Selection of the Key Earth Observation Sensors and Platforms Focusing on Applications for Polar Regions in the Scope of Copernicus System 2020–2030

Abstract

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.

1. Introduction

The Copernicus system, previously known as Global Monitoring for Environmental Security (GMES), is a revolutionary program of the European Union (EU) to address the end-user requirements over six thematic services: Atmosphere, Marine, Land, Climate Change, Emergency Management, and Security. Copernicus is supported by the space and in situ components. The space segment is based on a set of Earth Observation (EO) satellites known as the Sentinels and some contributing missions. Contributing missions with space infrastructure are the Earth Explorer missions [1] operated by the European Space Agency (ESA), the meteorological missions operated by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and EO missions operated by the European Union (EU), third countries, and commercial providers.

Currently, there are seven Sentinels satellites in orbit: Sentinel-1A and Sentinel-1B with C-band Synthetic Aperture Radar (SAR) for land and ocean observation, Sentinel-2A and Sentinel-2B with high resolution optical imager called Multi-Spectral Imager (MSI) for land and vegetation observation, Sentinel-3A and Sentinel-3B with a suite of instruments such as Synthetic Aperture Radar altimeter (SRAL), and medium resolution optical imager: Ocean and Land Colour Imager (OLCI) and Sea and Land Surface Temperature Radiometer (SLTR) for ocean and land observation, and Sentinel-5P with cross-nadir scanning sounder called Tropospheric Monitoring Instrument (TROPOMI) for atmospheric chemistry and aerosol studies. Future Sentinel missions that will be launched in the next decade are Sentinel-4 for atmospheric chemistry as hosted payload over Meteosat Third Generation-Sounding (MTG-S); Sentinel-5 will be launched as hosted payloads over MetOp-Second generation (MetOp SG) for atmospheric chemistry, aerosol and spectral irradiance studies; and Sentinel-6 will be launched in a Low Earth Orbit (LEO) inclined over the equator for ocean altimetry as an international program between ESA, the National Aeronautics and Space Administration (NASA), the National Centre for Space Studies (CNES), EUMETSAT, and the National Oceanic and Atmospheric Administration (NOAA). Additionally, the third and fourth units of Sentinel-1C/D, Sentinel-2C/D, and Sentinel-3C/D will have planned to launch for the continuity of these programs.

At present, Earth Explorer missions are: Soil Moisture and Ocean Salinity (SMOS) launched on 2 November 2009 for sea surface salinity and soil moisture monitoring; this is considered as a potential gap because this mission has no continuity; Atmospheric Dynamics Mission—Aeolus (ADM-AEOLUS) launched on 22 August 2018, with an Atmospheric Laser Doppler Instrument (ALADIN) for contribution to aerosol observation and wind profile. Future Earth Explorer missions are: EarthCARE mission with a suite of instruments such as a Atmospheric Lidar (ATLID), Broad-Band Radiometer (BBR), Cloud Profiling Radar (CPR), and Multi-Spectral Imager (MSI) for cloud, aerosol, and radiation process studies; Biomass mission with a interferometric and polarimetric P-band SAR for biomass and glacier topography study; and FLEX mission with a FLORIS instrument for photosynthetic activity monitoring. Additionally, the ESA has chosen two potential Earth Explorer candidates missions [2], the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) with measure in the 15–100 micron range, and Sea-Surface Kinematics Multi-scale (SKIM) monitoring with a multi-beam radar altimeter with a wide swath. These two candidates considered will spend the next two years being studied thoroughly and only one will be implemented.

State of the art of the meteorological contributing missions of Copernicus are MetOp in Low Earth Orbit (LEO), and Meteosat Second Generation (MSG) in Geostationary orbit (GEO). For the incoming decade (2020 to 2030), these programs will have continuity because new missions will be launched such as Meteosat Third Generation (MTG) and MetOp Second Generation (SG).

For Sentinel expansion, the ESA has identified six possible candidates with phase A/B under preparation for the expansions to the Copernicus space component [3], such as Sentinel-7 Anthropogenic CO${}_2$ monitoring mission, Sentinel-8 High Spatio-Temporal Resolution Land Surface Temperature (LST) Monitoring Mission (companion to Sentinel-2 C/D), Sentinel-9 with two components: Polar Ice and Snow Topographic Mission, and Polar Weather payload on a Highly Elliptical Orbit, and Sentinel-10 with a Hyperspectral Imaging Mission. Other possible candidates for the expansion of Copernicus are Passive Microwave Imaging Mission, and L-Band SAR mission. In parallel, a recent study of the Copernicus Market [4] mentioned that the agriculture, ocean monitoring, oil, and gas are a potential market in terms of Copernicus impact and user benefits. The approach followed is to identify the user’s needs, identifying the gaps and potential areas for improvement in the Copernicus EO infrastructure, taking into account the future instruments and missions. This form could analyse if the plans of the extension of Copernicus support the emergent needs.

The European Commission (EC) has led a revolutionary programme aiming at securing and exploiting space infrastructure to meet future demands and societal needs. The H2020 Operational Network of Individual Observation Node (ONION) project identified the main needs of the space segment infrastructure of the Copernicus system and identified the key technology challenges to be faced in the future, taking into account the user requirements at the center of the design process. The ONION project analyzed the user needs and ranked the top 10 use cases [5]. Each use case is associated with a Copernicus service, and they are formed by a set of measurements required to meet the users’ needs. The measurements are the geophysical products derived from satellite observations. In addition, the measurement gaps and user requirements were identified and defined by the ONION project (

Table 1. The top ten use cases.

