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AIAA Aviation Forum

作者： Brown, A. P. Natl Res Council Canada NRC Flight Res Lab Atmospher Res Grp U-61 Uplands Ottawa ON K1A 0R6 Canada

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

The NRC has conducted petroleum and SAF jet fuel contrail flight research, using optical, rearwards sensing of own-ship contrail generation. Jet fuels were petroleum derived Jet A1, and SAF fuels of HEFA SPK and ATJ SPK. Measurements consisted of rear-view optical sensing of generated contrails, both sublimating and persistent, in the visual wavelength spectral range. Optical characteristics, in rear-view, were observed and are described. Contrail image brightness was analysed in comparison to sun and space-sky images, deriving albedo numbers for various rear-view orientations. Satellite retrieval algorithms were used to derive ice particle size and number density values from albedo values, which were thereafter compared for back-to-back contrails generated by Jet A1 and SPK jet fuels. Large reductions in number concentrations of approximately 90% were attributed to SPK c.f. Jet A1, whilst SPK contrail ice particles were significantly larger.

关键词： Contrails Albedo retrieval algorithms Satellites Petroleum Jet Fuel Particle Number Optical Thickness In Situ Measurements Data retrieval

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A XCO2 retrieval Algorithm Coupled Spatial Correlation for the Aerosol and Carbon Detection Lidar

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ATMOSPHERIC ENVIRONMENT 2023年 309卷

作者： Pei, Zhipeng Han, Ge Shi, Tianqi Ma, Xin Gong, Wei Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Re Wuhan Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China Hubei Luojia Lab Wuhan Peoples R China Wuhan Inst Quantum Technol Wuhan Peoples R China Engn Res Ctr Minist Educ Percept & Effectiveness Assessment Carbon Neutral Wuhan Peoples R China

We describe the approach to estimating the atmospheric carbon dioxide (CO2) for the Aerosol and Carbon Detection Lidar (ACDL) onboard the Atmospheric Environment Monitoring Satellite (AEMS). The method estimates the optimal state vector by maximizing the measurement posterior probability under a given prior state vector probability distribution. A priori constraint considering the spatial correlation is used as regularization to solve the ill-posed problem. We ran a series of observing system simulation experiments to demonstrate the critical outcome and character percentage uncertainty reduction. The results show that the state vector uncertainty can be reduced by & SIM;10% near the surface for the single sounding. The CO2 column-averaged dry air mole fraction (XCO2 ) derived by this algorithm is more stable than that obtained by the conventional algorithm and enables the monitoring of concentration changes for the multiple soundings.

关键词： Carbon neutrality IPDA Atmospheric trace gases retrieval algorithms Regularization

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VERIFICATION OF THE SEA ICE CONCENTRATION retrievalS FROM THE MTVZA-GYA MEASUREMENTS USING AMSR2 SATELLITE PRODUCT.

VERIFICATION OF THE SEA ICE CONCENTRATION RETRIEVALS FROM TH...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zabolotskikh, Elizaveta Balashova, E. A. Azarov, S. M. Russian State Hydrometeorol Univ Satellite Oceanog Lab St Petersburg Russia

ISBN: (数字)9781665427920

ISBN: (纸本)9781665427920

In this study we have verified the algorithms for the Arctic sea ice concentration (SIC) retrieval from the data of the Russian satellite microwave imager/sounder MTVZA-GYa. The algorithms are based on the polarization differences (PD), measured by the MTVZA-GYa at the frequencies of 10.6 and 36.7 GHz. Verification is done with the SIC satellite product based on the data of the Advanced Microwave Scanning Radiometer 2 (AMSR2) produced with an advanced algorithm from PD measurements at 89 GHz. Verification is done using collocated in time and space AMSR2 and MTVZA-GYa measurements taken in 2020. Analysis of additional high resolution Sentinel-1 Synthetic Aperture Radar (SAR) data have shown that the usage of low frequency MTVZA-GYa PD measurements allow avoiding underestimation of SIC for some areas featured to high frequency AMSR2 PD measurements.

关键词： Arctic AMSR2 MTVZA-GYa sea ice concentration retrieval algorithms

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ATMOSPHERIC WATER VAPOR COLUMN retrievalS FROM MTVZA-GYA MEASUREMENTS.

