The Radio Regulations (RR) is the international treaty describing the rules for use of the electromagnetic spectrum. The RR are revised approximately every four years during World Radiocommunication Conferences (WRCs), organized by the International Telecommunication Union (ITU). During the last WRC, held at the end of 2023, several decisions have been made that are relevant for Earth Observation (EO). In addition, the last WRC has set the agenda for the work to be carried out in preparation for the next WRC, in 2027, which again may have significant implications for EO science.This paper presents the decisions made at WRC-23 that are relevant for the remote sensing community, including the agenda for WRC-27.

This paper will present the status of the on-going and planned mission concept studies in the period 2023 to 2025 in the frame of the ESA’s Future Earth Observation Programme (FutureEO).The European Space Agency (ESA) is conducting preparatory activities on innovative Earth Observation (EO) missions to foster better scientific understanding of the Earth system through research missions, respond to the requirements of the operational users via operational missions and assess the potential of "Newspace" approach with smallsat Earth Observation concepts to boost innovation through the Φsat missions.ESA’s program of EO research missions comprises Earth Explorers, Scouts and Mission of Opportunity. Earth Explorer missions objective is to advance Earth science by providing answers to key scientific questions on the Earth system. Up to date, five Earth Explorers have been launched and another five are in different stages of development. ESA’s Earth Explorer 11 mission candidates (CAIRT, Nitrosat, SEASTAR and WIVERN) are undergoing Phase 0 activities while preparatory activities to study mission concepts for the Earth Explorer 12 are expected to start in 2024.Missions of Opportunity are research missions implemented under cooperation frameworks with Space Agencies outside Europe and Canada. Next Generation Gravity Mission (NGGM) is a candidate Mission of Opportunity for ESA-NASA cooperation in the framework of MAGIC (MAss change and Geosciences International Constellation).Scouts are small budget research mission based on small satellites or CubeSats, implemented in three years and complementing Earth Explorers. Two mission concepts, TANGO and NanoMagSat, are currently undergoing risk retirement activities.Preparatory activities for operational mission are underway for the next generation of Sentinels in the frame of the Copernicus programme (e,g. Sentinel-2 Next Generation and Sentinel-3 Next Generation Optical, which are currently in phase 0) in close coordination with the European Commission). Preparatory activities are planned in the coming years for the next generation of meteorological missions (Meteosat 4thGeneration and EPS/MetOp 3rdGeneration) in close coordination with EUMETSAT.Φsat missions are CubeSat missions aimed to demonstrate radical and new technologies or remote sensing concepts in space, such as Φsat -2, which is currently under development and is focused on onboard Artificial Intelligence applications.

The Copernicus programme [1] is a European system for monitoring the Earth in support of European policy as developed by the European Commission (COM). It includes Earth Observation (EO) satellites (notably the Sentinel series developed by the European Space Agency (ESA)) that form part of the Copernicus Space Component (CSC). The Copernicus Imaging Microwave Radiometer (CIMR) mission [2] is one of six Copernicus Expansion (CopEx) Missions [3] that address emerging and urgent needs for new types of global coverage observations with a particular focus on monitoring Polar regions.

Accurate knowledge of the dielectric constant of sea water is important for remote sensing of surface parameters such as sea surface temperature (SST) and sea surface salinity (SSS). The advent of sensors in space, SMOS [1] , Aquarius [2] and SMAP [3] capable of measuring SSS motivated modern measurements [4] , [5] and modelling [5] , [6] of the dielectric constant at L-band (1.4 GHz). In the past, the range of salinity included in the data used to create these models has been restricted to values typically encountered in the open ocean (e.g., less than 40 psu). However, there are many smaller water bodies with much higher salinity. Notable examples are the Great Salt Lake in Utah with salinity on the order of 180 psu and Garabogazköl lagoon in Turkmenistan with even higher salinity. Unfortunately, existing models for the dielectric constant can’t necessarily just be extended to higher values of salinity. The problem is that the polynomials in salinity and temperature used to represent the unknown parameters in the models are not constrained outside the range of SSS and SST used to determine their coefficients. While the models for the dielectric constant may be very good within that range, outside that range they can lead to unrealistic behavior. Research is underway to develop a model that represents the dielectric constant well over the ocean and behaves well at high salinity. In preparation for possible wideband remote sensing of salinity [7] , [8] , [9] , the laboratory measurements made at 1.413 GHz [4] , [5] are being repeated at 0.707 GHz (P-band) and the plan is to include values of high salinity (50, 100, 150 psu).