	Use Case [5]	Copernicus Services Related	2020–2030
			Copernicus Instrument/Mission [7]	Contributing Instrument/Mission [8]	Measurements with Gaps Detected [6]
1	Marine for Weather Forecast	Marine	SAR-C/Sentinel-1 SRAL/Sentinel-3 OLCI/Sentinel-3 Poseidon-4/Sentinel-6	PALSAR-3/ALOS-4 SAR-2000 S.G/CSG SAR/HRWS SAR-X/TSX-NG SAR-X/PAZ SWIM/CFOSAT ASCAT/MetOp SCA/MetOp-SG	Wind speed over sea surface (horizontal), Ocean surface currents, Dominant wave direction, Dominant wave period, Significant wave height, Atmospheric pressure over sea surface.
2	Sea Ice Monitoring: Extent, Thickness	Marine	SAR-C/Sentinel-1 SLTR, OLCI, SRAL /Sentinel-3	PALSAR-3/ALOS-4 SAR-2000 S.G/CSG SAR/HRWS SAR-X/TSX-NG SAR-X/PAZ SWIM/CFOSAT ASCAT/MetOp SCA/MetOp-SG MSI/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG	Sea surface temperature, Sea ice cover, Sea ice type, Sea ice thickness, Iceberg tracking, Sea ice drift, Sea ice extent, Wind speed over sea surface horizontal, Ocean surface currents, Dominant wave direction, Dominant wave period, Significant wave height.
3	Fishing Pressure, Stock Assessment	Marine	OLCI/Sentinel-3 SAR-C/Sentinel-1	SEVERI/MSG MSI/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG FCI/MTG-I IRS/MTG-S FLORIS/FLEX	Color dissolved organic matter, Ocean imagery and water leaving radiance, Ocean chlorophyll concentration, Monitoring system- vessels.
4	Land for Infrastructure Status Assessment	Security	SAR-C/Sentinel-1 MSI/Sentinel-2 OLCI/Sentinel-3	SAR-2000 S.G/CSG SAR-X/TSX-NG HRWS-SAR/HRWS SAR-X/PAZ DESIS/ISS DESIS HYC/PRISMA P-BAND SAR/BIOMASS HSI/EnMap FCI/MTG-I HiRAIS/Deimos-2 NAOMI/SPOT-7 REIS/RapiEye	None
5	Agriculture and Forestry: Hydric Stress	Land	SAR-C/Sentinel-1 MSI/Sentinel-2 SLTR, OLCI/Sentinel-3	SAR-2000 S.G/CSG SAR-X/TSX-NG HRWS-SAR/HRWS SAR-X/PAZ DESIS/ISS DESIS HYC/PRISMA P-BAND SAR/BIOMASS ASCAT/MetOp SCA/MetOp-SG MSI/EartCARE HSI/EnMap FCI/MTG-I HiRAIS/Deimos-2 NAOMI/SPOT-7 REIS/RapiEye SEVERI/MSG MSI/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG FCI/MTG-I IRS/MTG-S FLORIS/FLEX	Surface soil moisture, Crop grow and conditions, detection of water stress in crops, Estimation of crop evapotranspiration.
6	Land for Basic Mapping: Risk Assessment	Emergency Management	SAR-C/Sentinel-1 MSI/Sentinel-2 OLCI/Sentinel-3	SAR-2000 S.G/CSG SAR-X/TSX-NG HRWS-SAR/HRWS SAR-X/PAZ DESIS/ISS DESIS HYC/PRISMA P-BAND SAR/BIOMASS HSI/EnMap FCI/MTG-I HiRAIS/Deimos-2 NAOMI/SPOT-7 REIS/RapiEye	Surface soil moisture.
7	Sea Ice Melting Emissions Assessment	Marine	SAR-C/Sentinel-1 SLTR, OLCI, SRAL/Sentinel-3	PALSAR-3/ALOS-4 SAR-2000 S.G/CSG SAR/HRWS SAR-X/TSX-NG SAR-X/PAZ SWIM/CFOSAT ASCAT/MetOp SCA/MetOp-SG MSI/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG	Sea surface temperature, Sea ice cover, Sea ice type, Sea ice thickness.
8	Atmosphere for Weather Forecast	Atmosphere	SAR-C/Sentinel-1 Sentinel-4/MTG-S Sentinel-5/MetOp-SG TROPOMI/Sentinel-5p	ASCAT/MetOp SCA/MetOP-SG SEVERI/MSG MSI, CPR/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG FCI/MTG-I IRS/MTG-S	Wind speed over sea surface (horizontal), Wind vector over sea surface (horizontal), Atmospheric pressure over sea surface.
9	Climate for Ozone Layer and UV	Climate Change	SLTR, OLCI/Sentinel-3 Sentinel-4/MTG-S Sentinel-5/MetOp-SG TROPOMI/Sentinel-5p	SEVERI/MSG MSI, CPR/Earth-CARE GOME-2, IASI, AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG FCI/MTG-I IRS/MTG-S HYC/PRISMA UVAS/Ingenio	None
10	Natural Habitat and Protected Species Monitoring	Land	SAR-C/Sentinel-1 MSI/Sentinel-2 OLCI, SLTR/Sentinel-3 Sentinel-4/MTG-S Sentinel-5/MetOp-SG TROPOMI/Sentinel-5p	ASCAT/MetOp SCA/MetOP-SG SEVERI/MSG MSI, CPR/Earth-CARE IASI and AVHRR-3/MetOp METimage,IASI-NG/MetOp-SG FCI/MTG-I IRS/MTG-S HYC/PRISMA FLORIS/FLEX	Surface soil moisture.

) [5,6], taking into account if, in the coming decade, the Copernicus and contributing missions satisfy the user requirements. This work focuses on the identification of the potential sensor technologies and platforms to meet those needs detected. The capability of the different technologies is evaluated according to current trends in the design of small satellites. These technologies are presented in view of the novel developments in spacecraft and sensor miniaturization, reduced power consumption, measurement requirements, and data quality, in order to cover the user requirements [6], so as to obtain competitive and cost-effectiveness services.

