IEEE IGARSS 2022 || Kuala Lumpur, Malaysia || 17

MO6.V16: Soils and Soil Moisture Remote Sensing

Mon, 18 Jul, 21:35 - 22:45 Malaysia Time (UTC +8)
Mon, 18 Jul, 15:35 - 16:45 Central European Time (UTC +1)
Mon, 18 Jul, 13:35 - 14:45 UTC
Mon, 18 Jul, 09:35 - 10:45 Eastern Time (UTC -5)

Location: Virtual Room 16

Session Type: Multimedia Virtual

Session Co-Chairs: Tianjie Zhao, Aerospace Information Research Institute, Chinese Academy of Sciences and Mehrez Zribi, CESBIO

Session Manager: Woan Shiang Lee

Track: Land Applications

MO6.V16.1: EVALUATION OF DIFFERENT METHODS FOR SOIL HEAT FLUX ESTIMATION AT LARGE SCALES USING REMOTE SENSING OBSERVATIONS

Chaolei Zheng, Li Jia, Aerospace Information Research Institute, Chinese Academy of Sciences, China

MO6.V16.2: SPECTRAL MODEL TRANSFER FROM SOIL SPECTRAL LIBRARIES TO ORBITAL SENSORS

Asa Gholizadeh, Czech University of Life Sciences Prague, Czechia; Mohammadmehdi Saberioon, GFZ German Research Center for Geosciences, Germany

MO6.V16.3: ESTIMATING SOIL MOISTURE FROM THE CYGNSS DATA USING A BILINEAR REGRESSION MODEL

Qingyun Yan, Nanjing University of Information Science and Technology, China; Yan Jia, Nanjing University of Posts and Telecommunications, China

MO6.V16.4: ASSESSMENT OF SIGNAL DEGRADATION PERFORMANCE ON VEGETATIONS FOR GNSS-R SM RETRIEVAL

Yan Jia, Jiaqi Zou, Nanjing University of Posts and Telecommunications, Italy; Shuanggen Jin, Qingyun Yan, Nanjing University of Information Science and Technology, Nanjing 210044, China, China

MO6.V16.5: SOIL MOISTURE INVERSION METHOD FOR HIGH GRAVEL SURFACE BASED ON POLSAR DATA

Suying He, Aoshen Qiu, Fengkai Lang, Hongtao Shi, Nanshan Zheng, China University of Mining and Technology, China

MO6.V16.6: A NEW INDEX OF REFLECTIVITY FOR SURFACE SOIL MOISTURE ESTIMATION

Mehrez Zribi, CESBIO, France; Nicolas Baghdadi, TETIS, France

MO6.V16.7: POTENTIAL OF C-BAND SENTINEL-1 DATA FOR ESTIMATING SOIL MOISTURE AND SURFACE ROUGHNESS IN A WATERSHED IN WESTERN FRANCE

Hayfa Zayani, SAS, Institut Agro, INRAE/Université de Carthage, INAT, Lr GREEN-TEAM, France; Mehrez Zribi, CESBIO/ Université de Toulouse/CNES/CNRS/INAE/IRD/UPS, France; Nicolas Baghdadi, CIRAD/CNRS/INRAE/TETIS/ Université de Montpellier/ AgroParistech, France; Emna Ayari, Université de Carthage, INAT, Lr GREEN-TEAM/CESBIO, Université de Toulouse, France; Zeineb Kassouk, Zohra Lili-Chabaane, Université de Carthage, INAT, Lr GREEN-TEAM, Tunisia; Didier Michot, Christian Walter, Youssef Fouad, SAS, Institut Agro, INRAE, France

MO6.V16.8: AN ALTERNATIVE SOIL MOISTURE RETRIEVAL FROM THE SMAP MISSION BY USING MULTI-CHANNEL COLLABORATIVE ALGORITHM

Tianjie Zhao, Zhiqing Peng, Panpan Yao, Aerospace Information Research Institute, Chinese Academy of Sciences, China; Jiancheng Shi, National Space Science Center, Chinese Academy of Sciences, China

MO6.V16.9: FORECASTING SOIL MOISTURE USING A DEEP LEARNING MODEL INTEGRATED WITH PASSIVE MICROWAVE RETRIEVAL

Archana Kannan, Mahta Moghaddam, University of Southern California, United States; Grigorios Tsagkatakis, Foundation for Research and Technology - Hellas (FORTH), Greece; Ruzbeh Akbar, Massachusetts Institute of Technology, United States; Daniel Selva, Texas A&M University, United States; Vinay Ravindra, Richard Levinson, Sreeja Nag, NASA Ames Research Center, United States

MO6.V16.10: EVALUATION OF BACKSCATTERING MODELS AND MACHINE LEARNING METHODS FOR SOIL MOISTURE RETRIEVING BASED ON SENTINEL-1 AND SENTINEL-2 DATA

Raja Inoubli, Ali Ben Abbes, Imed Riadh Farah, la recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente. École Nationale des Sciences de l'Informatique., Tunisia; Noureddine Jarray, Laboratoire d’Erémologie et de LCD (LR16IRA01), Institut des Régions Arides, Tunisia; Lilia Bennaceur, IPEIEM (Institut Préparatoire aux Études d'Ingénieurs El Manar.), Tunisia