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Ocean water colour retrieval method based on directional polarimetric camera

INTERNATIONAL JOURNAL OF REMOTE SENSING 2024年第15期45卷 5175-5191页

作者： Pan, Yuwei Chen, Jingjing Chen, Feinan Xiang, Guangfeng Luo, Donggen Sun, Liang Hong, Jin Shu, Shuangbao Hefei Univ Technol Sch Instrument Sci & Optoelect Engn 193 TunXi Rd Hefei Anhui Peoples R China Chinese Acad Sci Anhui Inst Opt & Fine Mech Hefei Inst Phys Sci Hefei Anhui Peoples R China Hefei Univ Technol Anhui Prov Key Lab Measuring Theory & Precis Instr Hefei Anhui Peoples R China

Chlorophyll-a (Chl-a) concentrations serve as a pivotal metric for assessing the biological content and eutrophication levels of waterbodies. In optical remote sensing, empirical and semi-analytical methods are commonly employed for Chl-a retrieval. Leveraging the Level-1B remote sensing data from the Directional Polarimetric Camera (DPC) aboard the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS), this study amalgamates empirical algorithms (OC2, OC3, Aiken-P, and Aiken-C) and look-up-table (LUT) techniques to estimate Chl-a in open water. Test data acquired from DPC on 20 August 2022, are validated against the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite and AERONET-Ocean Color water-leaving radiance data for the same area and date. The results reveal that among the tested algorithms, particularly in the log10 scale space, the Aiken-P algorithm demonstrates the highest correlation coefficient (R2 = 0.6333), with the lowest bias of 1.0366 and a minimum mean absolute error (MAE) of 1.2097. This underscores the suitability and accuracy of the Aiken-P algorithm for water colour retrieval based on DPC-derived data, highlighting its practical applicability.

关键词： Chlorophyll-a concentrations retrieval algorithm band-ratio look-up table remote sensing

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Simultaneous physical retrieval of daytime lunar surface temperature and spectral emissivity in the 3-5 μm range from Chandrayaan-2 IIRS observations

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CURRENT SCIENCE 2024年第7期126卷 781-790页

作者： Ojha, Satya P. Dagar, Aditya K. Vikram, K. V. N. G. Bhattacharya, Satadru Bhattacharya, Bimal Kumar Kumar, A. S. Kiran Space Applicat Ctr Ahmadabad 380015 India Indian Space Res Org Head Quarters Bengaluru 560094 India

The Imaging InfraRed Spectrometer (IIRS) on board Chandrayaan-2 has been providing high spatial and spectral resolution observations of the lunar surface in 256 spectral bands (0.7-5 mu m) since September 2019. It is primarily intended for mineral mapping and identifying hydration features on the lunar surface using reflectance spectra in the range of 0.7-3.2 mu m. Here, we have used the IIRS observations in the 3-5 mu m range to retrieve daytime lunar surface temperature and spectral emissivity using an optimal estimation theory -based retrieval algorithm. The surface temperature is retrieved at every pixel, while spectral emissivity is retrieved at every third pixel of the hyperspectral image. The mean uncertainty of the retrieved spectral emissivity varies from 0.04 to 0.08, while for surface temperature, it is about 3.5 K. The retrieved spectral emissivity is found to be in close agreement with the emissivity of the Apollo -16 return soil samples.

关键词： Hyperspectral imaging lunar exploration mission optimum estimation retrieval algorithm spectral emissivity surface temperature

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Improvement of temperature and humidity profile retrieval from brightness temperature data

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EARTH SCIENCE INFORMATICS 2025年第2期18卷 1-8页

作者： Zhang, Dan Chen, Rui Huanggang Normal Univ Sch Phys & Elect Informat Huanggang 438000 Peoples R China Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan 430074 Peoples R China