The 20 measurements with gaps detected [6] in the top ten use cases are: (1) Ocean surface currents, (2) dominant wave direction, (3) significant wave height, (4) horizontal wind speed over the sea surface, (5) sea ice type, (6) iceberg tracking, (7) sea ice cover, (8) sea ice extent, (9) sea ice drift, (10) sea ice thickness, (11) atmospheric pressure over the sea surface, (12) sea surface temperature, (13) ocean chlorophyll concentration, (14) ocean imagery and water leaving radiance, (15) color dissolved organic matter, (16) detection of water stress in crops, (17) estimation of crop evapotranspiration, (18) surface soil moisture, (19) crop growth and condition, and (20) monitoring system vessels. Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric Stress use cases involved all the measurements with observations gaps detected over Copernicus space infrastructure in the period 2020–2030. The Marine for Weather Forecast, Sea Ice Monitoring, and Fishing Pressure use cases are ranked as the emerging observation needs. These use cases required measurements that are of crucial importance for a wide range of activities from maritime traffic, fishery, environment, food and medicine supply for populations at high latitudes, as well as for oil and gas operations. Another high priority use case with observation gaps (Table 1) is the Agriculture and Forestry: Hydric Stress. The key measurements to cover for this use case are important to study the hydrological cycles, agriculture production, climatology, and meteorology. With the objective to cover these 20 measurements with gaps, we designed a methodology that focuses on the critical technologies to complement Copernicus observation gaps.

The methodology applied to select the appropriate sensors and platforms is sketched in Figure 1. First, a survey of the commercial small platform capabilities is presented in terms of mass, payload power, communications, pointing knowledge, and control. Second, the state-of-the-art sensors in terms of mass, power consumption, swath, and data rate is presented. Each sensor or technology is then studied to cover the observation gaps. Based on the survey of the instrument capabilities and data quality, a summary of the existing, and emerging in EO sensors is given, including the scientific and technological limitations in terms of spatial resolution, accuracy, and swath. Within these bounds, the potential instruments are selected according to the available commercial small platforms. The reference instruments are evaluated based on the variables with gaps that can be measured using a scoring method. This scoring method assigns a high score to the sensors that present lower power consumption, lower mass, and high data quality (better accuracy, smaller spatial resolution, and/or wider coverage). Finally, the most relevant instrument technologies compatible with small platforms are identified to complement the existing Copernicus Services for the selected use cases.

2. Survey of Commercial Small Platforms

This section presents the results of a comprehensive survey of commercial Low Earth Orbit (LEO) small platforms for EO, in order to properly select the platforms for each technology. To do this, the capabilities and limitations of the small commercial buses are taken into account. A total of forty-two commercial platforms from eighteen different companies have been identified, and their information has been compiled from company websites and conferences proceedings (Appendix A).

These small platforms cover a wide range of payload mass and power. They are categorized into three groups nano-, micro-, and mini-satellites.

Table 2. Summary of survey of commercial small platforms capabilities.

Classification	Satellite Mass [kg]	Max. Payload Mass [kg]	Max. Payload Power (average) [W]	Max. Data Rate (Downlink)
Nano	<10	≤3 [17]	≤15 [11,18]	≤15 Mbps [19]
Micro	10–100	≤54 [20]	≤150 [21]	≤160 Mbps [22]
Mini	100–1000	≤600 [9]	≤1500 [10]	≤1.2 Gbps [13]

summarizes their typical parameters. These platforms support payload masses from 1 kg to 600 kg [9], payload powers (orbital, average) from 1 W to 1500 W [10], downlink up 15 Mbps (S-band) [11], 100 Mbps (X-band) [12], and 1.2 Gbps (K-band) [13]. In this context, the recent evolution of the capability of micro- and mini-class platforms, and the payload miniaturization have demonstrated being a true competitor of large spacecrafts for some applications.

Table 3. Summary of survey of commercial CubeSat platforms capabilities.

Classification	Approximate Size [cm]	Payload Mass [kg]	Payload Power [average/peak] [W]	Payload Data Rate [downlink]	References
3U	10 × 10 × 30	<3	≤15	≤15 Mbps	[17]
6U	10 × 20 × 30	<12	≤20	≤15 Mbps	[23]
27U	30 × 30 × 30	<50	≤90	≤100 Mbps	[20]

summarizes the capabilities of CubeSat EO platforms (3U, 6U, and 27U). Nanosatellites are now becoming popular thanks to the CubeSat standard. Typical CubeSat missions can be implemented in 1 to 3 years, with typical budgets from 200 K to 1 M $ USD, including launch.

On the other side, ESA has promoted the development of a generic Small Geostationary Platform [14] (SmallGEO or SGEO) industrialized by OHB [15]. This flexible and modular platform has a lifetime of up to 15 years, a payload mass of up to 400 kg, and a payload power of up to 4 kW [16]. This platform was originally proposed to help European industries in the commercial telecom satellite market. However, the Earth Observation domain can also benefit from the capability of this platform in terms of available power and payload mass. In this way, an analysis of the EO technologies that are appropriate for use in small platforms is conducted in the next section.

3. Survey of Earth Observation Sensors and Measurements Requirements to Cover the Future Gaps on Copernicus

EO satellites have revolutionized the study of the environment, and are contributing to a more rational use of the natural resources, and environmental protection. The applications of the data supplied by these systems are enormous: disaster monitoring, weather forecast, maritime safety, marine resources monitoring, forestry, vegetation state, water cycle, energy budget, pollution control, water quality, climate change, and security; using radars, microwave and optical/IR radiometers, optical imagers or scanners.

Table 4. Instrument categorization: potential instruments to complement the Copernicus system [6].

