ranging sensor. The sensor is made of a configurable array of 16 × 16 SPADs, a 940 nm vertical-cavity surface-emitting laser (VCSEL), an integrated VCSEL driver, and an embedded microcontroller unit (MCU) core to implement the best matched filter. To achieve suitably high reliability and low cost, the above-mentioned features are all packaged into one module for ranging. The system resulted in a precision of better than 5 mm within 6 m with 80% reflectance of the target, and had a precision better than 8 mm at a distance within 4 m with 18% reflectance of the target.
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Lee, Soobong, and Jaewan Choi. "Daytime Cloud Detection Algorithm Based on a Multitemporal Dataset for GK-2A Imagery." Remote Sensing 13, no. 16 (August 13, 2021): 3215. http://dx.doi.org/10.3390/rs13163215.
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Cloud detection is an essential and important process in remote sensing when surface information is required for various fields. For this reason, we developed a daytime cloud detection algorithm for GEOstationary KOrea Multi-Purpose SATellite 2A (GEO-KOMPSAT-2A, GK-2A) imagery. For each pixel, the filtering technique using angular variance, which denotes the change in top of atmosphere (TOA) reflectance over time, was applied, and filtering technique by using the minimum TOA reflectance was used to remove remaining cloud pixels. Furthermore, near-infrared (NIR) and normalized difference vegetation index (NDVI) images were applied with dynamic thresholds to improve the accuracy of the cloud detection results. The quantitative results showed that the overall accuracy of proposed cloud detection was 0.88 and 0.92 with Visible Infrared Imaging Radiometer Suite (VIIRS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), respectively, and indicated that the proposed algorithm has good performance in detecting clouds.
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Juxin Yang, 杨巨鑫, 朱亚丹 Yadan Zhu, 王勤 Qin Wang, 卜令兵 Lingbing Bu, 刘继桥 Jiqiao Liu, and 陈卫标 Weibiao Chen. "Influence of Surface Reflectance and Aerosol Optical Depth on Performance of Spaceborne Integral Path Differential Absorption Lidar." Chinese Journal of Lasers 46, no. 9 (2019): 0910001. http://dx.doi.org/10.3788/cjl201946.0910001.
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Kim, Minsu, Jeff Danielson, Curt Storlazzi, and Seonkyung Park. "Physics-Based Satellite-Derived Bathymetry (SDB) Using Landsat OLI Images." Remote Sensing 16, no. 5 (February 28, 2024): 843. http://dx.doi.org/10.3390/rs16050843.
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The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance.
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Bretar, F., A. Chauve, J. S. Bailly, C. Mallet, and A. Jacome. "Terrain surfaces and 3-D landcover classification from small footprint full-waveform lidar data: application to badlands." Hydrology and Earth System Sciences Discussions 6, no. 1 (January 6, 2009): 151–205. http://dx.doi.org/10.5194/hessd-6-151-2009.
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Abstract. This article presents the use of new remote sensing data acquired from airborne full-waveform lidar systems. They are active sensors which record altimeter profiles. This paper introduces a set of methodologies for processing these data. These techniques are then applied to a particular landscape, the badlands, but the methodologies are designed to be applied to any other landscape. Indeed, the knowledge of an accurate topography and a landcover classification is a prior knowledge for any hydrological and erosion model. Badlands tend to be the most significant areas of erosion in the world with the highest erosion rate values. Monitoring and predicting erosion within badland mountainous catchments is highly strategic due to the arising downstream consequences and the need for natural hazard mitigation engineering. Additionaly, beyond the altimeter information, full-waveform lidar data are processed to extract intensity and width of echoes. They are related to the target reflectance and geometry. Wa will investigate the relevancy of using lidar-derived Digital Terrain Models (DTMs) and to investigate the potentiality of the intensity and width information for 3-D landcover classification. Considering the novelty and the complexity of such data, they are presented in details as well as guidelines to process them. DTMs are then validated with field measurements. The morphological validation of DTMs is then performed via the computation of hydrological indexes and photo-interpretation. Finally, a 3-D landcover classification is performed using a Support Vector Machine classifier. The introduction of an ortho-rectified optical image in the classification process as well as full-waveform lidar data for hydrological purposes is then discussed.
