Artists impression of the Soil Moisture and Ocean Salinity (SMOS) satellite. Image courtesy of ESA – P. Carril.
Two separate reports about the use of space data to enhance understanding of how the plant-water cycle operates caught our attention this week, as they relate to products and services we provide.
The first was the announcement that from the 11th June 2019 data from ESA’s Soil Moisture and Ocean Salinity (SMOS) mission are being incorporated into the European Centre for Medium-Range Weather Forecasts (ECMWF) forecasting system to improve the accuracy of their soil moisture measurements.
We also use SMOS data for the measurement of soil moisture, although some of our products combine EUMETSAT’s Advanced SCATterometer (ASCAT) data to improve coverage. Our products provide a daily observation update, while the ECMWF Integrated Forecasting System is a numerical weather prediction model that provides weather forecasts twenty-four hours a day, every day of the year. The SMOS data will improve their understanding of the spatial distribution of water in the soil, and how the plant-water cycle operates within the model.
It’s not been easy to get to this point for ECMWF as producing geophysical soil-moisture measurements takes around eight hours after sensing, and recent development is the result of a fifteen-year journey. They are using machine learning to improve the processing speed to within seconds of the data being available, enabling soil moisture to be part of the forecasting model. We already verify our products against ECMWF hindcast products, and their improvements will also us to refine this.
The second interesting article also reported last week, by the BBC, was the work of UK scientists who are leading work to try and persuade the European Union to add a Land Surface Temperature Monitoring (LSTM) mission to its Copernicus Programme. We talked about the future Copernicus mission in a recent blog.
The work, led by Prof Martin Wooster at King’s College London, is about to collect airborne heat maps over various parts of Europe using the Hyperspectral Thermal Emission Spectrometer (HyTES). The aim is to develop datasets on ground conditions and the response of crops to drought, which could be used to calibrate the satellite’s sensors.
LSTM would measure land temperatures of individual fields of crops to a spatial resolution of 40 m, improving the accuracy of estimates of plant’s water-use, transpiration and their stress from lack of water as the data would be in near-real time. This would help predict droughts and improve agriculture yields. It’s hoped the mission could be operational within ten years.
Similarly, we also have land surface temperature products data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument carried onboard both the Aqua and Terra satellites, and data from Landsat 8. We’ve also been working with Sentinel-3 to see if this can be added to develop the product further.
It’s exciting to see these new developments in the areas we are working in. From a commercial viewpoint, it means we need to be on our toes to make sure Pixalytics products continue to develop, but from an Earth Observation viewpoint it is great to see the expansion of products and use of this data
