LabEarthObs

1. Spaceborne Earth observation mission concepts

The design of a minisatellite FLOwer constellation (FC), deploying millimeter-wave (MMW) scanning RADiometers, namely, FLORAD, and devoted to tropospheric observations, is analyzed and discussed in this work, as an example . The FLORAD mission is aimed at the retrieval of thermal and hydrological properties of the troposphere, specifically temperature profile, water-vapor profile, cloud liquid content, and rainfall and snowfall rate. The goal of frequent revisit time at regional scale, coupled with quasi-global coverage and relatively high spatial resolution, is here called pseudo-geostationary scale and implemented through a FC of three minisatellites in elliptical orbits. FCs are built on compatible (resonant) orbits and can offer several degrees of freedom in their design. The payload MMW channels for tropospheric retrieval were selected following the ranking based on a reduced-entropy method between 90 and 230 GHz. Various configurations of the MMW radiometer multiband channels are investigated, pointing out the tradeoff between performances and complexity within the constraint of minisatellite platform. Statistical inversion schemes are employed to quantify the overall accuracy of the selected MMW radiometer configurations.

2. Spaceborne remote sensing of snow cover

Snow is an essential component of the water cycle. Seasonal snow cover is the largest cryospheric component of in areal extent, covering more than 50 million square kilometers of the Earth surface (more than 31% of its land area) every year. Snow cover area (SCA) and its local properties, in terms of snowpack height and snowpack density, are the main parameters characterizing the snow accumulation in mountainous regions. Such parameters result in particular importance in meteorology, hydrology, and climate monitoring applications.

Current research goals are: 1) to develop high spatial resolution mapping of the snow and ice cover by SAR interferometry (Sentinel 1) by means of statistical-neural approaches; 2) To develop snow cover fraction algorithms based on visible-infrared spectroradiometers data (Sentinel 2 and 3) by means of machine-learning approaches.

3. Spaceborne remote sensing of ocean surfaces

The Copernicus Space Component Expansion program includes new missions that have been identified by the European Commission as priorities for implementation in the coming years by providing additional capabilities in support of current emerging user needs. The passive microwave imaging mission, such as the Copernicus Imaging Microwave Radiometer (CIMR) is uniquely able to observe a wide range of parameters, in particular sea ice concentration, and serve operational systems under almost all-weather conditions, day, and night. This mission shall provide improved continuity of sea ice concentration monitoring missions, in terms of spatial resolution (about 15 km), temporal resolution (sub-daily), and accuracy (in particular, near the ice edges). Additional measurements of sea surface temperature in the polar regions may also be included.

Current research goals are: 1) to support the system design of CIMR to be compliant with its scientific requirements; 2) to develop polarimetric geophysical modeling of ocean surface CMR response by using statistical and machine learning approaches.

4. Spaceborne remote sensing of volcanic plumes

Volcanic eruptions produce columns of tephra (proximal cloud) which disperse in the form of ash (distal clouds). Volcanic eruptions are one of the most impressive natural phenomena to which our planet is subjected and which over the years have influenced human life. During explosive eruptions a great amount of volcanic particles are ejected in the atmosphere and can remain suspended for days, also creating aviation traffic impairments. Orbiting satellite observations can provide a large amount of daily data. The global perspective offered by Geosynchronous Earth Orbit (GEO) and Low Earth Orbit (LEO) satellite systems is of vital importance for the monitoring of volcanoes, especially those in remote and inaccessible areas. Data from LEO satellite visible-infrared (VIS-IR) spectroradiometers (e.g., VIIRS, AVHRR), but also from microwave radiometers (MHS, ATMS), can be used.

Current research goals are: 1) to develop synergistic techniques exploiting radiometric measurements in the visible-infrared but also millimeter wave ones for estimating the proximal cloud for observation and mapping on a global scale ; 2) to combine the latter with microwave meteorological radar observations in synergy with other ground sensors. Both approaches are essential for the initialization of dispersion models for prevention and protection applications.

5. Spaceborne remote sensing of coastline water

Costal water is an essential component of the water cycle and water quality chain. Recent optical remote sensing satellite missions, such as Sentinel-2 with the MultiSpectral Imager (MSI) on board, allow the estimation of coastal water key parameters with very high spatial resolutions (down to 10 m). Multiple approaches are proposed for retrieving chlorophyll-a (Chl-a) and total suspended matter (TSM) along the Adriatic and Tyrrhenian coasts in Italy, using both empirical and model-based frameworks to design regressive and neural network (NN) estimation methods. The latter proves to be more accurate on a regional scale, where standard ocean color physical models exhibit high uncertainty in their local parameterization due to the complex spectral characteristics of the observed scene.

Current research goals are: 1) to develop a high-spatial resolution estimation algorithms of the coastal waters from Sentinel 2 and 3 spectroradiometric measurements; 2) to use direct models and innovative algorithms (machine learning).

6. Spaceborne remote sensing of clouds and precipitation

The atmosphere can be quantified through atmospheric remote sensing. In particular: i) High spatial resolution mapping of atmospheric water vapor from SAR interferometry using multitemporal approaches. ii) Estimation and monitoring of clouds and extreme precipitation at kilometric resolution by multi-frequency microwave and millimeter-wave radiometers using direct models, innovative algorithms (machine learning) and data fusion. The forthcoming spaceborne Ice Cloud Imager (ICI) radiometer has 11 channels in the millimeter (mm) and sub-mm wave range from 183 up to 664 GHz. At some of these frequencies, the atmosphere is very opaque due to strong gaseous and cloud extinction, precluding the observation of the surface. We aim at investigating how to evaluate the ICI channels geolocation error using surface landmark targets. The most transparent ICI channels, i.e., those around 183.3 ± 7.0 GHz at vertical (V) polarization (ICI-1) and around 243.2 ± 2.5 GHz (ICI-4) at horizontal (H)/ V polarization, are considered.

Current research goals are: 1) starting from previous work, to extend the ICI database of the surface landmark targets to cover boreal and austral dry seasons at various latitudes. 2) to retrieve rainfall from the upcoming Copernicus Imaging Microwave Radiometer (CIMR).