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Cooper, Matthew, and Laurence Smith. "Satellite Remote Sensing of the Greenland Ice Sheet Ablation Zone: A Review." Remote Sensing 11, no. 20 (October 16, 2019): 2405. http://dx.doi.org/10.3390/rs11202405.
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The Greenland Ice Sheet is now the largest land ice contributor to global sea level rise, largely driven by increased surface meltwater runoff from the ablation zone, i.e., areas of the ice sheet where annual mass losses exceed gains. This small but critically important area of the ice sheet has expanded in size by ~50% since the early 1960s, and satellite remote sensing is a powerful tool for monitoring the physical processes that influence its surface mass balance. This review synthesizes key remote sensing methods and scientific findings from satellite remote sensing of the Greenland Ice Sheet ablation zone, covering progress in (1) radar altimetry, (2) laser (lidar) altimetry, (3) gravimetry, (4) multispectral optical imagery, and (5) microwave and thermal imagery. Physical characteristics and quantities examined include surface elevation change, gravimetric mass balance, reflectance, albedo, and mapping of surface melt extent and glaciological facies and zones. The review concludes that future progress will benefit most from methods that combine multi-sensor, multi-wavelength, and cross-platform datasets designed to discriminate the widely varying surface processes in the ablation zone. Specific examples include fusing laser altimetry, radar altimetry, and optical stereophotogrammetry to enhance spatial measurement density, cross-validate surface elevation change, and diagnose radar elevation bias; employing dual-frequency radar, microwave scatterometry, or combining radar and laser altimetry to map seasonal snow depth; fusing optical imagery, radar imagery, and microwave scatterometry to discriminate between snow, liquid water, refrozen meltwater, and bare ice near the equilibrium line altitude; combining optical reflectance with laser altimetry to map supraglacial lake, stream, and crevasse bathymetry; and monitoring the inland migration of snowlines, surface melt extent, and supraglacial hydrologic features.
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Fricke, C., A. Ehrlich, E. Jäkel, B. Bohn, M. Wirth, and M. Wendisch. "Influence of surface albedo heterogeneity on passive remote sensing of cirrus properties." Atmospheric Chemistry and Physics Discussions 13, no. 2 (February 11, 2013): 3783–816. http://dx.doi.org/10.5194/acpd-13-3783-2013.
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Abstract. Airborne measurements of solar spectral radiance reflected by cirrus are performed with the HALO-SR instrument onboard the High Altitude and Long Range Research Aircraft (HALO) in November 2010. The data are used to quantify the influence of surface albedo heterogeneities on the retrieval of cirrus optical thickness and crystal effective radius. Based on radiative transfer calculations the cirrus properties are derived using a standard bispectral retrieval method. Frequency distributions of the surface albedos derived from MODIS satellite observations are used to create albedo dependend lookup tables of reflected radiance. For each albedo respectively lookup table, a corresponding result for the cirrus optical thickness and effective radius is retrieved. The retrieved cloud properties are analysed in a statistical manner to investigate the influence of surface albedo heterogeneities. The results for the cirrus optical thickness are compared to HSRL-lidar derived values which allows to investigate the role of ice crystal shape in addition. It is found that if assuming aggregate ice crystals the HSRL-lidar observations fit best to the retrieved optical thickness using spectral radiance. The uncertainty in cirrus optical thickness due to uncertainties in the surface albedo is below 0.1 and thus below the instrument uncertainty. Therefor, it is concluded that for the retrieval of cirrus optical thickness the surface albedo heterogeneity is negligible. For the retrieval of cirrus effective radius, the surface albedo is of importance introducing uncertainties up to 50%. However, it was be shown that the influence of the bidirectional reflectance distribution function (BRDF) is below 10% and thus smaller than the uncertainty caused by the surface albedo.
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Barnes, Celeste, Chris Hopkinson, Thomas Porter, and Zhouxin Xi. "In-Situ LED-Based Observation of Snow Surface and Depth Transects." Sensors 20, no. 8 (April 17, 2020): 2292. http://dx.doi.org/10.3390/s20082292.
