scholarly journals Two Simulated Spectral Databases of Lunar Regolith: Method, Validation, and Application

2022 ◽  
Vol 14 (2) ◽  
pp. 277
Author(s):  
Ping Zhou ◽  
Zhe Zhao ◽  
Guangyuan Wei ◽  
Hong-Yuan Huo
Keyword(s):  
Particle Size ◽  
Lunar Regolith ◽  
Simulation Method ◽  
Lunar Soil ◽  
Optimization Method ◽  
Least Square ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spectral Simulation ◽  
Mean Square Errors

Our simulated lunar regolith spectra database, based on the Hapke AMSA radiative transfer model (RTM), is a large supplement to the limited number of lunar spectra data. By analyzing the multiple solutions and applicable scopes of the Hapke model by means of Newton interpolation and the least square optimization method, an improved method was found for the simulation of spectra, but it remained challenging to use to invert mineral abundance. Then, we simulated the spectra, mineral abundance, particle size and maturity of 57 mare and highland samples of the Lunar Soil Characterization Consortium (LSCC) in size groups of 10 µm, 10–20 µm and 20–45 µm. The simulated and measured spectra fit well with each other, with correlation coefficients greater than 0.99 and root mean square errors at a magnitude of 10-3. The parameters of mineral abundance, particle size and maturity are highly consistent with the measured values. Having confirmed the reliability of our simulation method, we analyzed the mechanism, reliability and applicability of the “spectral characteristic angle parameter” proposed by Lucey using the simulated spectral data of lunar regolith. Lucey’s method is only suitable for macro analysis of the entire moon, and the error is large when it is used for areas with high abundance of forsterite or ilmenite. In the spectral simulation of lunar regolith, olivine was subdivided into forsterite and fayalite, and the two end-members were mixed to approximately estimate the effect of the chemical composition of olivine on the spectra, which has been confirmed to be feasible.

scholarly journals Modeling the Reflectance of the Lunar Regolith by a New Method Combining Monte Carlo Ray Tracing and Hapke’s Model with Application to Chang’E-1 IIM Data

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Un-Hong Wong ◽  
Yunzhao Wu ◽  
Hon-Cheng Wong ◽  
Yanyan Liang ◽  
Zesheng Tang
Keyword(s):  
Monte Carlo ◽  
Ray Tracing ◽  
Large Scale ◽  
Scale Effects ◽  
Lunar Regolith ◽  
Lunar Soil ◽  
New Method ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Composition Of Minerals

In this paper, we model the reflectance of the lunar regolith by a new method combining Monte Carlo ray tracing and Hapke’s model. The existing modeling methods exploit either a radiative transfer model or a geometric optical model. However, the measured data from an Interference Imaging spectrometer (IIM) on an orbiter were affected not only by the composition of minerals but also by the environmental factors. These factors cannot be well addressed by a single model alone. Our method implemented Monte Carlo ray tracing for simulating the large-scale effects such as the reflection of topography of the lunar soil and Hapke’s model for calculating the reflection intensity of the internal scattering effects of particles of the lunar soil. Therefore, both the large-scale and microscale effects are considered in our method, providing a more accurate modeling of the reflectance of the lunar regolith. Simulation results using the Lunar Soil Characterization Consortium (LSCC) data and Chang’E-1 elevation map show that our method is effective and useful. We have also applied our method to Chang’E-1 IIM data for removing the influence of lunar topography to the reflectance of the lunar soil and to generate more realistic visualizations of the lunar surface.

scholarly journals MINERAL ABUNDANCE AND PARTICLE SIZE DISTRIBUTION DERIVED FROM IN-SITU SPECTRA MEASUREMENTS OF YUTU ROVER OF CHANG’E-3

2017 ◽  
Vol XLII-3/W1 ◽  
pp. 85-89
Author(s):  
H. Lin ◽  
X. Zhang ◽  
Y. Yang ◽  
X. Wu ◽  
D. Guo
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Landing Site ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Particle Sizes ◽  
The Mean ◽  
The Difference ◽  
Yutu Rover

From geologic perspective, understanding the types, abundance, and size distributions of minerals allows us to address what geologic processes have been active on the lunar and planetary surface. The imaging spectrometer which was carried by the Yutu Rover of Chinese Chang’E-3 mission collected the reflectance at four different sites at the height of ~ 1 m, providing a new insight to understand the lunar surface. The mineral composition and Particle Size Distribution (PSD) of these four sites were derived in this study using a Radiative Transfer Model (RTM) and Sparse Unmixing (SU) algorithm. The endmembers used were clinopyroxene, orthopyroxene, olivine, plagioclase and agglutinate collected from the lunar sample spectral dataset in RELAB. The results show that the agglutinate, clinopyroxene and olivine are the dominant minerals around the landing site. In location Node E, the abundance of agglutinate can reach up to 70 %, and the abundances of clinopyroxene and olivine are around 10 %. The mean particle sizes and the deviations of these endmembers were retrieved. PSDs of all these endmembers are close to normal distribution, and differences exist in the mean particle sizes, indicating the difference of space weathering rate of these endmembers.