	PASSIVE		ACTIVE
MICROWAVE	Radiometer	Imager Sounder	Real Aperture Radar	Altimeter Scatterometer
	Signals of Opportunity (SoOp)	GNSS-R ${}^a$ Receiver of SoOP ${}^b$	Synthetic Aperture Radar	Altimeter Imager
	Receiver	Automatic Identification System (AIS)
OPTICAL	Radiometer	Multispectral Hyperspectral	Lidar
	Sounder

${}^a$ multi-static radar using satellite navigation signals of opportunity (SoOp). ${}^b$ e.g., Direct Broadcast Satellite (DBS) television at Ku-band or X-band.

presents the generic classification of the remote sensors. Instruments are classified in the following four categories: active or passive, either microwave or optical. Optical sensors measure the signals received around the visible part of the spectrum, from the Ultra-Violet (UV) to the Thermal Infrared (TIR). Microwave sensors use the signals in the microwave and millimetre-wave parts of the spectrum, typically from 1 GHz to 1 THz. Passive systems are based on the collection of the electromagnetic waves that are emitted/scattered by external sources, such as the Sun or other bodies. On the other hand, active systems such as radars and lidars, transmit an electromagnetic wave, either radio or laser, and measure the scattered/reflected signal from the Earth’s surface or atmosphere. Microwave sensors do not rely on the Sun as source of illumination. These particular characteristics are especially important in Polar Regions that have extended dark periods in winter. In addition, microwaves are mostly unaffected by the cloud cover, except in some specific bands. This feature makes microwave sensors more suitable than optical sensors in these regions.

This section presents a survey of the selected EO technologies. In order to identify the potential EO sensors to improve the Copernicus space infrastructure, EO technologies are analyzed in depth based on the measurements with identified gaps, and the technological limitations. A total of 77 instruments have been surveyed, and their parameters (mass, power consumption, spatial resolution, swath, frequency bands, aperture, and orbit altitude) have been compiled from the Observing Systems Capability Analysis and Review (OSCAR) Tool [24], the Earth Observation Portal Directory [25], and companies websites (Appendix B). The best instruments in terms of data quality and suitable for the small platform are identified for each technology.

3.1. Passive Microwave

3.1.1. Microwave Imagers (MWIm)

The main applications of Microwave Imagers (MWIm) are atmospheric (X, K, Ka, and milimiter waves bands), oceanographic (C, X, K, and Ka bands), vegetation and soil moisture monitoring (P, L, S, C and X bands). High frequency microwave radiometers are particularly well suited for small platforms because of the antenna size constraints. These types of instruments can measure: wind speed [26,27], sea ice thickness [28,29], and sea ice cover [30], among other variables.

Table A4. Survey of microwave imagers (MWI).

Instrument [Mission]	Frequencies Bands [GHz]	Spatial Resolution [km]	Antenna Size [m]	Swath Width [km]	Mass [kg]	Power [W]	Data Rate [kbps]	Orbit Altitude [km]
Soil Moisture Active and Passive (SMAP) [SMAP] [25,89]	1.41	40	6	1000	356	448	40,000	685
Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) [Soil Moisture and Ocean Salinity (SMOS)] [25,88]	1.41	<50	4 ${}^a$	1000	355	511	89	755
WindSat (Coriolis) [25]	6.8, 10.7, 18.7, 23.8, 37	39 × 71 to 8 × 13	1.83	1200	341	350	256	838
AMSR (ADEOS-II) [25]	6.93, 10.65, 18.7, 23.8, 36.5, 50.3, 52.8 and 89	3 × 6 to 40 × 70	2	1600	320	400	130	812
AMSR-2 (GCOM) [25]	6.93, 7.3, 10.65, 18.7, 23.8, 36.5 and 89	5 to 50 ${}^b$	2	1450	320	400	130	700
AMSR-E (Aqua) [112]	6.93, 7.3, 10.65, 18.7, 23.8, 36.5 and 89	3 × 5 to 35 × 62	2.4	1450	314	350	874	705
Aquarius (SAC-D) [25]	1.4 GHz	100	2.5	390	247	291	5	661
MWI (Metop-SG) [25]	18.7–183.31 (26 channels)	8 × 13 to 40 × 65	0.75	1700	220	250	160	817
MADRAS (Megha Tropiques) [25]	18.7, 23.8, 36.5, 89 and 157	40 × 60 to 6 × 9	0.65	1700	162	153	37	867
GMI (GPM) [25]	10.65, 18.7, 23.8, 36.5, 89, 166, 183.31	19 × 32 to 4.4 × 7.2	1.2	850	150	140	25	407
TMI (TRMM) [25]	10.65, 19.35, 21.3, 37, 85.5	37 × 63 to 5 × 7	0.61	790	65	50	8.8	402
SSM/I (DMSP) [84]	19.35, 23.235, 37, 85.5	45 × 68 to 11 × 16	0.61	1400	48.5	45	3.3	850

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements; Light gray: Micro-platform; Gray: Mini-Platform; ${}^a$ 3 arm size; ${}^b$ Resolution range for standard products.

presents the features of some microwave radiometers, in terms of frequency bands, spatial resolution, antenna size, swath, mass, power consumption, and data rate. Assuming only one payload per platform, the affordable platforms (nano, micro, mini, and large) for the instruments are identified according to the power and mass requirements. This information is valuable in order to choose the potential instruments that will complement the Copernicus Space segment, trying to make them compatible with the smallest possible platforms, while fulfilling the user requirements. The measurement gaps that can be covered with this technology are: horizontal wind speed over the sea surface (MWIm with channels around 7, 10, 19, 37 GHz or 19 and 37 GHz), sea ice monitoring (cover, type, drift, MWIm with channels around 7, 10, 19, 37, and 90 GHz), sea ice thickness (MWIm with channels around 1.4 GHz), soil moisture (MWI with channels around 1.4 GHz, or 7 GHz, or 11 GHz), and sea surface temperature (MWIm with channels around 7 and/or 10 GHz).

According to Table A4, two microwave imagers capable of measuring the variables with gaps have been identified. These are selected because they are suitable for small platforms and present good data quality, to cover the user requirements.