This paper presents an analysis of Radio Frequency Interference (RFI) in the 1.400-1.427 GHz frequency band. The study considers the sudden and strong increase of interference from a particular emitter in China that has been observed in July 2020 by radiometers from both ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's SMAP (Soil Moisture Active Passive) missions. It provides an example of the characterization of a source of RFI and illustrates the capabilities of the SMAP radiometer receiver and RFI processing incorporated in it to identify and understand interference.

Radio Frequency Interference (RFI) is a growing threat to all Earth Observation (EO) passive microwave missions. Many RFI detection algorithms are used on-board and in the ground segment data processing, but there is no single algorithm that can detect all RFI instances. The best strategy is always to combine several detection methods. This paper presents the results of the new Ground RFI Detection System (GRDS). The GRDS uses a combination of a wide variety of RFI detection algorithms to clean the Earth Observation measurements from RFI. The system is built to be able to scan for RFI for any EO mission. The initial results show the important reduction on RFI in the EO data as measured by the European Center for Mid-Range Weather Forecast (ECMWF) first guess departure statistics.

The radiometer on the NASA Soil Moisture Active/Passive (SMAP) mission is a fully polarimetric instrument that operates at L-band in the spectrum window at 1400–1427 MHz protected for passive use only. A unique feature of the radiometer is the fully digital back-end which permits direct computation of the third and fourth Stokes parameters: the real and imaginary part of the correlation of signal at horizontal and vertical polarizations, respectively. In particular, the SMAP conical scanning geometry provides the opportunity to look at the global distribution of the fourth Stokes parameter, TA4, at constant incidence angle (40°). A striking feature of TA4 is the existence of a strong (±10 K) spurious signal at coastlines. This article provides examples of the spikes and an explanation of the cause. Simulations have shown that the spurious signal is associated with antenna imperfections, such as cross polarization coupling and phase mismatch between polarizations.

Radio-frequency interference (RFI) has had a detrimental effect on L-band passive observatories such as SMOS, Aquarius and SMAP. A better knowledge of the characteristics of RFI signals might help mitigate this issue by leading to additional and better focused RFI detection algorithms and it might help identify RFI emitters on the ground. In this study we present approaches to retrieve some of the features of the RFI signals using SMAP data and we present some statistical considerations about the temporal and spectral characteristics of RFI sources.

We present a physics-based algorithm for retrieving sea surface salinity from L-band radiometric observations from the NASA SMAP instrument. The model is used to assess the radiometer calibration and its long-term stability and produce salinity products that are evaluated against in situ measurements from the Argo network of drifting floats.

Microwave remote sensing relies on the utilisation of the electromagnetic spectrum, which is becoming a precious commodity due to increasing demand by commercial telecommunication and other radio services. The access to this resource is regulated by the International Telecommunication Union, which periodically holds a World Radiocommunication Conference (WRC) where representatives from different countries meet to define international rules for its use.The next WRC will take place in November 2019, and the Frequency Allocations in Remote Sensing (FARS) Technical Committee of the IEEE Geoscience and Remote Sensing Society (GRSS) has prepared a report discussing the Agenda Items of the conference that are most relevant to remote sensing. This contribution will explain the issues at stake for remote sensing at WRC-19, illustrate the document conclusions and provide suggestions on what remote sensing scientists and engineers can do to become more involved in tackling these issues.

