Developing high resolution Soil Moisture Estimates from Satellites
Welcome to SoMoSAT, funded by the Environmental Protection Agency, which is developing high resolution soil moisture estimates for Ireland. SoMoSAT is a multi-partner and multi-disciplinary team, comprised of computer scientists, Earth Observation specialists, land surface modellers, soil experts, catchment and climate scientists and wireless sensor communications researchers, all working together to understand the factors that contribute to soil moisture at a location and across scales. Collaborators include Teagasc, the Agriculture and Food Development Authority, and Net Feasa.
SoMoSAT is employing the latest technologies, data infrastructure and computational workflows to address the needs of the research, agricultural and hydrological community for accurate, reliable estimates of soil mositure.
In spite of the recognised importance of soil moisture interactions on climate, and its relevance for understanding hydrological, agricultural and ecological processes, there is a limited number of soil water observations globally.
Even at the regional or country scale, few observations are typically available and many of these are limited in duration and/or extent. Alternative techniques are required to derive estimates of soil moisture. These include water balance based approaches, such as soil–vegetation–atmosphere transfer (SVAT) models, the use of remotely sensed information (SMAP, AMSR2, SMOS, ASCAT) or the application of land surface modelling (LSM) techniques.
Satellite based techniques offer significant potential for deriving estimates of soil moisture at high spatial and temporal resolutions, however, their use is non-trivial.
The use of neural networks, artificial intelligence and machine learning techniques to combine data from both active (microwave) and passive (radiometers) satellite sensors are increasingly being employed to derive high spatio-temporal resolution soil moisture estimates, which address the complexity/issues of single sensor based approaches; merged active and passive data products have been shown to generally outperform single sensor based approaches
This project is funded under the EPA Research Programme 2014-2020. The EPA Research programme is a Government of Ireland initiative funded by the Department of the Environment, Climate and Communications. It is administered by the Environmental Protection Agency, which has the statutory function of co-ordinating and promoting environmental research.
DISCLAIMER: Although every effort has been made to ensure the accuracy of the material contained in this website, complete accuracy cannot be guaranteed. Neither the Environmental Protection Agency nor the authors accept any responsibility whatsoever for loss or damage occasioned or claimed to have been occasioned, in part or in full, as a consequence of any person acting or refraining from acting, as a result of a matter contained in this website.
Now Dr. Rowan Fealy & Prof. Tim McCarthy, Terrain AI @MaynoothUni, speaking about “Terrain AI – Accelerating our Understanding of Carbon Reduction” @Maynoothgeog #TerrainAI @IRLDeptPER #ODImpact #ClimateAction #OpenData #Environment #carbonemissions #carbonneutral Originally tweeted by Derilinx (@derilinx) on April 20, 2021.
The second Panel Conversation is on: “Research and Innovation and Open Data – Climate Change” with Gavin Smith, Prof. Brian Ó Gallachóir, Rowan Fealy, Tim McCarthy and Charlotte O’Kelly @EPAIreland @MaREIcentre @MaynoothUni @Maynoothgeog @TechWorksMarine @IRLDeptPER #ODImpact Originally tweeted by Derilinx (@derilinx) on April 20, 2021.
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