*4.12. Surface Soil Moisture*

The soil moisture is a key parameter to understand the water cycle, and in cryosphere regions, it provides information about the freeze-thaw cycles. Several remote sensing technologies have been proposed to estimate soil moisture. Two criteria were selected to perform the technology categorization. The first one is related to the region of the spectrum (optical or microwave). Optical instruments acquire soil moisture measurements using the Thermal Infrared (TIR). Microwave instruments use signals in the L-, S- and C-bands. L-band is the main frequency band to acquire soil moisture due to its large sensitivity and its direct relationship with the soil water content [49]. The second criterion is related to the way of measuring: passive vs. active microwave instruments.

Microwave sensors do not rely on Sun illumination and are able to work in all weather and illumination conditions. This particular characteristic is especially important in polar regions that have long dark periods in winter and where it is cloudy most of the time. This feature also makes microwave sensors more suitable than optical sensors in this region. Several missions have been launched with active microwave instruments, which can be grouped into two main families: SAR and radar scatterometers. Current SAR instruments for the C-band are Sentinel-1A and Sentinel-1B, RADARSAT-2, the Radar Imaging Satellite-1 (RISAT-1)and Gao Fen-3 (GF-3). They provide dual polarization and multi-polarization data. Soil moisture estimation by Sentinel-1 is derived from the Advanced Synthetic Aperture Radar (ASAR) algorithm [50]. Operational SAR sensors in the S-band are HJ-1A/B/C and in the L-band the one on the Advanced Land Observing Satellite-2 (ALOS-2). The main limitations of these instruments are: the narrow swath, the dependence on the vegetation cover and the surface roughness and the speckle noise that makes SAR images appear very noisy. The main limitation of the SAR system for soil moisture is also the lower accuracy, as compared to passive microwave data.

The SMOS mission of the ESA was the first satellite dedicated to providing global soil moisture data [51,52]. SMOS-derived soil moisture products have an accuracy of 0.04 m3/m3 at a spatial resolution ranging from 35–50 km, as well as a revisit time of 1–3 days. Before SMOS, soil moisture measurements were performed using passive microwave radiometers [53] at 7 and 10 GHz (AMSR; AMSR-2; AMSR-E; the Multi-frequency Scanning Microwave Radiometer, MSMR). However, at these frequencies, soil moisture measurements are more affected by the vegetation cover. On the other hand, the L-band offers additional advantages such as less atmospheric attenuation than at higher frequencies and additional smaller water content effects (up to at least 5 kg/m). GNSS-reflectometry is another potential technology, so far having modest accuracy, that can be implemented even in CubeSats for soil moisture measurements. Data fusion between microwave radiometry, optical and SAR can improve the spatial resolution and accuracy of soil moisture measurements, as has been demonstrated in the SMOS and the Soil Moisture Active-Passive (SMAP) missions [54].

## *4.13. Monitoring System: Vessel and Fish Farming Cage Position Tracking*

Norsat-2 and Triton-2 are contributing missions under the Advanced Research in Telecommunications Systems (ARTES) program by ESA. Spaceborne SAR and AIS can also be considered complementary systems to improve the security and surveillance services for maritime navigation.

#### **5. Discussion**

The aim of this section is to establish the promising technologies and to address the technological challenges, to ensure they satisfy the measurement requirements for the observation gaps detected in the Copernicus space segment. As shown in Table 3, the measurements with gaps detected in this study can be monitored by different types of sensors. According to the state of the art of the potential payloads to cover the gaps of the Copernicus space infrastructure in 2020–2030, the next generation of instruments require overcoming challenges and new technological developments in order to meet the end-user requirements.

GNSS-R is a promising technology to detect surface currents, significant wave height, sea ice cover, horizontal wind speed, dominant wave direction and sea ice thickness. The advantage of this technology is that it can process data in real time and onboard, through the use of Delay-Doppler Mapping (DDM); in this way, the latency time can be improved. However, the next generation of GNSS-R sensors should improve the spatial resolution to <10 km and the accuracy to <1 cm and <0.5 m/s, in order to meet the end-user requirements. In this regard, a precise clock module is required to reduce the errors in the retrieval computation.

For the passive microwave, a spatial resolution of <25 km is feasible by increasing the size of the antenna and would be suitable on CubeSats, as well as meet the spatial resolution requirement for atmospheric pressure over the sea surface. Microwave radiometers on small platforms demand the use of inflatable antennas in order to improve the spatial resolution and meet the end-user requirements, covering a variety of measurements between sea ice parameters, ocean conditions and sea surface temperature.

Future cloud radar, radar altimeters, LiDAR and SAR are required to improve the coverage and adopt the use of a new concept to allow a wide-swath. For the the next generation of scatterometer, it is imperative to improve the accuracy for horizontal wind speed over the sea surface <0.5 m/s with a spatial resolution <10 km, in order to meet the user requirements.

Optical sensors (such multispectral, hyperspectral radiometers and spectrometers) can monitor many variables with gaps, but the data can only be acquired in daylight and clear sky, a limiting factor for observing polar regions, where it is very often cloudy and the dark period is long. However, they are a good complement to microwave sensors, where the fusion of data could result in better products in terms of spatial resolution and accuracy.
