Advancing our understanding of land surface interactions via the development of innovative geoinformation tools

Advances in geo-information technologies, including Earth Observation (EO), GIS, cloud computing and software tool development, have shown great potential towards addressing key societal challenges faced today associated with the study of land-atmosphere interactions. Accurate information on spatially explicit, distributed estimates of land-atmosphere fluxes and soil surface moisture is essential in a wide range of disciplines, including meteorology, hydrology, agriculture and ecology.

Use of simulation process models has played a key role in extending our abilities to study Earth system processes and enhancing our understanding on how different components of it interplay. A special category of such models includes the so-called Soil Vegetation Atmosphere Transfer (SVAT) models. Those are deterministic simulation models that describe the physical processes controlling energy and mass transport in the soil/vegetation/atmosphere system.

 

SimSphere is such a software toolkit written in Java for simulating the interactions of soil, vegetation and atmosphere layers of the Earth’s land surface. Its use is at present continually expanding worldwide both as an educational and as a research tool for scientific investigations. It is being used either as a stand-alone application or synergistically with EO data and important advancements particularly in the recent years have been implemented to the model.

 

Herein, we present state of the art advancements introduced recently to SimSphere SVAT model aiming at making its use more robust when integrated with EO data via the so-called “triangle” method. Use of the recently developed add-on to SimSphere is illustrated herein using a variety of examples that involve both satellite and UAV data. The presented work  is of key significance to the users' community of the model and very timely, given that variants of the so-called “triangle” method being considered for deriving operationally regional estimates of energy fluxes and soil moisture from EO data provided by non-commercial vendors.

KEYWORDS: land surface interactions, geoinformation, earth observation, triangle, SimSphere   Acknowledgements The research presented herein has been conducted in the framework of the project LISTEN-EO (DeveLoping new awareness and Innovative toolS to support efficient waTer rEsources man- agement Exploiting geoinformatiOn technologies), funded by the Hellenic Foundation for Research and Innovation programme (ID 15898).