• A Tropical Rainfall Measuring Mission Microwave Imager (TMI) like instrument is capable of measuring wind speed (at 10.65, 19.35 and 37 GHz), sea ice cover (at 19.35, 37, and 85.5 GHz), and sea surface temperature (at 10.65 GHz). Modified versions of TMI for micro- or mini-platforms achieving a 10 km spatial resolution using an aperture size (inflatable antenna) of 3.4 m @ 10.65 GHz from 600 km height will suit LEO polar Sun-Synchronous Orbit (SSO, ∼14 orbits/day) reducing the revisit time to 3 h in the Polar Regions. The required number of satellites was optimized in [31].
• The available L-Band microwave sensors, such as Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) and Soil Moisture Active-Passive (SMAP) are suitable for mini-platforms. L-band microwave radiometers are capable of measuring the variables with the detected gaps, such as sea ice thickness and soil moisture. Sea ice thickness presents gaps in the revisit and latency times. The revisit time required is 24 h, and a latency time of 1 h. Surface soil moisture monitoring presents gaps in the accuracy 0.01 m${}^3$/m${}^3$ and the latency time 1 h.

3.1.2. Microwave Sounders (MWS)

In the last few years, intensive work has been conducted to develop missions to prove the feasibility of using microwave sounders on nano-platforms, such as MicroMas [32], and the Earth Observing Nanosatellite-Microwave (EON-MW) [33]. The measurement with gaps that can be analyzed with this technology is the atmospheric pressure over the sea surface.

Table A5. Survey of microwave sounders (MWS).

Instrument [mission]	Frequencies [GHz]	Spatial Resolution [km]	Antenna Size [m]	Swath Width [km]	Mass [kg]	Power (W)	Data Rate [kbps]	Orbit Altitude [km]
ATMS (SNPP, JPSS) [25]	23.8–183 (22 channels)	16, 32 and 75	-	2600	75	130	30	824
AMSU-A (NOAA-15/16/17/18/19, Metop A/B/C and Aqua) [25]	23 to 89 (15 Channels)	48	0.17 and 0.08 ${}^a$	2100	104	99	3.4	817
Tri-band Microwave Radiometer (MiRaTA) [25,32]	52–58 175–191 203.8–206.8 (10 channels)	-	0.1	-	<4.5	6	10	400
Miniature microwave sounder (EON-MW) [33]	23/31, 50–60/88, 166/183 (22 channels)	44, 23, 7.5	0.11	1000	5	23	50	505

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform; Gray: Mini-Platform; ${}^a$ This instrument has two antennas with different apertures.

presents a survey of the representative current and future missions with microwave sounders capable of measuring the atmospheric pressure over the sea surface. The gaps for this variable are the revisit and the latency times. To fill these gaps, a constellation of microwave sounders based on CubeSats missions could observe fast weather phenomena requiring high revisit time (3 h or less). A good example of CubeSat mission is EON-MW. The payload is a dual-reflector radiometer with a mass of 4 kg, an antenna size of 11 cm, and spatial resolution of 30 km on altitude of 600 km at 54 GHz.

3.1.3. Signals of Opportunity (SoOp): GNSS-R, and Receiver of SoOp

The utmost sensors used for oceanography (SARs and radar altimeters) have features that make them difficult to board on nano-satellites, most notably the power requirements, and the antenna size. An attractive option to explore the sea surface topography is the use of reflected Global Navigation Satellite Systems (GNSS) signals [34,35]. GNSS reflectometry is a favourable technique to perform some ocean measurements with small satellites [36]. The advantage of this technique is the capability to operate in all-weather conditions with a spatial resolution of ∼25 km. In the last two decades, a big effort has been made to develop models that prove the feasibility of using GNSS signals, proving to be successful for sea surface, altimetry measurements [37,38], wind speed [39,40], soil moisture [41,42,43,44,45], ice thickness [46], ice cover [47], and others. A few characteristics of GNSS-R missions have been identified and summarized in

Table A6. Survey of GNSS-R instruments.

Available Instruments	Frequencies & Signals	Spatial Resolution [km]	Swath [km]	Mass [Kg]	Power [W]	Data Rate [kbps]	Orbit Altitude [km]
SGR-ReSI (TechDemoSat-1 (TDS-1), CYGNSS) [57]	L1 C/A Code (Options: Galileo E1, GPS L2C, Glonass L1, GPS L5, Galileo E5)	20–50	740	1.4 ${}^a$	<12	200	680
GEROS-ISS (GEROS-ISS) [80]	L1 C/A Code (Options: Galileo E1, GPS L2C, Glonass L1, GPS L5, Galileo E5, and QZSS)	30	∼2000	376	395	1200	375–435
FMMPL-2 (FSSCAT) [49]	L1 C/A Code (Options: Galileo E1)	0.3	∼350	1.5	>8.0	40	500–550

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform; Gray: Mini-Platform; ${}^a$ Antenna mass doesn’t include.

.

The current and planned missions using GNSS-R technology are presented in Table A6, such as TechDemosat-1 (TDS-1) [48], the Cyclone Global Navigation Satellite System (CYGNSS) [36], and FSSCAT [49,50].

TDS-1 was launched in June 2014 and it includes a GNSS-R payload with a mass of around 1.5 kg and approximately 10 W power consumption. It demonstrated the capabilities of GNSS-R for low power, low cost, and low mass. This payload measures complete delay-Doppler Maps (DDM) providing scientific-quality data [51]. The CYGNSS mission takes advantage of a constellation of eight microsatellites (weighting 17.6 kg) that provide nearly gap-free Earth coverage over Equatorial regions, with an average revisit time of seven hours and a median revisit time of three hours. CYGNSS was launched on December 2016. FFSCAT is a tandem mission of two 6U Cubesats (${}^3$Cat-5/A and ${}^3$Cat-5/B) featuring a hybrid microwave radiometer/GNSS- Reflectometer and a hyperspectral imager. FSSCAT will be the first nanosatellite mission to complement the Copernicus program [49]. Its main focus is over Polar Regions, and it will be launched in 2019.

The European Space Agency (ESA) conducted the studies of a space-borne demonstrator called Passive Reflectometry and Interferometry System In-Orbit Demonstrator (PARIS IoD) [52,53,54]. PARIS IoD was later reincarnated into the GEROS experiment on board the International Space Station [55], but it was never implemented.

Novel techniques using signals of opportunity, such as from Direct Broadcast Satellite (DBS) television at Ku- or X-bands, can be used to measure precipitation and winds over the sea surface [56], and these signals are sensitive to detect fluctuations of the sea surface roughness.

