LAGRS-Soil: A Full-Polarization GNSS-Reflectometry Model for Bare Soil Applications in FY-3E GNOS-R Payload

被引:2
作者
Wu, Xuerui [1 ,2 ]
Ouyang, Xinqiu [3 ]
Xia, Junming [4 ]
Yan, Zhe [5 ]
Wang, Fang [6 ]
机构
[1] Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
[2] Chifeng Univ, Sch Resources Environm & Architectural Engn, Chifeng 024000, Peoples R China
[3] Guangzhou Urban Planning & Design Survey Res Inst, Guangzhou 510060, Peoples R China
[4] Chinese Acad Sci, Natl Space Sci Ctr, Beijing 100190, Peoples R China
[5] Nanjing Univ, Subject Serv Dept, Nanjing 200030, Peoples R China
[6] North China Inst Sci & Technol, Sch Architectural Engn, Yanjiao 065201, Peoples R China
基金
中国国家自然科学基金;
关键词
diffuse scattering; GNOS-R; GNSS-Reflectometry; polarization; random surface scattering models; soil moisture; SCATTERING;
D O I
10.3390/rs15225296
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Land Surface GNSS Reflection Simulator (LAGRS)-Soil model represents a significant advancement in soil moisture detection with the aid of Global Navigation Satellite System (GNSS) Occultation Sounder-Reflectometry (GNOS-R) technology, which is one payload of the Fengyun-3E (FY-3E) satellite that was launched on 5 July 2021. To fully exploit the properties of noncoherent scattering, the LAGRS-Soil model has the capability to calculate DDM information for different observational geometries, which relies on the random surface scattering models employed in LAGRS-Soil. This will provide a comprehensive understanding of soil moisture dynamics across diverse terrains and environments. One of the most notable features of LAGRS-Soil is its ability to obtain DDMs for full polarizations, which enhances soil moisture retrievals compared to current methods that only utilize the commonly used LR polarization (left-hand circular polarization received and right-hand circular polarization transmitted). Meanwhile, the model can also capture frozen soil DDMs which holds immense potential for near-surface Freezing/Thawing (F/T) detection, opening up new research and application opportunities in cold climate regions. LAGRS-Soil is built on microwave scattering models, making it a robust and efficient theoretical model for the FY-3E GNOS-R payload. This model can support ongoing soil moisture retrieval efforts by combining physical models with investigations of diffuse scattering and polarization capabilities for soil moisture detection.
引用
收藏
页数:18
相关论文
共 40 条
[1]   CYGNSS Ocean Surface Wind Validation in the Tropics [J].
Asharaf, Shakeel ;
Waliser, Duane E. ;
Posselt, Derek J. ;
Ruf, Christopher S. ;
Zhang, Chidong ;
Putra, Agie W. .
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2021, 38 (04) :711-724
[2]   Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and Regional Differences and Impact of Different Spatial Scales [J].
Camps, Adriano ;
Vall Llossera, Mercedes ;
Park, Hyuk ;
Portal, Gerard ;
Rossato, Luciana .
REMOTE SENSING, 2018, 10 (11)
[3]   Mapping Freezing and Thawing Surface State Periods With the CYGNSS Based F/T Seasonal Threshold Algorithm [J].
Carreno-Luengo, Hugo ;
Ruf, Christopher S. S. .
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2022, 15 :9943-9952
[4]   Retrieving Freeze/Thaw Surface State From CYGNSS Measurements [J].
Carreno-Luengo, Hugo ;
Ruf, Christopher S. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
[5]   Above-Ground Biomass Retrieval over Tropical Forests: A Novel GNSS-R Approach with CyGNSS [J].
Carreno-Luengo, Hugo ;
Luzi, Guido ;
Crosetto, Michele .
REMOTE SENSING, 2020, 12 (09)
[6]   Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method Simulations [J].
Chen, KS ;
Wu, TD ;
Tsang, L ;
Li, Q ;
Shi, JC ;
Fung, AK .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (01) :90-101
[7]   Estimating inundation extent using CYGNSS data: A conceptual modeling study [J].
Chew, Clara ;
Small, Eric .
REMOTE SENSING OF ENVIRONMENT, 2020, 246
[8]   CYGNSS data map flood inundation during the 2017 Atlantic hurricane season [J].
Chew, Clara ;
Reager, John T. ;
Small, Eric .
SCIENTIFIC REPORTS, 2018, 8
[9]   Analysis of CYGNSS Data for Soil Moisture Retrieval [J].
Clarizia, Maria Paola ;
Pierdicca, Nazzareno ;
Costantini, Fabiano ;
Floury, Nicolas .
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 12 (07) :2227-2235
[10]   Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System (CYGNSS) Mission [J].
Clarizia, Maria Paola ;
Ruf, Christopher S. .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016, 54 (08) :4419-4432