Even though the Sea Surface Salinity (SSS) retrieved from Aquarius are generally very close to in-situ measurements, the level of similarity varies with the region and with the circumstances of the observations (wind speed, sea surface temperature, etc.). SSS is currently retrieved from the brightness temperatures measured by Aquarius and applying the current theoretical model for the propagation and emission of the natural thermal radiation. In this contribution we consider an alternative retrieval approach based on a Neural Network (NN) with the goal of improving the subsets of Aquarius SSS data that are in poorer agreement with in-situ measurements. The subset considered here are the SSS retrieved at latitudes higher than 30 . The output of the NN approach are compared against in-situ measurements using four statistical metrics (correlation coefficient, bias, RMSD and 5% trimmed range). The output of the NN and the nominal Aquarius SSS are compared against SSS values from in-situ measurements and from ocean models. From these comparisons it appears that the output of the NN matches the in-situ measurements better than the nominal Aquarius SSS.

Measurements are reported of the fourth Stokes parameter as observed from space by the SMAP polarimetric radiometer. The SMAP radiometer has a digital back-end that provides fully polarimetric processing, including the direct measurement of the third and fourth Stokes parameters. The data provide a first look at the fourth Stokes parameter from space at L-band. Features are reported that can be associated with RFI and the characteristics of the antenna pattern. With processing to remove such effects, features associated with the surface, such as snow/ice over Greenland and land vegetation canopy have also been observed.

The Soil Moisture Active/Passive satellite microwave radiometer has been providing measurements of L-band thermal emission from Earth for more than 2 years. SMAP retrieves surface soil moisture from its brightness temperature measurements, and continues to provide science products to the user community. Even though the SMAP radiometer operates in a protected band, its measurements are still corrupted by Radio Frequency Interference (RFI) caused by illegal in-band transmissions or out-of-band emissions. The SMAP radiometer was designed to include special hardware to enable RFI detection and filtering using multiple detection algorithms. Given the good overall performance of SMAP algorithms to detect RFI sources, an automatic tool to report source properties automatically was developed and is now operational. This paper provides a preliminary analysis of the outputs of this reporting tool with a particular focus on the evolution of the RFI environment observed by SMAP during its period of operations.

Aquarius has produced maps of salinity by measuring Earth's natural emissions at L-band. However, measurements made by its instruments are affected by the presence of Radio Frequency Interference (RFI). For this reason, RFI detection algorithms had been implemented, both for the radiometer and the scatterometer, in order to reduce the impact of RFI on science data. In an effort to improve understanding of L-band RFI, the Aquarius mission has generated a new series of products. This contribution presents how these products were produced as well as the information that they contain. These products will be available starting at the end of January 2018 on the Aquarius website.

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI, which can then be reported; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is an additional RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

The land emissivity model used in the Aquarius data processing has been updated for the latest data release (V5.0). In order to improve the estimates of the brightness temperatures of frozen regions, the new model uses values of surface emissivity that have been estimated from the Aquarius measurements averaged over the entire duration of the mission. The retrieved emissivities depend on the geographic location, but they depend only marginally on time, temperature and snow cover.

The Soil Moisture Active/Passive (SMAP) satellite mission measures Earth's radiation in the protected portion of the spectrum at 1.413 GHz (L-band) to retrieve geophysical quantities of the surface, such as soil moisture and the frozen/thawed state of the soil. The presence of radio-frequency interference (RFI) in this band is significant and impacts the quality of SMAP measurements. Knowing the location of the sources of RFI is important, because it can help to identify the source itself and also be used to develop strategies to mitigate its impact of the RFI on the data. This paper presents an algorithm that takes advantage of the viewing geometry of SMAP to locate sources of RFI. The results are validated using known locations of RFI sources and by comparison with the measurements of Soil Moisture and Ocean Salinity (SMOS) and Aquarius, two other satellite missions with L-band microwave radiometers operating in the protected band. Comparison with RFI of known location suggests that the algorithm is accurate to 1-2 km. The median distance between the locations reported by SMOS and this algorithm is 2.27 km. A study of the relationship between the localization error and the number of observations of RFI sources shows that the median localization error is about 2 km with 12 observations and about 1 km with 30 observations.