scholarly journals Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

2013 ◽  
Vol 6 (1) ◽  
pp. 105-119 ◽  
Author(s):  
J. T. Wiensz ◽  
D. A. Degenstein ◽  
N. D. Lloyd ◽  
A. E. Bourassa
Keyword(s):  
Particle Size ◽  
Optical Thickness ◽  
Imaging System ◽  
Radiative Transfer Model ◽  
Model Parameters ◽  
Transfer Model ◽  
Reconstruction Technique ◽  
Cirrus Cloud ◽  
Multiplicative Algebraic Reconstruction Technique ◽  
Cloud Particle

Abstract. We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

scholarly journals Mapping Benthic Habitats by Extending Non-Negative Matrix Factorization to Address the Water Column and Seabed Adjacency Effects

2020 ◽  
Vol 12 (13) ◽  
pp. 2072
Author(s):  
Mireille Guillaume ◽  
Audrey Minghelli ◽  
Yannick Deville ◽  
Malik Chami ◽  
Louis Juste ◽  
...  
Keyword(s):  
Optical Properties ◽  
Water Column ◽  
Matrix Factorization ◽  
Coastal Areas ◽  
Least Square ◽  
Local Analysis ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Benthic Habitats ◽  
Non Negative Matrix Factorization

Monitoring of coastal areas by remote sensing is an important issue. The interest of using an unmixing method to determine the seabed composition from hyperspectral aerial images of coastal areas is investigated. Unmixing provides both seabed abundances and endmember reflectances. A sub-surface mixing model is presented, based on a recently proposed oceanic radiative transfer model that accounts for seabed adjacency effects in the water column. Two original non-negative matrix factorization ( N M F )-based unmixing algorithms, referred to as W A D J U M (Water ADJacency UnMixing) and W U M (Water UnMixing, no adjacency effects) are developed, assuming as known the water column bio-optical properties. Simulations show that W A D J U M algorithm achieves performance close to that of the N M F -based unmixing of the seabed without any water column, up to 10 m depth. W U M performance is lower and decreases with the depth. The robustness of the algorithms when using erroneous information about the water column bio-optical properties is evaluated. The results show that the abundance estimation is more reliable using W A D J U M approach. W A D J U M is applied to real data acquired along the French coast; the derived abundance maps of the benthic habitats are discussed and compared to the maps obtained using a fixed spectral library and a least-square ( L S ) estimation of the seabed mixing coefficients. The results show the relevance of the W A D J U M algorithm for the local analysis of the benthic habitats.

scholarly journals Numerical Experiments of an Advanced Radiative Transfer Model in the U.S. Navy Operational Global Atmospheric Prediction System

2012 ◽  
Vol 51 (3) ◽  
pp. 554-570 ◽  
Author(s):  
Ming Liu ◽  
Young-Joon Kim ◽  
Qingyun Zhao
Keyword(s):  
Radiative Transfer ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Forecast Errors ◽  
Prediction System ◽  
Surface Data ◽  
Ice Water ◽  
The Impact ◽  
Mean Square Errors

AbstractA high-order accurate radiative transfer (RT) model developed by Fu and Liou has been implemented into the Navy Operational Global Atmospheric Prediction System (NOGAPS) to improve the energy budget and forecast skill. The Fu–Liou RT model is a four-stream algorithm (with a two-stream option) integrating over 6 shortwave bands and 12 longwave bands. The experimental 10-day forecasts and analyses from data assimilation cycles are compared with the operational output, which uses a two-stream RT model of three shortwave and five longwave bands, for both winter and summer periods. The verifications against observations of radiosonde and surface data show that the new RT model increases temperature accuracy in both forecasts and analyses by reducing mean bias and root-mean-square errors globally. In addition, the forecast errors also grow more slowly in time than those of the operational NOGAPS because of accumulated effects of more accurate cloud–radiation interactions. The impact of parameterized cloud effective radius in estimating liquid and ice water optical properties is also investigated through a sensitivity test by comparing with the cases using constant cloud effective radius to examine the temperature changes in response to cloud scattering and absorption. The parameterization approach is demonstrated to outperform that of constant radius by showing smaller errors and better matches to observations. This suggests the superiority of the new RT model relative to its operational counterpart, which does not use cloud effective radius. An effort has also been made to improve the computational efficiency of the new RT model for operational applications.