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As part of a new snowpack monitoring framework, this study evaluated the feasibility of using an LED LIDAR (Leddar) time of flight sensor for snowpack depth measurement. The Leddar sensor has two additional features over simple sonic ranging sensors: (i) the return signal is divided into 16 segments across a 48° field of view, each recording individual distance-to-target (DTT) measurements; (ii) an index of reflectance or intensity signal is recorded for each segment. These two features provide information describing snowpack morphology and surface condition. The accuracy of Leddar sensor DTT measurements for snow depth monitoring was found to be < 20 mm, which was better than the 50 mm quoted by the manufacturer, and the precision was < 5 mm. Leddar and independent sonic ranger snow depth measurement showed strong linear agreement (r2 = 0.98). There was also a strong linear relationship (r2 = 0.98) between Leddar and manual field snow depth measurements. The intensity signal response was found to correlate with snow surface albedo and inversely with air temperature (r = 0.77 and −0.77, respectively).
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Luan, Chenglong, Yingchun Li, Huichao Guo, Houpeng Sun, Laixian Zhang, Haijing Zheng, and Xiaoyu Zhang. "Modified Model of Polarized Bidirectional Reflectance Distribution Function Used for Light Detection and Ranging (LiDAR)." Photonics 10, no. 10 (October 4, 2023): 1119. http://dx.doi.org/10.3390/photonics10101119.
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In order to analyze the performance of a light detection and ranging system based on polarization modulation, it is necessary to theoretically analyze and model the polarization scattering characteristics of common target materials. In this paper, the shortcomings of the classical Hyde pBRDF (polarization bidirectional reflectance distribution function) model are analyzed. Based on the research results of many researchers in recent years, a new six-parameter pBRDF model is proposed. To verify the accuracy of the proposed model, this paper builds a measurement system for the polarization scattering characteristics of the target surface in the laser active imaging scene, and the polarization scattering characteristics of two common materials, namely a white paint coating and an aluminum plate, are measured. Based on the measurement results of the DOP (degree of polarization) of the scattered light of the target material and the BBO-FA (biogeography-based optimization-Firefly algorithm) algorithm, we performed inversion calculations on the key parameters of the target material. Using the parameters of the target material obtained via inversion, we use the model to simulate the Stokes vectors of the target and compare the simulated values of Stokes vectors with the measured values to verify the accuracy of the model. The verification results show that the simulation results of Stokes vectors are in good agreement with the measurement results for these two materials, and the introduction of various improvements to the model can effectively improve the accuracy of the model, which provides a tool for studying the performance parameters of a laser three-dimensional imaging system based on polarization modulation.
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Ma, Yue, Wenhao Zhang, Jinyan Sun, Guoyuan Li, Xiao Wang, Song Li, and Nan Xu. "Photon-Counting Lidar: An Adaptive Signal Detection Method for Different Land Cover Types in Coastal Areas." Remote Sensing 11, no. 4 (February 25, 2019): 471. http://dx.doi.org/10.3390/rs11040471.
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Airborne or space-borne photon-counting lidar can provide successive photon clouds of the Earth’s surface. The distribution and density of signal photons are very different because different land cover types have different surface profiles and reflectance, especially in coastal areas where the land cover types are various and complex. A new adaptive signal photon detection method is proposed to extract the signal photons for different land cover types from the raw photons captured by the MABEL (Multiple Altimeter Beam Experimental Lidar) photon-counting lidar in coastal areas. First, the surface types with 30 m resolution are obtained via matching the geographic coordinates of the MABEL trajectory with the NLCD (National Land Cover Database) datasets. Second, in each along-track segment with a specific land cover type, an improved DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm with adaptive thresholds and a JONSWAP (Joint North Sea Wave Project) wave algorithm is proposed and integrated to detect signal photons on different surface types. The result in Pamlico Sound indicates that this new method can effectively detect signal photons and successfully eliminate noise photons below the water level, whereas the MABEL result failed to extract the signal photons in vegetation segments and failed to discard the after-pulsing noise photons. In the Atlantic Ocean and Pamlico Sound, the errors of the RMS (Root Mean Square) wave height between our result and in-situ result are −0.06 m and 0.00 m, respectively. However, between the MABEL and in-situ result, the errors are −0.44 m and −0.37 m, respectively. The mean vegetation height between the East Lake and Pamlico Sound was also calculated as 15.17 m using the detecting signal photons from our method, which agrees well with the results (15.56 m) from the GFCH (Global Forest Canopy Height) dataset. Overall, for different land cover types in coastal areas, our study indicates that the proposed method can significantly improve the performance of the signal photon detection for photon-counting lidar data, and the detected signal photons can further obtain the water levels and vegetation heights. The proposed approach can also be extended for ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) datasets in the future.