In this regard, the SGR-ReSI [57] payload onboard TDS-1 is selected as a possible candidate to cover the measurements with gaps such as wind speed over the sea surface (horizontal), sea ice cover, sea ice thickness, and soil moisture [6].

3.1.4. Receiver: Automatic Identification System (AIS)

Although not an EO technique, Automatic identification systems (AIS) could also be a potential technology for emergency and management for the Copernicus services. AIS is an automatic tracking system used by ships and vessel traffic services. The AIS is a standardized receiver using two channels in the maritime VHF band. It has a positioning system with electronic navigation sensors such as a gyrocompass or rate of turn indicator. The main advantages of this system are the accuraccy of the position, course, and speed information. Additionally, the International Maritime Organization (IMO) has normative guidelines to put AIS on board for all passenger ships larger than 300 GT. Additionally, the latency can be reduced thanks to an update rate of ∼3 min. In addition, it is suitable for nano-satellites [58] (low size, low power, low weight, and these can be translated into low system cost) (

Table A7. Survey of Automatic Identification System (AIS) missions.

Missions	Satellite Mass [kg]	Size	Power Consumption [W]	Launch Date	Payload
Triton-2/E-SAIL [97]	100	60 × 60 × 70 cm	100	2018	AIS
Norsat-2/SAT-AIS [97]	1.5	51 × 140 × =168 mm	5	2016	AIS
AISSat [25]	14	1 U	15	2013	AIS
${}^3$CAT-4 [113]	9	6U	2	-	AIS + VIS/NIR camera
Canx-6 [25]	6.5	2U	5.6	2008	AIS
AISSat 1 [25]	6	-	0.97	2010	AIS
AISSat 2 [25]	6	-	0.97	2014	AIS
ZACube-2 [25]	4	3U	-	2017	AIS + imager
AAUSAT-4 [25]	0.88	1U	1.15	2016	AIS

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform.

).

3.2. Passive Optical

This type of technology has shown its feasibility for small missions [59,60]. For example, for an optical instrument in the visible part of the spectrum, with a ground resolution better than 10 m, and an aperture of 10 cm (CubeSat size), the altitude of the satellite should be less than 500 km.

The data provided by passive optical instruments, from the ultraviolet to the far-infrared wavelengths can be used for weather forecast, vegetation, atmosphere, ocean and land studies. The main limitation of optical sensors is that data cannot be acquired in night-time (visible and near infrared parts of the spectrum) or cloudy conditions, and cloudy weather is very frequent in Polar Regions.

In this manuscript, the classification of optical sensors as radiometer imager and atmospheric sounders, and its subclassification between multispectral and hyperspectral is studied. Radiometer imagers measure the intensity of electromagnetic radiation in the visible or infrared bands, and sounders measure the vertical distribution of atmospheric parameters such as pressure, temperature, and humidity. Multispectral instrument refers to a maximum number of tens of bands, and hyperspectral radiometers consist of hundreds of narrow and continuously distributed bands (10–20 nm).

3.2.1. Radiometer: Multispectral and Hyperspectral

Table A8. Survey of optical radiometer instruments: multispectral and hyperspectral.

Instrument (Mission)	Classification	Wavelength [$\mathsf{\mu }$m]	Aperture Size [m]	Spatial Resolution [km]	Swath Width [km]	Mass [kg]	Power [W]	Data Rate [Mbps]	Orbit Altitude [km]
MetImage ${}^a$ (MetOp-SG) [25]	Radiometer/ Multispectral resolution	[0.443–13.345] 20 spectral channels	0.17	0.25 to 0.5 or 1	2670	296	465	18	817
VIIRS ${}^a$ (NOAA-20) [25]	Radiometer/ Multispectral resolution	[0.4–12.5] 22 spectral channels	0.184	0.375 to 0.75	3000	275	240	5.9	825
Modis ${}^a$ (Terra/Aqua) [25]	Radiometer/ Multispectral resolution	[0.4–14] 36 spectral channels	0.178	0.25–1	2330	229	162.5	6.1	705
SLSTR ${}^b$ (Sentinel-3) [24,25]	Radiometer/ Multispectral resolution	[0.545–12.5] 11 spectral channels	-	0.5–1.0	1400	140	100	64	814.5
OLCI ${}^c$ (Sentinel-3) [25]	Radiometer/ Multispectral resolution	[0.55–10.85] 21 spectral channels	-	0.3	1270	150	124	5	814.5
AATSR ${}^b$ (Envisat) [25]	Radiometer/ Multispectral resolution	[0.4–15] 7 spectral channels	-	1	500	101	100	0.625	774
VIRS ${}^b$ (TRMM) [25]	Radiometer/ Multispectral resolution	[0.58–12.05]	-	2	833	34.5	40	0.05	402
AVHRR/3 ${}^b$ (Metop/ NOAA) [25,61]	Radiometer/ Multispectral resolution	[0.58–12.5] 6 spectral channels	0.21 × 0.295	1.1	2900	33	27	0.621	850
Naomi ${}^b$ (SPOT-6/7) [25]	Radiometer/ Multispectral resolution	[0.45–0.89] 5 spectral channels	-	0.08	25	18.5	-	60	695
CHRIS ${}^b$ (PROBA-1) [25]	Imager Spectrometer/ Hyperspectral resolution	[0.4–1.05] 63 spectral channels	0.12	0.036	14	14	8	1	615
COMIS ${}^c$ (STSat-3) [25]	Imager Radiometer/ Hyperspectral resolution	[0.4–1.05] 64 spectral channels	-	30 or 60	15 or 30	4.3	5	-	700
HyperScout/ FSSCAT, (3CAT 5/B) [49]	Imager/ Hyperspectral resolution	[0.4–1.0] 45 spectral bands	0.1	0.04	164	1.1	11	-	300
CIRC ${}^c$ (ALOS-2) [25]	Infrared radiometer	[8–12] Single TIR channel	0.08	200	128	3	<20	-	640