Estimation of Surface and Top-of-Atmosphere Shortwave Irradiance in Biomass-Burning Regions during SCAR-B

2000 ◽  
Vol 39 (10) ◽  
pp. 1742-1753 ◽  
Author(s):  
Sundar A. Christopher ◽  
Xiang Li ◽  
Ronald M. Welch ◽  
Jeffrey S. Reid ◽  
Peter V. Hobbs ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Biomass Burning ◽  
Optical Thickness ◽  
Radiative Forcing ◽  
Wavelength Dependence ◽  
Single Scattering ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Radiative Forcing ◽  
Mean Square Errors

Abstract Using in situ measurements of aerosol optical properties and ground-based measurements of aerosol optical thickness (τs) during the Smoke, Clouds and Radiation—Brazil (SCAR-B) experiment, a four-stream broadband radiative transfer model is used to estimate the downward shortwave irradiance (DSWI) and top-of-atmosphere (TOA) shortwave aerosol radiative forcing (SWARF) in cloud-free regions dominated by smoke from biomass burning in Brazil. The calculated DSWI values are compared with broadband pyranometer measurements made at the surface. The results show that, for two days when near-coincident measurements of single-scattering albedo ω0 and τs are available, the root-mean-square errors between the measured and calculated DSWI for daytime data are within 30 W m−2. For five days during SCAR-B, however, when assumptions about ω0 have to be made and also when τs was significantly higher, the differences can be as large as 100 W m−2. At TOA, the SWARF per unit optical thickness ranges from −20 to −60 W m−2 over four major ecosystems in South America. The results show that τs and ω0 are the two most important parameters that affect DSWI calculations. For SWARF values, surface albedos also play an important role. It is shown that ω0 must be known within 0.05 and τs at 0.55 μm must be known to within 0.1 to estimate DSWI to within 20 W m−2. The methodology described in this paper could serve as a potential strategy for determining DSWI values in the presence of aerosols. The wavelength dependence of τs and ω0 over the entire shortwave spectrum is needed to improve radiative transfer calculations. If global retrievals of DSWI and SWARF from satellite measurements are to be performed in the presence of biomass-burning aerosols on a routine basis, a concerted effort should be made to develop methodologies for estimating ω0 and τs from satellite and ground-based measurements.

scholarly journals Temperature and Humidity Profile Retrieval from FY4-GIIRS Hyperspectral Data Using Artificial Neural Networks

2020 ◽  
Vol 12 (11) ◽  
pp. 1872
Author(s):  
Xi Cai ◽  
Yansong Bao ◽  
George P. Petropoulos ◽  
Feng Lu ◽  
Qifeng Lu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Hyperspectral Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Retrieval Accuracy ◽  
Temperature And Humidity ◽  
Artificial Neural ◽  
Mean Square Errors ◽  
Humidity Profiles

This study proposes a new technique for retrieving temperature and humidity profiles based on Artificial Neural Networks (ANNs) using data acquired from the GIIRS (Geosynchronous Interferometric Infrared Sounder) L1 and ERA-Interim (European Centre for Medium-Range Weather Forecasts Reanalysis). The approach is also compared against another method that uses simulated data from the radiative transfer model to construct the retrieval network. Furthermore, the two methods of network construction are evaluated in the North China Plain for July and August 2018, for which ground validated observations concurrent to the satellite data were available. In summary, the results showed that: (1) the ANN built with the GIIRS L1 and the EC data is superior to that built with the forward simulation and EC data in retrieval accuracy; (2) the retrieval accuracy for the troposphere exceeds that for the stratosphere; (3) the root mean square errors (RMSEs) of the relative humidity in the troposphere as retrieved by the two ANNs are 6.003% and 10.608%, respectively; (4) a relatively low correlation (R) between the simulated and observed radiance of the GIIRS is found, ranging between 720 and 736.875 cm−1, and the correlation between the simulated and observed radiance of the water vapor channels exceeds that between the temperature channels; (5) compared with Atmospheric Infrared Sounder’s (AIRS’) products, our retrieved temperature profiles exhibit preferable consistency and the humidity retrievals also show an acceptable accuracy. Our study offers important insights towards improving our ability to retrieve atmospheric temperature and humidity profiles from the most sophisticated Earth Observation instruments such as the GIIRS of the FY-4 satellite, which could assist in expanding the use of those products globally.

scholarly journals Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

2015 ◽  
Vol 8 (5) ◽  
pp. 4051-4073
Author(s):  
M. J. Prather
Keyword(s):  
Cross Sections ◽  
Atmospheric Chemistry ◽  
Climate Models ◽  
Accurate Method ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
New Approach ◽  
Photolysis Rates ◽  
Fractional Cloud ◽  
Mean Square Errors

Abstract. A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations. Cloud-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.

