We use microwave remote sensing to monitor the transport of water through vegetation from the land surface to the atmosphere in order to understand the role of vegetation in the water, energy and carbon cycles. We perform research from field to global scales, combining in-situ and spaceborne sensors to improve our understanding of the influence of vegetation water dynamics on radar observables. Our research embraces the latest developments in modeling, data assimilation and machine learning to exploit existing spaceborne radar instruments for a wide range of applications in ecosystem and agricultural monitoring, and prepare for future missions.
The M-WAVE research group is lead by Prof. Susan Steele-Dunne from the Department of Geoscience and Remote Sensing at Delft University of Technology (TU Delft).
People Publications
To support the development of the SLAINTE mission concept, we are installing a network of GNSS sensors to measure L-band attenuation in forested areas. All sensors are located close to flux towers and dendrometry and/or sap flow sensors, allowing us to relate L-band attenuation to vegetation water dynamics. These measurements will be used to strengthen the science case for SLAINTE and contribute to the consolidation of requirements.
SLAINTE is a new mission concept for a constellation of SARs to provide insight into vegetation health, stress and resilience by observing vegetation water dynamics. Initiated as an ESA New Earth Observation Mission Idea (NEOMI), the concept was further developed and submitted in response to ESA's 12th call for Earth Explorers.
Mission overview Technical concept
The slope of the relation between microwave backscattering coefficient and incidence angle from ASCAT is sensitive to vegetation water dynamics. We have developed a new method to estimate the ASCAT backscatter-incidence angle relation using temporally constrained least squares. This new approach captures the timing of short-term changes, allowing us to isolate high-frequency variations due to intercepted precipitation and soil moisture changes from changes due to biomass and water status.
New approach to estimate slope - full paper ASCAT slope reveals vegetation dynamics in Amazonia ASCAT dynamic vegetation parameters in grasslands
Together with ESA, we generated a database of processed, parcel-level Sentinel-1 data for the Netherlands that can be queried by crop type, administrative boundary and time. We hope that this will stimulate new users to explore potential applications of SAR data in agricultural monitoring.
Link to database Link to data paper Sandbox NL data used to study drought Sandbox NL data used to train ML model for Sentinel-1
Sucrose content affects the dielectric properties of sugar cane. We showed that Sentinel-1 backscatter, and particularly the Sentinel-1 (VH/VV) cross-ratio are sensitive to sucrose accumulation. This opens new opportunities for sugar cane monitoring and yield prediction.
Link to full paper
Sentinel-1 data have significant potential value to monitor growth and development of key Dutch crops. Furthermore, the guaranteed availability of Sentinel-1 imagery in clouded conditions ensures the reliability of data to meet the real-time monitoring needs of farmers, food producers and regulatory bodies.
Link to full paper
This review discusses the relationship between landscape‐scale plant water content from microwave RS and common stand‐scale metrics, including plant‐scale relative water content, live fuel moisture content and leaf water potential.
Link to review paper