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform; gray: mini-platform; ${}^a$ Instrument affordable for a wide range of geophysical variables, from cloud classification and properties, to aerosol main properties, land surface variables and sea surface variables. ${}^b$ Instrument affordable for cloud analysis, aerosol inference, land surface variables and sea surface variables. ${}^c$ Instrument affordable for Observation of land surface (e.g., vegetation), marine biology (e.g., ocean color), and cloud/aerosol.

presents the features of the available multispectral and hyperspectral radiometers instruments, in terms of wavelength, spatial resolution, aperture size, swath, mass, power consumption, and data rate. The variables of interest that can be measured with optical sensors for the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress use cases are the Sea Surface Temperature (SST), atmospheric pressure over the sea surface, ocean chlorophyll concentration, ocean imagery and weather leaving radiance, Color Dissolved Organic Matter (CDOM), detection of water in crops, estimation of crop evapotranspiration and the sea ice cover.

A good example of multispectral radiometer on micro-platform is AVHRR/3 [61] and also has good performance, and it could support the measurements with detected gaps, such as SST, ocean chlorophyll concentration, ocean imagery and weather leaving radiance, CDOM, detection of water in crops, estimation of crop evapotranspiration, sea ice cover, and atmospheric pressure over the sea surface (it can be inferred through measurements in the infrared band).

3.2.2. Sounder: Multispectral and Hyperspectral

A good example of hyperspectral infrared sounder capable of measuring atmospheric pressure over the sea surface on CubeSat is EON-IR [62]. This instrument is under development with spatial resolution comparable to legacy sounders such as Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infra-Red Sounder (AIRS), and Cross-track Infrared Sounder (CrIS).

Table A9. Survey of optical sounders instruments: multispectral and hyperspectral.

Instrument (Mission)	Classification	Wavelength [$\mathsf{\mu }$m]	Aperture Size [m]	Spatial Resolution [km]	Swath Width [km]	Mass [kg]	Power [W]	Data Rate [Mbps]	Orbit Altitude [km]
IASI ${}^b$ (MetOp) [25]	Fourier Transform spectrometer b Radiometer/ Hyperspectral resolution	[3.62–15.5] 8461 spectral samples	1.1	25, 1–30	2052	236	210	1.5	827
AIRS ${}^a$ (Aqua) [25]	Infrared sounder/ Hyperspectral resolution	[0.4–15.4] spectral channel >2300	0.219	13.5, 1	1650	177	220	1.27	705
CrIS ${}^a$ (JPSS) [25]	Infrared Sounder/ Hyperspectral resolution	[3.92–15.38] 1345 spectral channels	0.8	14	2200	152	124	1.5	824
HIRS/4 ${}^a$ (MetOp, NOAA) [25]	Infrared sounder/ Multispectral resolution	[0.69–14.95] 20 spectral channels	0.15	10	2160	35	24	0.003	850
EON-IR ${}^a$ CIRAS [25,62]	Infrared Sounder/ Hyperspectral resolution	[4.08–5.13] 625 channels	0.15	3, 13.5	2200	2.5	15	2	450–600

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform; gray: mini-platform; ${}^a$ Instrument affordable for cloud analysis, aerosol inference, land surface variables and sea surface variables.

presents the details of the available multispectral and hyperspectral sounders instruments, in terms of spatial resolution, aperture size, swath, mass, power consumption, and data rate. For each optical sensor, it classifies (nano-, micro-, mini-, and large-satellite) according to the payload power and mass that can support the available commercial platforms summarized in Table 2.

3.3. Active Microwave

Several missions have been launched with active microwave instruments that can be grouped into three main families: Scatterometers, Synthetic Aperture Radars (SAR), and Radar Altimeters (RA). This section describes the variables of interest that can be measured with satellite-based active microwave sensors: wind speed, and direction over the sea surface using radar scatterometers, SAR and SAR altimeters; sea level, significant wave height, wave and wind speed using RA; and dominant wave direction, significant wave height and sea ice cover by SAR. Then, each variable is presented with the available active microwave technology, and the new trends of these sensors in small satellites.

3.3.1. Real Aperture Radar Altimeter

Radar altimeters measure the distance of the Earth’s surface underneath the spacecraft by measuring the time between transmitting the signal and receiving the echo. Microwave radar altimeters have been used for a wide range of applications that can be grouped as: (a) geodesy and geophysics, study the Earth’s shape and size, on the ground as well as on the sea surface [63]; (b) ocean applications (ocean surface currents, wind speed, significant wave height); (c) ice sheets and sea ice (sea ice thickness, and glacier topography) [64]; (d) climate (ocean topography and the heat exchange with the atmosphere); and (e) hydrology.

Nowadays, altimeter constellations on small platforms are deemed important, since they bring improved temporal resolution, and some ocean phenomena can only be perceived if subject to an almost continuous observation. At the same time, a shorter revisit time represents an increase in the spatial coverage and a finer spatial sampling grid. Equally, SSO should be avoided because of the errors associated with solar tidal effects.

Examples of recent altimetry missions are presented in

Table A10. Survey of Radar Altimeter instruments.

Instrument/Mission	Frequency [GHz]	Antenna Size [m]	Spatial Resolution [km]	Mass [kg]	Power [W]	Data Rate [kbps]	Orbit Altitude [km]
Altika/SARAL [25]	23.8, 36.5, 35.75	1	10	40	85	43	800
SWIM/CFOSAT [25]	13.58	0.9	-	-	120	50	519
Altimeter/SWOT [24]	5.3, 13.58	1.2	25	70	78	22.5	891
Karin*/SWOT [24]	35.75	5 × 0.25	0.05 ${}^a$ 1 ${}^b$	300	1100	320,000	891
RA-2/Envisat [24,25]	3.2, 13.6	1.5	20	110	161	100	774
SSALT/TOPEX- Poseidon [24,25]	13.65	1.5	25	24	49	-	1336

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: light gray: micro-platform; gray: mini-platform. * Interferometry; ${}^a$ Spatial resolution over land; ${}^b$ Spatial resolution over ocean.