scholarly journals Remote Sensing Energy Balance Model for the Assessment of Crop Evapotranspiration and Water Status in an Almond Rootstock Collection

2021 ◽  
Vol 12 ◽  
Author(s):  
Joaquim Bellvert ◽  
Héctor Nieto ◽  
Ana Pelechá ◽  
Christian Jofre-Čekalović ◽  
Lourdes Zazurca ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Water Productivity ◽  
Balance Model ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Stem Water Potential ◽  
Crop Evapotranspiration ◽  
Area Index ◽  
Mean Square Errors

One of the objectives of many studies conducted by breeding programs is to characterize and select rootstocks well-adapted to drought conditions. In recent years, field high-throughput phenotyping methods have been developed to characterize plant traits and to identify the most water use efficient varieties and rootstocks. However, none of these studies have been able to quantify the behavior of crop evapotranspiration in almond rootstocks under different water regimes. In this study, remote sensing phenotyping methods were used to assess the evapotranspiration of almond cv. “Marinada” grafted onto a rootstock collection. In particular, the two-source energy balance and Shuttleworth and Wallace models were used to, respectively, estimate the actual and potential evapotranspiration of almonds grafted onto 10 rootstock under three different irrigation treatments. For this purpose, three flights were conducted during the 2018 and 2019 growing seasons with an aircraft equipped with a thermal and multispectral camera. Stem water potential (Ψstem) was also measured concomitant to image acquisition. Biophysical traits of the vegetation were firstly assessed through photogrammetry techniques, spectral vegetation indices and the radiative transfer model PROSAIL. The estimates of canopy height, leaf area index and daily fraction of intercepted radiation had root mean square errors of 0.57 m, 0.24 m m–1 and 0.07%, respectively. Findings of this study showed significant differences between rootstocks in all of the evaluated parameters. Cadaman® and Garnem® had the highest canopy vigor traits, evapotranspiration, Ψstem and kernel yield. In contrast, Rootpac® 20 and Rootpac® R had the lowest values of the same parameters, suggesting that this was due to an incompatibility between plum-almond species or to a lower water absorption capability of the rooting system. Among the rootstocks with medium canopy vigor, Adesoto and IRTA 1 had a lower evapotranspiration than Rootpac® 40 and Ishtara®. Water productivity (WP) (kg kernel/mm water evapotranspired) tended to decrease with Ψstem, mainly in 2018. Cadaman® and Garnem® had the highest WP, followed by INRA GF-677, IRTA 1, IRTA 2, and Rootpac® 40. Despite the low Ψstem of Rootpac® R, the WP of this rootstock was also high.

scholarly journals Retrieval of Ice Cloud Optical Thickness and Effective Particle Size Using a Fast Infrared Radiative Transfer Model

2011 ◽  
Vol 50 (11) ◽  
pp. 2283-2297 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Bryan A. Baum ◽  
Steven Platnick ◽  
Andrew K. Heidinger ◽  
...  
Keyword(s):  
Particle Size ◽  
Radiative Transfer ◽  
Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Distribution Method ◽  
Ice Cloud ◽  
Effective Particle Size ◽  
Effective Particle ◽  
Cloud Optical Thickness

AbstractA computationally efficient radiative transfer model (RTM) is developed for the inference of ice cloud optical thickness and effective particle size from satellite-based infrared (IR) measurements and is aimed at potential use in operational cloud-property retrievals from multispectral satellite imagery. The RTM employs precomputed lookup tables to simulate the top-of-the-atmosphere (TOA) radiances (or brightness temperatures) at 8.5-, 11-, and 12-μm bands. For the clear-sky atmosphere, the optical thickness of each atmospheric layer resulting from gaseous absorption is derived from the correlated-k-distribution method. The cloud reflectance, transmittance, emissivity, and effective temperature are precomputed using the Discrete Ordinate Radiative Transfer model (DISORT). For an atmosphere containing a semitransparent ice cloud layer with a visible optical thickness τ smaller than 5, the TOA brightness temperature differences (BTDs) between the fast model and the more rigorous DISORT results are less than 0.1 K, whereas the BTDs are less than 0.01 K if τ is larger than 10. With the proposed RTM, the cloud optical and microphysical properties are retrieved from collocated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) in conjunction with the Modern Era Retrospective-Analysis for Research and Applications (MERRA) data. Comparisons between the retrieved ice cloud properties (optical thickness and effective particle size) based on the present IR fast model and those from the Aqua/MODIS operational collection-5 cloud products indicate that the IR retrievals are smaller. A comparison between the IR-retrieved ice water path (IWP) and CALIOP-retrieved IWP shows robust agreement over most of the IWP range.

Sign in / Sign up

Export Citation Format

Share Document