Soil moisture information for risk anticipation

isardSAT’s soil moisture is a 1-km satellite-based product offering historical and up-to-date soil moisture data and drought index in any place in the world. Information is provided for surface and for any depth of the root-zone level. The product has been extensively validated across the globe, offering superior performance in semi-arid to arid regions. Data is available globally, without the need of local calibration.

Drought indices

Drought indices help to easily understand and quantify anomalies intensity by comparing values of soil moisture at different points in time. Drought indices are available at root and surface level, with different time steps and for different periods, including comparison with historical average values.

  • Drought index (seasonal anomalies)
  • Weekly deficit index

Contact us for personalized data aggregation and info.

Soil Moisture

The product is particularly suitable for application in semi-arid and arid areas, for its sensitivity in identifying basins, rivers and irrigation districts not captured in existing open data.

  • Available at Surface and root-zone level since 2010 and up to 1950 for specific cases.
  • 1 km resolution every 2-3 days or better (depending on latitude).

Contact us for personalized data aggregation and info.

Excellence

isardSAT product captures trends in watersheds, large-scale agricultural fields and assets. Its accuracy is clearly visible in its sensitivity to basins, rivers and irrigation districts not correctly represented by existing open-access products. Our product also correlates very well with precipitations, demonstrating the superior quality of the product and its accuracy. Please contact us if you wish to know more about this.

Methodology

The product is developed by leading scientists in remote sensing and climate risk. Data is computed through the use of the Dispatch disaggregation algorithm (Merlin et al. 2013, Escorihuela et al., 2018; Stefan, V. et al., 2021) that increases the spatial resolution of ESA SMOS and SMAP missions’ passive microwave observations from 40km to 1km, by combining data from Sentinel 1, 2 and 3, among others.

Optimal for large areas with 1km resolution

No need for local calibration

Global coverage and low latency

High performance also in semi-arid regions

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Fields of application

Soil moisture plays a crucial role in exchange of water, energy and biogeochemical fluxes between the atmosphere and the land surface. For this reason it is used in hydrological modeling and risk index, with application in agriculture, insurance, land monitoring and it is key in the anticipation of hydrometeorological disasters, such as drought and floods, among others.

Agriculture

High resolution large-scale information helps in crop yield estimation and irrigation practices, as well as to select crops suitable for the future climate.

Risk anticipation

Soil moisture is a precursor of prolonged droughts and of correlated risks, such as fires. It is a good indicator of locust breeding optimal conditions, helping to anticipate invasion with months in advance. It also improves flood forecasting, by informing about soil saturation and its capability to absorb additional water from storms.

Insurance

Insurance sector uses soil moisture to develop parametric products, which pay out if a certain predefined limit is reached. We provide long time series for analysis and monitoring services.

Hydrological modelling

Soil moisture data improve hydrological modeling by providing accurate estimation of precipitation, run-off of the soil, river flows based on soil water saturation and risk of flood.

Forest and land management

Soil moisture is an important indicator of the hydrological health of ecosystems. By monitoring correlation between forest changes and soil moisture it is possible to understand how the management of the forest is impacting the soil and its water content.

Wetland monitoring

Soil moisture is a critical data to understand and monitor wetland status and health. By offering consistent data, it helps in identifying changes, characterizing trends over time and support the management and protection of wetland resources.