Microwave Remote Sensing of Vegetation Water Dynamics

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 Water Management, and the Department of Geosciences and Remote Sensing at Delft University of Technology (TU Delft).  

People Publications

Research Highlights

Sentinel-1 for Agriculture

Our recent study shows that 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.

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ASCAT Dynamic Vegetation Parameters

Our latest research demonstrated that the seasonal, interannual and diurnal variations in the new “dynamic vegetation parameters” derived from ASCAT reflect vegetation phenology and moisture content variations in soil and vegetation.

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Microwave Remote sensing for Physiology and Ecology

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.

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Joint assimilation of microwave and thermal data

SMAP and thermal data are assimilated into a land surface model using particle filtering and smoothing to obtain consistent soil moisture and surface energy fluxes.

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