To improve the retrieval accuracy of atmospheric temperature and humidity profile and promote the development of the domestic ground-based microwave radiometer (MWR), we developed an improved indirect sample retrieval algorithm. This study applied the improved algorithm to the HRA002 ground-based MWR produced by Wuhan Huameng Technology Co., Ltd and tested at Wuhan National Basic Meteorological Station. Compared with the conventional gradient descent method and the trainLM (Levenberg-Marquardt) algorithm, validation of the Bayesian regularization (BR) algorithm with the radiosonde at the same station showed a root-mean-square error (RMSE) decrease from 2.21 K, 2.59 K to 2.06 K for temperature, from 1.31 g/m3, 1.16 g/m3 to 1.04 g/m3 for water vapor density, and from 22.33%, 24.53-21.49% for relative humidity. On the basis of adopting the BR algorithm, compared with the ordinary network, the RMSE between the retrieved results of temperature, water vapor density and relative humidity of the improved network and the radiosonde data decreased from 2.06 K, 1.04 g/m3, and 21.49% to 1.89 K, 0.98 g/m3, and 19.41%, respectively. The retrieval accuracy was improved by the modifications made by this study to the algorithm. The research results in this paper show that the improved algorithm can further improve the retrieval accuracy on the basis of the existing indirect sample retrieval algorithm and can effectively promote the development of domestic ground-based MWR.

关键词： Ground-based microwave radiometer retrieval algorithm Network improvement Co-site observation

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EXAMINATION OF A COUPLED-PIXEL MODEL (CPM) ATMOSPHERIC retrieval algorithm

EXAMINATION OF A COUPLED-PIXEL MODEL (CPM) ATMOSPHERIC RETRI...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Mary Morris Christopher S. Ruf University of Michigan

ISBN: (纸本)9781479979301

Oceanic remote sensing of rain rate and surface wind speed is possible using low frequency passive microwave sensors on both space-based and aircraft-based platforms. The particular observing geometries of these sensors allows for simplifying assumptions about the rain in the field of view - assumptions that are not possible for the Hurricane Imaging Radiometer (HIRad). HIRad's unique observing capabilities are such that a single atmospheric column can affect the observations at multiple cross-track positions. This motivated the development of the Coupled Pixel Model (CPM) atmospheric retrieval algorithm. This newly developed retrieval algorithm performance is limited by beam averaging. With increasing earth incidence angle (EIA), it becomes more difficult to deconvolve distinct neighboring rain bands.

关键词： HIRad Microwave radiometry Tropical cyclone imaging retrieval algorithm RADIOMETRY retrieval Critical path method rain Inspection field of view algorithms passive microwave sensor

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An efficient data retrieval method for grid blockchain

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2023年第2期43卷 118-125页

作者： Zhang, Caijun Wu, Qianjun Lang, Jiayi Yang, Huafei Wang, Xiaolong Xian, Kaiqiang Zhang, Jingqiu State Grid Co Ltd Customer Serv Ctr Tianjin 300309 Peoples R China State Grid Elect Power Res Inst Co Ltd Nanjing 211106 Jiangsu Peoples R China State Grid Jiangsu Elect Power Co Ltd Mkt Serv Ctr Nanjing 211000 Jiangsu Peoples R China

The blockchain-based power grid integration business system (PG-IBS) is increasing rapidly. However, due to the limitation of blockchain, these systems have problem of low data retrieval efficiency. To solve this problem, through careful investigation and analysis, an efficient data retrieval method for power grid blockchain (EDRM-PGB) is proposed in the paper. EDRM-PGB rebuilds an efficient retrieval index structure transaction index structure (TIS) for a PG-IBS, while maintaining compatibility with the original system. TIS index structure is built on two data structures blockchain account bloom filter (BABF) and binary tree with transaction information (BTTI). Based on the structure, EDRM-PGB efficient retrieval algorithm is designed. EDRM-PGB's feasibility is verified by the prototype system implementation and performance simulation. Simulation result shows that compared with the traditional retrieval method, EDRM-PGB can greatly improve the data retrieval performance of PG-IBS. Meanwhile, it also has advantage of sharing of index files easily.

关键词： data retrieval blockchain power grid retrieval algorithm

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Using Saildrones to Assess the SMAP Sea Surface Salinity retrieval in the Coastal Regions

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2022年 15卷 7042-7051页

作者： Tang, Wenqing Yueh, Simon H. Fore, Alexander G. Vazquez-Cuervo, Jorge Gentemann, Chelle Hayashi, Akiko K. Akins, Alex Garcia-Reyes, Marisol CALTECH Jet Prop Lab Pasadena CA 91109 USA Farallon Inst Petaluma CA 94592 USA