ATMOSPHERIC WATER VAPOR COLUMN RETRIEVALS FROM MTVZA-GYA MEA...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zabolotskikh, Elizaveta Zhivotovskaia, M. A. Russian State Hydrometeorol Univ Satellite Oceanog Lab St Petersburg Russia

ISBN: (数字)9781665427920

ISBN: (纸本)9781665427920

In this paper we present the algorithms for the atmospheric water vapor column (WVC) retrieval from the data of the Russian satellite microwave imager/sounder MTVZA-GYa. The algorithms are based on the numerical modeling of the brightness temperatures (BT) of the microwave radiation of the atmosphere-ocean system measured by MTVZA-GYa at the frequencies from 10.6 to 36.7 GHz. Recently developed models of microwave radiation interaction with environment are used for BT calculations for a wide range of environmental conditions. Two Neural Networks (NNs) are trained to solve an inverse problem of WVC retrieval from BT values - global NN and tropical NN. The global NN explores all the scanner frequency channels from 10.6 to 36.7 GHz. The tropical NN is based on the measurements at 10.6 and 18.7 GHz. This NN is applicable under conditions of high atmospheric water and specifically in Tropical Cyclones.

关键词： MTVZA-GYa water vapor column Neural Networks numerical experiment retrieval algorithms

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The relationship between chlorophyll fluorescence and polarized light field: Polarization-curve fluorescence height

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2024年 329卷

作者： El-Habashi, Ahmed Ahmed, Sam US Naval Res Lab Remote Sensing Div Washington DC 20375 USA CUNY City Coll Dept Elect Engn Opt Remote Sensing Lab New York NY 10031 USA

The impact of the un-polarized nature of chlorophyll fluorescence, which causes a dip in the degree of polarization of the underwater light field matching the fluorescence spectrum, led to the development of a theoretical relationship indicating that the resulting fractional reduction in observed polarization is linearly proportional to the magnitude of the fluorescence causing it. To evaluate this relationship, we used a vector radiative transfer code (VRTE) for the coupled atmosphere-ocean system using measured inherent optical properties (IOPs) for a variety of oligotrophic and eutrophic waters as inputs. The VRTE was used to simulate elastic components of the underwater reflectance as well as the degree of linear polarization (DoLP) for these different conditions. These values were compared with the underwater reflectances and the DoLPs measured by a multi-angular hyperspectral polarimeter to determine the magnitude of the fluorescence component in the reflectance spectra at 685 nm, and the decrease of the DoLP due to the fluorescence impact at the same wavelength. Fluorescence magnitudes retrieved from the differences between simulated and measured reflectances were found to match well the magnitudes estimated through the relationship based on the drop of the DoLP. It is noted that retrieval accuracies increase for both larger fluorescence and larger underlying DoLP values. Furthermore, a new method is evolved from the measured polarization analysis, Polarization-Curve Fluorescence Height (PCFH). Measured polarization were used to approximate the elastic signal and derive the inelastic un-polarized signal (fluorescence) from the difference in the fluorescence vicinity. These results open possibilities for estimating the magnitude of natural fluorescence using polarization measurements below or above the water surface, .in-situ, or remotely from aircraft or future satellites. Results of ongoing work on potential sensitivities and retrieval accuracies for these a

关键词： Vector radiative transfer Sun Induced Chlorophyll fluorescence retrieval algorithms Remote sensing Ocean Color Hyperspectral Polarimetry PACE Open ocean Coastal waters Scattering Bio-optics Plankton Chlorophyll Minerals CDOM

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Evaluation of regression algorithms for estimating leaf area index and canopy water content from water stressed rice canopy reflectance

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Information Processing in Agriculture 2021年第2期8卷 284-298页

作者： Niranjan Panigrahi Bhabani Sankar Das Agricultural and Food Engineering Department Indian Institute of Technology KharagpurWest Bengal 721302India School of Water Energy and EnvironmentCranfield UniversityCranfield MK430ALUK

Optical remote sensing(RS)with robust algorithms is needed for accurate assessment of crop canopy *** intensive studies on algorithms,their performance using RS needs to be *** evaluated five different algorithms(partial-least-squares regression(PLSR),support vector regression(SVR),random forest regression(RFR),locally-weighted-PLSR(PLSRLW)and PLSR with feature selection(PLSRFS))for rapid assessment of leaf area index(LAI)and canopy water content(CWC)for rice canopies using canopy reflectance spectra over visible to short-wave infrared *** pooled datasets of LAI(600)and CWC(480)were collected from two replicated field experiments during 2014–15 and 2015–16 rice growing *** performance of each algorithm was evaluated using coefficient of determination(R^(2)).Results showed that PLSRLW performed more accurately than other algorithms with R^(2) values 0.77 and 0.66 for LAI and CWC,*** also used a bootstrapping approach to generate a kernel density estimator of root mean squared error values for each *** results suggested that the improvement in prediction accuracy of LAI and CWC can be achieved if a suitable algorithm is selected by assigning higher weights to calibration samples,which has similar canopy structure as the test *** of the canopy spectral data results large error values in test dataset,therefore the use of entire season canopy spectral data should be used for model calibration.

