Please login first
Events About
Contact
My Submissions
Topics Webinar | EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data

Topics Webinar | EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data

Topics Webinar | EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data

Part of the MDPI Topics Webinars series
12 Feb 2025, 08:00 (CET)

Registration Deadline
12 February 2025
Remote sensing, soil moisture, optical, SAR
Calendar
Bookmark
Bookmark event Remove event from bookmarks
Add this event to bookmarks
Event Registration Contact Us

Welcome from the Chair

EO&GEO Series: Soil Moisture Retrieval from Remote Sensing Data

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 special 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 several 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 been able to provide soil moisture estimations at different spatial scales from meters to tens of kilometers, as well as temporal resolutions from hours to daily.

However, obtaining reliable soil moisture information at the required spatial/temporal resolution and along soil depth with a high accuracy level 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, as well as uncertainties in radiative transfer models and ancillary datasets.

In this webinar, it's our great honor to invite Prof. Dr. Arnon Karnieli to discuss soil moisture retrieval from remote sensing data. He will talk about the OPTRAM model and its applications in worldwide rangelands. The Chair-Prof. Dr. Maofang Gao will talk about soil moisture retrieval from L band SAR data.

Date: 12 February 2025
Time: 8:00 am CET | 3:00 pm CST Asia | 9:00 am EET
Webinar ID: 868 0301 6682
Webinar Secretariat: journal.webinar@mdpi.com

Event Chair

Prof. Dr. Maofang Gao

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China

Introduction
Bio
Maofang Gao, PhD., Professor. Youth Chief of Agricultural Remote Sensing Innovation Team, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences. She has been engaged in agricultural remote sensing, remote sensing and crop model assimilation research for more than 20 years. She is the project leader of several national project from National Natural Science Foundation of China and Ministry of Science and Technology. She published more than 50 peer review paper in international famous journals. She has 9 national invention patents with first author.

Invited Speakers

Prof. Dr. Arnon Karnieli

The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, Israel

Introduction
Talk
Presentation Title: OPTRAM Model and Its Applications in Worldwide Rangelands
Bio
Prof. Arnon Karnieli (Mail) received his Ph.D. from the University of Arizona, Tucson, in 1988. Since then, he has been the Head of the Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker Campus, Israel. His primary research is focused on processing spaceborne, airborne, and ground spectroscopic data of drylands concerning desertification and climate change processes. In this regard, his study’s applications cover dryland ecosystems and agriculture, and to a lesser extent, dust/aerosols and coastal water. He has experience in land-use and land-cover change, spectral, spatial, and temporal analyses. Prof. Karnieli is the Israeli Principal Investigator of the Vegetation and Environmental New Micro Spacecraft (VENμS) mission. Until recently, Prof. Karnieli supervised tens of Master students, 15 Ph.D. students, and several post-docs. Prof. Karnieli has published more than 250 papers in peer-reviewed journals. His H index = 52 (ISI).

Prof. Dr. Maofang Gao

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China

Introduction
Talk
Presentation Title: Soil Moisture Retrieval From L Band SAR Data and Its Applications in Southwest and Northeast China
Bio
Maofang Gao, PhD., Professor. Youth Chief of Agricultural Remote Sensing Innovation Team, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences. She has been engaged in agricultural remote sensing, remote sensing and crop model assimilation research for more than 20 years. She is the project leader of several national project from National Natural Science Foundation of China and Ministry of Science and Technology. She published more than 50 peer review paper in international famous journals. She has 9 national invention patents with first author.

Registration

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.

Certificates of attendance will be delivered to those who attend the live webinar.

Can’t attend? Register anyway and we’ll let you know when the recording is available to watch.

Event Registration

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

Presentation Title: 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

Presentation Title: 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

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

Relevant Articles

Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS
ISPRS Int. J. Geo-Inf. 2023, 12(7), 271; https://doi.org/10.3390/ijgi12070271

Comparative Analysis of Algorithms to Cleanse Soil Micro-Relief Point Clouds
Geomatics 2023, 3(4), 501-521; https://doi.org/10.3390/geomatics3040027

High-Precision Mapping of Soil Organic Matter Based on UAV Imagery Using Machine Learning Algorithms
Drones 2023, 7(5), 290; https://doi.org/10.3390/drones7050290

Sponsors and Partners

Organizers

Top