Remote sensing of sea surface salinity (SSS) near land is difficult due to land contamination. In this article, we assess SSS retrieved from the soil moisture active passive (SMAP) mission in coastal region. SMAP SSS products from the Jet Propulsion Laboratory (JPL), and from the remote sensing systems (RSS) are collocated with in situ data collected by saildrones during the North American West Coast Survey. Satellite and saildrone salinity measurements reveal consistent large-scale features: the fresh water (low SSS) assocciated with the Columbia River discharge, and the relatively salty water (high SSS) near Baja California associated with regional upwelling. The standard deviation of the difference for collocations with SMAP Level 3 (eight days average) between 40 and 100 km from land is 0.51 (0.56) psu for JPL V5 (RSS V4 70 km). This is encouraging for the potential application of SMAP SSS in monitoring coastal zone freshwater particularly where there exists large freshwater variance. We analyze the different land correction approaches independently developed at JPL and RSS using SMAP level 2 matchups. We found that JPL's land correction method is more promising in pushing SMAP SSS retrieval towards land. For future improvement, we suggest implementing dynamic land correction versus the current climatology-based static land correction to reduce uncertainty in estimating land contribution. In level 2 to level 3 processing, a more rigorous quality control may help to eliminate outliers and deliver reliable level 3 products without over-smoothing, which is important in resolving coastal processes such as fronts or upwelling.

关键词： Sea measurements Salinity (geophysical) Ocean temperature Rivers Satellites Satellite broadcasting Propulsion Coastal retrieval algorithm saildrone sea surface salinity (SSS) soil moisture active passive (SMAP) validation

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A Review of Anthropogenic Ground-Level Carbon Emissions Based on Satellite Data

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2024年 17卷 8339-8357页

作者： Hu, Kai Zhang, Qi Gong, Shen Zhang, Fuying Weng, Liguo Jiang, Shanshan Xia, Min Nanjing Univ Informat Sci Technol Nanjing 210044 Peoples R China Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing 210044 Peoples R China

The severity of the global warming issue emphasizes the critical importance of utilizing carbon satellite data to estimate ground-level carbon dioxide emissions. However, existing reviews have not kept pace with the latest research developments. Therefore, this article provides an overview of relevant work in the global carbon emissions field to address this knowledge gap. Through visual analysis using Citespace software, the article outlines two methods for quantifying carbon dioxide: 1) ground-level observations;and 2) satellite remote sensing. Despite the unique advantages of ground-level observations, satellite remote sensing is crucial for its extensive spatial coverage and long-term continuity in understanding carbon cycling, drawing significant attention. In addition, the article integrates the application of machine learning in the carbon emissions field, dividing it into two parts: Direct estimation based on ground emission inventory data and estimation of ground-level carbon emissions based on carbon satellite data. This innovative approach combines satellite observational data with ground data to accurately estimate the current ground-level carbon emissions with robust spatial distribution characteristics.

关键词： Climate change Satellite images Machine learning Carbon dioxide Remote sensing Global warming Distribution functions Visualization Graphical models Carbon satellite machine learning retrieval algorithm XCO2

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Aerosol Optical Depth Over Ocean From Ocean Color Monitor-3 Onboard the Earth Observation Satellite (EOS-06)

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2024年 21卷 1页

作者： Prijith, S. S. Athul, A. K. Babu, S. Suresh Indian Space Res Org Space Phys Lab Vikram Sarabhai Space Ctr Thiruvananthapuram 695022 India Univ Kerala Dept Phys Thiruvananthapuram 695021 India

The Continuance of satellite-based retrievals with series of space-borne sensors is essential to generate long term climate quality data records. Indian Space Research Organisation (ISRO) launched Ocean Color Monitor-3 (OCM-3), onboard the Earth Observation Satellite-06 (EOS-06), which is the third one in the series of OCM sensors. EOS-06/OCM-3 has potential for the retrieval of AOD at 555 nm (tau (555) ) over oceanic regions at pixel level resolution of 366 m at nadir. Here, an algorithm for AOD retrieval based on look-up table (LUT) approach, employing radiative transfer computations to account for multiple scattering in the atmosphere, is presented. LUTs of top of the atmosphere (TOA) reflectance are generated with region and season specific aerosol models, based on the measurements of aerosol properties over the oceanic regions around India in pre-monsoon and winter seasons. Theoretically expected uncertainty in tau (555) from OCM-3 (tau (OCM3) ) is estimated to be epsilon (tau) = 0.1 x tau + 0.2, (correlation coefficient, R = 0.95). Validation of tau (OCM3) with AERONET AOD shows a linear regression slope (m) 0.79, intercept (c) 0.02 and R 0.85. tau (OCM3) is in good agreement with MODIS AOD with m, c and R values 0.996, 0.06 and 0.78, respectively and thereby ensures continuity of climate quality AOD data for longer period. retrieval of AOD from OCM-3 at a finer spatial resolution would significantly improve regional characterization of aerosol properties and assessment of aerosol climate impacts.

