Topics Webinar | EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data, 12 February 2025
Soil moisture plays a crucial role in the exchange of water and energy within the soil–plant–atmosphere system. Its significance is acknowledged across a spectrum of environmental disciplines, encompassing meteorology, hydrology, agriculture, and climate change studies. Consequently, the precise monitoring and estimation of the spatial and temporal fluctuations in soil moisture are of particular importance.
Remote sensing technologies have revolutionized our ability to monitor soil moisture dynamics at a regional scale. Satellite-based remote sensing offers a global-scale perspective with continuous spatiotemporal resolution, making it a cornerstone for soil moisture estimation. During the last few decades, significant progress has been made in estimating soil moisture from remote sensing data. Advancements in both active and passive remote sensing technologies, satellite remote sensing, drone technologies, and data assimilation methods have enabled us to obtain soil moisture estimations at different spatial scales from meters to tens of kilometers, in addition to temporal resolutions from hours to daily.
However, obtaining reliable soil moisture information at the required spatiotemporal resolution and along soil depth with a high level of accuracy is still challenging, especially due to highly variable soil moisture behavior on its spatiotemporal domains and its complex relationships with forcing factors such as vegetation, soil texture, topography, and meteorology. The retrieval of soil moisture remains challenging due to limited satellite observations, the high correlation between different polarizations, angles, and channels, and the uncertainties in radiative transfer models and ancillary datasets.
As part of this webinar, it is our great honor to invite Prof. Dr. Arnon Karnieli to discuss soil moisture retrieval from remote sensing data. He will discuss the OPTRAM model and its applications in worldwide rangelands. Prof. Dr. Maofang Gao will discuss soil moisture retrieval from L-band SAR data.
Title: EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data
Date: 12 February 2025
Time: 8:00 a.m. CET | 3:00 p.m. CST Asia | 9:00 a.m. EET
More information: https://sciforum.net/event/Topics-31
This is a free webinar. After registering, you will receive a confirmation email containing information on how to join the webinar. Registrations with academic institutional email addresses will be prioritized.
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Program:
| Speaker/Presentation | Time in CET | Time in CST Asia |
| Prof. Dr. Maofang Gao (Chair) Chair Introduction |
8:00-8:10 | 15:00-15:10 |
| Prof. Dr. Maofang Gao Soil Moisture Retrieval From L Band SAR Data and its Applications in Southwest and Northeast China |
8:10-8:30 | 15:10-15:30 |
| Prof. Dr. Arnon Karnieli OPTRAM Model and its Applications in Worldwide Rangelands |
8:30-8:50 | 15:30-15:50 |
| Q&A Session | 8:50-9:10 | 15:50-16:10 |
| Prof. Dr. Maofang Gao (Chair) Closing of Webinar |
9:10-9:15 | 16:10-16:15 |
Webinar Chair and Speakers:
- Prof. Dr. Maofang Gao, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China;
- Prof. Dr. Arnon Karnieli, The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, Israel.
Relevant Special Issues:
“Root-Zone Soil Moisture Retrieval and Applications from Remote Sensing Measurements”
Guest Editors: Dr. David Fairbairn, Dr. Bertrand Bonan and Dr. Luca Brocca
Deadline for manuscript submissions: 31 August 2025
“Salinity Monitoring and Modelling at Different Scales: 2nd Edition”
Guest Editors: Dr. Maria da Conceição Gonçalves, Dr. Mohammad Farzamian and Dr. Tiago Brito Ramos
Deadline for manuscript submissions: 28 February 2025