关键词： Rice canopy Reflectance spectroscopy Calibration retrieval algorithms Partial-least-squares regression

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Monitoring and spatial traceability of river water quality using Sentinel-2 satellite images

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SCIENCE OF THE TOTAL ENVIRONMENT 2023年第1期894卷 164862页

作者： Zhang, Yingyin He, Xianqiang Lian, Gang Bai, Yan Yang, Ying Gong, Fang Wang, Difeng Zhang, Zili Li, Teng Jin, Xuchen Zhejiang Univ Ocean Coll Zhoushan 316021 Peoples R China Minist Nat Resources Inst Oceanog 2 State Key Lab Satellite Ocean Environm Dynam Hangzhou 310012 Peoples R China Zhejiang Ecol & Environm Monitoring Ctr Zhejiang Key Lab Ecol & Environm Monitoring Hangzhou 310012 Peoples R China Donghai Lab Zhoushan 316021 Peoples R China Shanghai Jiao Tong Univ Sch Oceanog Shanghai 200030 Peoples R China Guangdong Lab Guangzhou South Marine Sci & Engn Guangzhou 510000 Guangdong Peoples R China

Due to limited monitoring stations along rivers, it is difficult to trace the specific locations of high pollution areas along the whole river by traditionally in situ measurement. High-spatiotemporal-resolution Sentinel-2 satellite images make it possible to routinely monitor and trace the spatial distributions of river water quality if reliable retrieval algorithms are available. This study took seven major rivers (Qiantang River (QTR), Cao'e River (CEJ), Yongjiang River (YJ), Jiaojiang River (JJ), Oujiang River (OJ), Feiyun River (FYR), and Aojiang River (AJ)) in Zhejiang Province, China, as examples to illustrate the spatial traceability of river water quality parameters (permanganate index (CODMn), total phosphorus (TP), and total nitrogen (TN)) from Sentinel-2 satellite images. The regional retrieval models established for these parameters (CODMn, TP and TN) provided correlation coefficients (R) of 0.68, 0.82, and 0.7, respectively. Based on these models, time-series CODMn, TP, and TN products were obtained for the seven rivers from 2016 to 2021 from Sentinel-2 satellite images, and the results show that the CODMn, TP and TN were high downstream and low upstream;exceptions the CEJ, which was slightly higher in the middle reach than other reaches, and the TN in YJ, which was higher upstream than downstream. The downstream reaches were the main areas suffering from relatively high values in most seasons. Except for the springtime TN level in CEJ, the high value areas were located along the middle reaches. In summer and autumn, the high TN areas in JJ, OJ, and AJ were located along the middle and lower reaches, and the TN in YJ was highest in the upstream. More importantly, this study revealed that the specific locations of high pollution areas along rivers can be effectively traced using Sentinel-2 satellite images, which would be helpful for precise water quality control of rivers.

关键词： River water quality Spatial traceability Satellite remote sensing Sentinel-2 images retrieval algorithms

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Physically Based Thermal Infrared Snow/Ice Surface Emissivity for Fast Radiative Transfer Models

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REMOTE SENSING 2023年第23期15卷 5509-5509页

作者： Nalli, Nicholas R. Dang, Cheng Jung, James A. Knuteson, Robert O. Borbas, E. Eva Johnson, Benjamin T. Pryor, Ken Zhou, Lihang IMSG Inc NOAA NESDIS Ctr Satellite Applicat & Res STAR College Pk MD 20740 USA Natl Geospatial Intelligence Agcy NGA Springfield VA 22150 USA Univ Corp Atmospher Res UCAR Boulder CO 80301 USA Joint Ctr Satellite Data Assimilat JCSDA Boulder CO 20740 USA Univ Wisconsin Madison Cooperat Inst Meteorol Satellite Studies CIMSS Madison WI 53706 USA Univ Wisconsin Madison Space Sci & Engn Ctr Madison WI 53706 USA NOAA NWS Natl Ctr Environm Predict NCEP College Pk MD 20740 USA NOAA NESDIS STAR College Pk MD 20740 USA NOAA JPSS Program Off Lanham MD 20706 USA

Accurate thermal infrared (TIR) fast-forward models are critical for weather forecasting via numerical weather prediction (NWP) satellite radiance assimilation and operational environmental data record (EDR) retrieval algorithms. The thermodynamic and compositional data about the surface and lower troposphere are derived from semi-transparent TIR window bands (i.e., surface-sensitive channels) that can span into the far-infrared (FIR) region under dry polar conditions. To model the satellite observed radiance within these bands, an accurate a priori emissivity is necessary for the surface in question, usually provided in the form of a physical or empirical model. To address the needs of hyperspectral TIR satellite radiance assimilation, this paper discusses the research, development, and preliminary validation of a physically based snow/ice emissivity model designed for practical implementation within operational fast-forward models such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Community Radiative Transfer Model (CRTM). To accommodate the range of snow grain sizes, a hybrid modeling approach is adopted, combining a layer scattering model based on the Mie theory (viz., the Wiscombe-Warren 1980 snow albedo model, its complete derivation provided in the Appendices) with a specular facet model. The Mie-scattering model is valid for the smallest snow grain sizes typical of fresh snow and frost, whereas the specular facet model is better suited for the larger sizes and welded snow surfaces typical of aged snow. Comparisons of the model against the previously published spectral emissivity measurements show reasonable agreement across zenith observing angles and snow grain sizes, and preliminary observing system experiments (OSEs) have revealed notable improvements in snow/ice surface window channel calculations versus hyperspectral TIR satellite observations within the NOAA NWP radiance assimilation system.