关键词： Aerosols Sea measurements Reflectivity Pollution measurement Table lookup Atmospheric modeling Atmospheric measurements Satellites Clouds Sea surface Aerosol lookup table (LUT) Ocean Color Monitor (OCM) remote sensing retrieval algorithm satellite

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China's First Infrared Occultation Spectrometer (GaoFen-5/AIUS) Monitoring Atmosphere Above Antarctic: Evaluation of Methane Profiles

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2024年 17卷 7946-7956页

作者： Liu, Shuanghui Li, Xiaoying Xu, Jian Shi, Hailiang Guo, Yuhang Zhang, Xingying Ge, Shule Wang, Yapeng Wang, Hongmei Cao, Xifeng Rao, Lanlan Shi, Jiancheng Chinese Acad Sci Natl Space Sci Ctr Beijing 100190 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst Beijing 100094 Peoples R China Innovat Ctr FengYun Meteorol Satellite FYSIC Beijing 100081 Peoples R China Chinese Acad Sci Anhui Inst Opticsand Fine Mech Hefei 230031 Peoples R China China Meteorol Adm Natl Satellite Meteorol Ctr Beijing 100081 Peoples R China China Ctr Resources Satellite Data & Applicat Beijing 100094 Peoples R China Nantong Univ Nantong 226019 Peoples R China

The atmospheric infrared ultraspectral sounder (AIUS) is China's first infrared occultation spectrometer onboard the GaoFen-5 satellite. This instrument provides measurements in the near-infrared and mid-infrared spectral regions with a spectral resolution of 0.02 cm( -1) , monitoring key greenhouse gases like methane (CH (4) ). In this study, we have developed a physics-based retrieval algorithm for accurately deriving CH (4 )mole fraction profiles from infrared absorption spectra. The retrieval algorithm is applied to the AIUS and successfully obtains CH 4 mole fraction profiles from January to December 2019 over Antarctic. The validation results show that the retrieval algorithm has a satisfactory performance using AIUS measurements, with average relative standard deviation of the differences less than 7.2% throughout the altitude range of 10-70 km.

关键词： Antarctic GaoFen-5 (GF-5)/atmospheric infrared ultraspectral sounder (AIUS) methane (CH4 ) retrieval algorithm

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EXPERIMENTAL STUDY OF WAVE PARAMETERS retrieval BY AN UNDERWATER ACOUSTIC WAVEGAUGE

EXPERIMENTAL STUDY OF WAVE PARAMETERS RETRIEVAL BY AN UNDERW...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Titchenko, Yuriy Ponur, Kirill Karaev, Vladimir Meshkov, Eugeny Kovaldov, Dmitry Epanova, Kseniya Russian Acad Sci Inst Appl Phys Moscow Russia

ISBN: (纸本)9798350320107

To solve the problems of measuring wave parameters on the water surface, it is proposed to use an underwater acoustic wave gauge. Underwater observation of surface waves has several advantages over sea buoys and string wave gauge. Underwater instruments can operate anywhere in the World Ocean and do not require mounting on the rigid structure of offshore platforms. Underwater methods are not sensitive to any atmospheric conditions, for example, they can work in hurricane winds and even in freezing waters. There are various devices for underwater measurement of wave parameters. However, they are united by the desire to determine the wave spectrum, which requires making the antenna beam as narrow as possible, and the measurement results will depend on the installation depth. Because of this, it is necessary to limit the region of the measured spectrum only to low-frequency (long) waves, usually the upper limit is about 0.35 Hz. In this work, experimental testing of a new approach for determining the integral parameters of waves by the shape of the reflected acoustic pulse averaged over space and time, is carried out. A feature of this approach is the insensitivity to the instrument installation depth (deeper installation will even provide shorter time averaging). Another important advantage of this approach is the ability to measure the same surface parameters that affect the characteristics of microwave backscattering with the same wavelength.

关键词： underwater acoustics significant wave height mean square slopes experiment retrieval algorithm string wave gauge

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