Toward a forest biomass reference measurement system for remote sensing applications.

Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA-ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation.

Increasing stratification as observed by satellite sea surface salinity measurements.

Changes in the Earth's water cycle can be estimated by analyzing sea surface salinity. This variable reflects the balance between precipitation and evaporation over the ocean, since the upper layers of the ocean are the most sensitive to atmosphere-ocean interactions. In situ measurements lack spatial and temporal synopticity and are typically acquired at few meters below the surface.

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass.

Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS).

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR).

The high spatio-temporal variability of soil moisture is the result of atmosphericforcing and redistribution processes related to terrain, soil, and vegetation characteristics.Despite this high variability, many field studies have shown that in the temporal domainsoil moisture measured at specific locations is correlated to the mean soil moisture contentover an area. Since the measurements taken by Synthetic Aperture Radar (SAR)instruments are very sensitive to soil moisture it is hypothesized that the temporally stablesoil moisture patterns are reflected in the radar backscatter measurements.