International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

FR1.O-6: Machine Learning and AI Methods for Soil Moisture Retrieval
Fri, 16 Jul, 08:30 - 10:00 (UTC)
Fri, 16 Jul, 10:30 - 12:00 Central Europe Summer Time (UTC +2)
Fri, 16 Jul, 16:30 - 18:00 China Standard Time (UTC +8)
Fri, 16 Jul, 04:30 - 06:00 Eastern Standard Time (UTC -4)
Session Co-Chairs: Mehmet Kurum, Mississippi State University and Emanuele Santi, CNR-IFAC
Session Manager: Simon van Diepen
Track: Land Applications

FR1.O-6.1: CYGNSS SOIL MOISTURE ESTIMATION USING MACHINE LEARNING REGRESSION

Yan Jia, Nanjing University of Posts and Telecommunications, China; Qingyun Yan, Shuanggen Jin, Nanjing University of Information Science and Technology, China; Patrizia Savi, Politecnico di Torino, Italy

FR1.O-6.2: NEURAL NETWORK INTEGRATION OF SMAP AND SENTINEL-1 FOR ESTIMATING SOIL MOISTURE AT HIGH SPATIAL RESOLUTION

Emanuele Santi, Simonetta Paloscia, Simone Pettinato, Giacomo Fontanelli, CNR-IFAC, Italy

FR1.O-6.3: AN EVALUATION OF SOIL MOISTURE RETRIEVAL USING MACHINE LEARNING METHODS: APPLICATION IN ARID REGIONS OF TUNISIA

Noureddine Jarray, Ali Ben Abbes, Imed Riadh Farah, RIADI Laboratory, National School of Computer Science, Manouba, Tunisia, Tunisia

FR1.O-6.4: MACHINE LEARNING BASED SOIL MOISTURE RETRIEVAL ALGORITHM AND VALIDATION AT SELECTED AGRICULTURAL SITES OVER INDIA USING CYGNSS DATA

Shivani Tyagi, Dharmendra Kumar Pandey, Deepak Putrevu, Space Application Centre Ahmedabad, India; Prashant k. Srivastava, Banaras Hindu University, Varanasi, India; Arundhati Misra, Space Application Centre Ahmedabad, India

FR1.O-6.5: DEEP MULTI-MODAL SATELLITE AND IN-SITU OBSERVATION FUSION FOR SOIL MOISTURE RETRIEVAL

Grigorios Tsagkatakis, Foundation for Research and Technology - Hellas, Greece; Mahta Moghaddam, University of Southern California, United States; Panagiotis Tsakalides, Foundation for Research and Technology - Hellas, Greece

FR1.O-6.6: OBSERVING SOIL MOISTURE CHANGE USING C-BAND INTERFEROMETRY USING MACHINE LEARNING REGRESSION

Nuno Cirne Mira, CINAMIL - Academia Militar, Portugal; João Catalão, IDL, Faculdade de Ciências da Universidade de Lisboa, Portugal; Giovanni Nico, Consiglio Nazionale delle Ricerche, Istituto per le Applicazioni del Calcolo, Italy