Ocean salinity and soil moisture are key parameters for understanding the global water cycle, weather, and climate. These parameters are being measured with spaceborne radiometers operating in the L-band window at 1400-1427 MHz. Although man-made activity in this band is prohibited, radio frequency interference (RFI) is still a problem over significant portions of the earth. This paper reports a comparison of the RFI environment in this window as observed by two L-band radiometer systems, Aquarius and Soil Moisture and Ocean Salinity. The observed RFI environment depends on the sources and also on the characteristics of the instrument. Comparing the observations provides insight into the extent of the problem (actual sources), the influence of the instrument on the observation of RFI, and on potential ways of mitigating the effects. As this report shows, the global distribution of RFI is largely consistent between the two instruments, but the details, especially at low levels of RFI, depend on the characteristics of the instrument.

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space [1, 2]. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI), which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

In this communication we present an update on the RFI detection used in the SMOS processing chain and some elements on quantified impact of RFIs on level 2 soil moisture products. The level 2 soil moisture algorithms which included since the beginning a screening mechanism to reject contaminated brightness temperatures is now stricter. New approaches at the level 1 processors are also emerging and will be operational at their next release in 2014. Despite these strengthen procedures, RFIs are still impacting strongly SMOS observations and examples of quantified deterioration are given.

The Soil Moisture and Ocean Salinity (SMOS) mission is a European Space Agency project aimed to observe two important geophysical variables, i.e., soil moisture over land and ocean salinity by L-band microwave imaging radiometry. This work is concerned with the contamination of the SMOS data by radio-frequency interferences (RFIs), which degrades the performance of the mission. In this paper, we propose an approach that detects if a given snapshot is contaminated, or not, by RFI. This approach is based on evaluating the kurtosis of each snapshot or data set, using all interferometric measurements provided by the instrument. The obtained kurtosis is considered as an indicator on how much the snapshot is polluted by RFI, thus allowing the user to decide on whether to keep or discard it.

The Soil Moisture and Ocean Salinity (SMOS) satellite was launched by the European Space Agency on November 2, 2009. Its payload, i.e., Microwave Imaging Radiometer with Aperture Synthesis, which is a 2-D L-band interferometric radiometer, measures the brightness temperatures (BTs) in the protected 1400-1427-MHz band. Although this band was preserved for passive measurements, numerous radio frequency interferences (RFIs) are clearly visible in SMOS data. One method to get rid of these interferences is to create a synthetic signal as close as possible to the measured interference and subtract it from the instrument visibilities. In this paper, we describe an approach to create such a signal and on how to use it for geolocalization of the emitters. Then, different methods for assessing the quality of the mitigation are introduced. Due to the complexity of estimating the effects of mitigation globally, it is finally proposed to use mitigation results to create flag maps about the estimated RFI impact, to be associated with BT measurements.

Artificial sources emitting in the protected part of the L-band are polluting the retrievals of ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. Detection and localization of such sources are of interest for the exploitation of science products as well as for the identification of the emitters. A simple and fast method that provides snapshot-wise information is presented. From a statistical analysis of the results, some systematic errors are reported along with their potential causes and an approach to mitigate them. In the case of sources at high geomagnetic latitudes a seasonal variation of the localization error is also noticed; the origin of such phenomenon is still under investigation.

The Soil Moisture and Ocean Salinity (SMOS) satellite was launched by ESA on November 2nd, 2009. Its payload MIRAS, is a two-dimensional L-band interferometric radiometer, and it measures brightness temperatures (BT) in the protected 1400-1427 MHz band. Although this band was preserved for passive measurements numerous radio frequency interferences (RFIs) are clearly visible in SMOS' data. One method to get rid of these interferences is to create a synthetic signal as close as possible to the measured interference and subtract it from the instrument's visibilities. Here is described how to create such a signal and how to use it for geo-localization of the sources. Then different methods for assessing the quality of the mitigation are introduced. A possible explanation for the dissimilarity of RFI sources as seen by SMOS is also advanced.