关键词： surface emissivity multiple scattering quasi-specular reflectance albedo radiative transfer forward modeling fast-models thermal infrared (TIR) far infrared (FIR) delta-Eddington approximation a priori estimate satellite radiance assimilation retrieval algorithms environmental satellites arctic polar regions snow/ice surfaces

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Constrained Inversion of a Microwave Snowpack Emission Model Using Dictionary Matching: Applications for GPM Satellite

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2022年 60卷

作者： Ebtehaj, Ardeshir Durand, Michael Tedesco, Marco Univ Minnesota Dept Civil Environm & Geoengn Minneapolis MN 55455 USA Ohio State Univ Sch Earth Sci Columbus OH 43210 USA Columbia Univ Lamont Doherty Earth Observ Palisades NY 10964 USA NASA Goddard Inst Space Studies GISS New York NY 10026 USA

This article presents a new algorithmic framework for multilayer inversion of the dense media radiative transfer (DMRT) equations of snowpack emission, with particular emphasis on the role of high-frequency microwave channels above 60 GHz. The approach relies on dictionary matching and locally constrained least squares. The results demonstrate that the algorithm can invert the DMRT model and retrieve depth, density, and grain size of a single-layer snowpack when dependencies of density and grain size on depth are properly accounted for. However, as the number of layers increases, the sensitivity of the inversion to observation noise grows markedly. Using observations, over the Great Plains in the United States, from the microwave imager onboard the global precipitation measurement (GPM, 10-166 GHz) core satellite, the initial results demonstrate that under a clear-sky condition and no vegetation canopy, the algorithm is capable to retrieve the snow depth and water equivalent of seasonal snow with a mean absolute error (MAE) of less than 0.15 m--when compared to the high-resolution analysis data from the SNOw Data Assimilation System (SNODAS).

关键词： Snow Microwave radiometry Microwave integrated circuits Microwave imaging Microwave FET integrated circuits Mathematical models Dictionaries Inverse problems passive microwaves retrieval algorithms satellite hydrology snow hydrology

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Validation of MODIS ocean-colour products in the coastal waters of the Yellow Sea and East China Sea

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Acta Oceanologica Sinica 2020年第1期39卷 91-101页

作者： Lingling Jiang Xiangyu Guo Lin Wang Shubha Sathyendranath Hayley Evers-King Yanlong Chen Bingnan Li College of Environmental Science and Engineering Dalian Maritime UniversityDalian 116026China Ministry of Ecology Environment National Marine Environmental Monitoring CenterDalian 116023China Plymouth Marine Laboratory(PML) PlymouthDevonPL13DHUK

An extensive study collected in situ data along the Yellow Sea(YS) and East China Sea(ECS) to assess the radiometric properties and the concentration of the water constituents derived from Moderate Resolution Imaging Spectroradiometer(MODIS). Thirteen high quality match-ups were obtained for evaluating the MODIS estimates of Rrs(λ), chlorophyll a(Chl a) and concentrations of suspended particulate sediment matter(SPM). For MODIS Rrs(λ), the mean absolute percentage difference(APD) was in the range of 20%–36%, and the highest uncertainty appeared at 412 nm, whereas the band ratio of Rrs(λ) at 488 nm compared with that at 547 nm was highly consistent, with an APD of 7%. A combination of near-infrared bands and shortwave infrared wavelengths atmosphere correction algorithm(NIR-SWIR algorithm) was applied to the MODIS data, and the estimation accuracy of Rrs were improved at most of the visible spectral bands except 645 nm, 667 nm and 678 nm. Two ocean-colour empirical algorithms for Chl a estimation were applied to the processed data, the results indicated that the accuracy of the derived Chl a values was obviously improved, the four-band algorithms outperformed the other algorithm for measured and simulated datasets, and the minimum APD was 35%. The SPM was also quantified. Two regional and two coastal SPM algorithms were modified according to the in situ data. By comparison, the modified Tassan model had a higher accuracy for the application along the YS and ECS with an APD of 21%. However, given the limited match-up dataset and the potential influence of the aerosol properties on atmosphere correction, further research is required to develop additional algorithms especially for the low Chl a coastal water.

关键词： MODIS turbid waters chlorophyll a SPM retrieval algorithms Yellow and East China Sea

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