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Fricke, C., A. Ehrlich, E. Jäkel, B. Bohn, M. Wirth, and M. Wendisch. "Influence of local surface albedo variability and ice crystal shape on passive remote sensing of thin cirrus." Atmospheric Chemistry and Physics 14, no. 4 (February 20, 2014): 1943–58. http://dx.doi.org/10.5194/acp-14-1943-2014.
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Abstract. Airborne measurements of solar spectral radiance reflected by cirrus are performed with the HALO-Solar Radiation (HALO-SR) instrument onboard the High Altitude and Long Range Research Aircraft (HALO) in November 2010. The data are used to quantify the influence of surface albedo variability on the retrieval of cirrus optical thickness and crystal effective radius. The applied retrieval of cirrus optical properties is based on a standard two-wavelength approach utilizing measured and simulated reflected radiance in the visible and near-infrared spectral region. Frequency distributions of the surface albedos from Moderate resolution Imaging Spectroradiometer (MODIS) satellite observations are used to compile surface-albedo-dependent lookup tables of reflected radiance. For each assumed surface albedo the cirrus optical thickness and effective crystal radius are retrieved as a function of the assumed surface albedo. The results for the cirrus optical thickness are compared to measurements from the High Spectral Resolution Lidar (HSRL). The uncertainty in cirrus optical thickness due to local variability of surface albedo in the specific case study investigated here is below 0.1 and thus less than that caused by the measurement uncertainty of both instruments. It is concluded that for the retrieval of cirrus optical thickness the surface albedo variability is negligible. However, for the retrieval of crystal effective radius, the surface albedo variability is of major importance, introducing uncertainties up to 50%. Furthermore, the influence of the bidirectional reflectance distribution function (BRDF) on the retrieval of crystal effective radius was investigated and quantified with uncertainties below 10%, which ranges below the uncertainty caused by the surface albedo variability. The comparison with the independent lidar data allowed for investigation of the role of the crystal shape in the retrieval. It is found that if assuming aggregate ice crystals, the HSRL observations fit best with the retrieved optical thickness from HALO-SR.
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Kassianov, E., M. Ovchinnikov, L. K. Berg, S. A. McFarlane, C. Flynn, R. Ferrare, C. Hostetler, and M. Alexandrov. "Retrieval of aerosol optical depth in vicinity of broken clouds from reflectance ratios: case study." Atmospheric Measurement Techniques Discussions 3, no. 2 (April 21, 2010): 1889–932. http://dx.doi.org/10.5194/amtd-3-1889-2010.
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Abstract. A recently developed reflectance ratio (RR) method for the retrieval of aerosol optical depth (AOD) is evaluated using extensive airborne and ground-based data sets collected during the Cloud and Land Surface Interaction Campaign (CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS), which took place in June 2007 over the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site. A detailed case study is performed for a field of single-layer shallow cumuli observed on 12 June 2007. The RR method is applied to retrieve the spectral values of AOD from the reflectance ratios measured by the MODIS Airborne Simulator (MAS) for two pairs of wavelengths (660 and 470 nm and 870 and 470 nm) collected at a spatial resolution of 0.05 km. The retrieval is compared with an independent AOD estimate from three ground-based Multi-filter Rotating Shadowband Radiometers (MFRSRs). The interpolation algorithm that is used to project MFRSR point measurements onto the aircraft flight tracks is tested using AOD derived from NASA Langley High Spectral Resolution Lidar (HSRL). The RR AOD estimates are in a good agreement (within 5%) with the MFRSR-derived AOD values for the 660-nm wavelength. The AODs obtained from MAS reflectance ratios overestimate those derived from MFRSR measurements by 15–30% for the 470-nm wavelength and underestimate the 870-nm AOD by the same amount.