. Typical requirements are: 100 W average power consumption, 1.2 m antenna diameter, 61 kg payload mass. The implementation on nano- platforms for radar altimeters may partially degrade the quality of the measurements. Additionally, nadir looking altimeters do not provide a wide swath. In this way, constellations of small satellites embarking a compact nadir altimeter [65] could improve the temporal/spatial sampling and therefore closing the gap with current planned missions.

3.3.2. Real Aperture Radar Scatterometers

Current and planned scatterometers missions have been identified and are summarized in

Table A11. Survey of scatterometer instruments.

Instrument (Mission)	Frequencies [GHz]	Spatial Resolution [km]	Swath Width [km]	Mass [kg]	Power [W]	Data Rate [kbps]	Orbit Altitude [km]
ASCAT (Metop) [25]	5.255	50, 25 and 12.5	550	260	215	42	817
RapidScat (ISS RapidScat) [24]	13.4	50, 25 and 12.5	900	200	220	40	407
SCA (Metop-SG-B1/B2/B3) [25]	5.3	17–25	550	600	540	5000	817
SCAT (CFOSAT) [25,82]	13.256	50, 10	>1000	<70	<200	220	500
WindRAD (FY-3E/3H) [25]	5.3 and 13.265	20 (C-band), and 10 (Ku-band)	1200	-	265	-	836

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: gray: mini-platform; black: large-platform.

. Earth Observation missions based on scatterometers typically operate at C-, and Ku-bands, and present spatial resolutions from 10 to 50 km. Current and future contributing missions to the Copernicus system with radar scatterometer are: ASCAT and SCA, ASCAT/Metop-A/B/C (2007 to 2021), with global coverage every 1.5 days and 12.5 km spatial resolution for basic sampling, SCA/Metop-SG-B1/B2/B3 (from 2022 to 2030) with near global coverage every 1.5 days, from 15 to 20 km of spatial resolution with sampling at 6.25 km intervals.

The main variables derived from radar scatterometer data are wind speed and vector over sea surface [66], but scatterometers are also capable to obtain surface soil moisture indices [67], leaf area index [68], snow water equivalent, snow cover [69], and sea ice extent measurements [70] Table A11 shows the characteristics of the radar scatterometer. The power consumption of these sensors is in the range of 210–540 W, and mass is in the range from 260 to 600 kg. According to the requirements of power consumption, size and mass, this payload can be carried over mini- or large-satellites.

3.3.3. Synthetic Aperture Radar (SAR) Altimeter

SAR altimeter differs from real aperture radar altimeter (conventional) in that it exploits coherent processing of groups of transmitted pulses, while conventional altimeters is exploited to make the most efficient use of the power reflected from the surface. The SAR altimeter offers many potential improvements over conventional altimetry for measurements, since it increases the resolution and offers multilook processing.

Currently, three mini-satellites are dedicated to altimetry with SAR processing, such as SARAL, Sentinel-3A, and Sentinel-3B. The planned missions are Sentinel 6 (Jason-CS).

Table A12. Survey of Radar Altimeter instruments with SAR processing.

Instrument/Mission	Frequency [GHz]	Antenna Size [m]	Spatial Resolution [km]	Mass [kg]	Power [W]	Data Rate [kbps]	Orbit Altitude [km]
SIRAL/Cryosat-2 [24,25]	13.56	1.2	15 0.25 ${}^a$	70	149	24,000	717
SRAL/Sentinel-3 [24,25]	5.3, 13.58	1.2	20 0.3 ${}^a$	60	90	12,000	810
Poseidon-4/ Sentinel-6 [24]	5.3, 13.58	-	20 0.3 ${}^a$	60	90	12,000	1336

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: light gray: micro-platform; gray: mini-platform. ${}^a$ Along track resolution (SAR mode).

summarizes the main characteristics of radar altimeters with SAR processing. Typical requirements are similar to the conventional altimeters for mini-platform: 100 W average power consumption, 1.2 m antenna diameter, 63 kg payload mass.

The geophysical variables of interest to analyze with SAR altimeter are ocean surface currents, significant wave height, dominant wave direction, sea ice cover, sea ice type, sea ice thickness, and horizontal wind speed over the sea surface.

3.3.4. Synthetic Aperture Radar (SAR) Imager

Spaceborne SAR imager sensors have been widely used for ocean monitoring (e.g., sea-ice cover, oil spills monitoring, sea-ice type, wave direction, dominant wave period, sea level, etc.), and land applications (e.g., soil moisture indices, vegetation monitoring, classification, fire fractional cover, fraction of vegetation over land, landslides and motion risk assessment, permafrost, and others) to support the environment management, with resolutions comparable to those of optical systems. The manufacturing and implementation related to a small SAR satellite mission have opened a market for a new technology which has recently been developed: the constellations of small SAR satellites, being the principle of Fractionated and Federated Satellites (FSS) [71], and/or bistatic SARs as companion satellites (e.g., SAOCOM [72]).

The use of SARs imager in small satellites poses some major challenges, such as the antenna dimensions and power requirements of the system. Another challenge is how to generate the power required by this sensor, reducing the transmitted power, resulting in a narrow swath and therefore increasing the revisit time. In this line, SARs are now feasible in small platforms—for example, NovaSAR-S [73] and ICEYE’s Synthetic Aperture Radar [74]. NovaSAR-S is a novel platform for small synthetic aperture Radar (S-band) development by Surrey Satellite Technology Ltd. (Guildford, United Kingdom), with a mass of 500 kg and peak power of 1.8 kW. The antenna is a microstrip patch phased array with size of 3 × 1 m. ICEYE’s Synthetic Aperture Radar is a microsatellite developed by ICEYE, with a satellite mass of 100 kg, and phase array antenna at X-band. According to the frequency band of the SAR, beyond 2028, there will be no X-band SAR mission in orbit, but there will be L- and C-band SARs mission (Figure 2). On this subject, the frequency band selected for SAR instrument is X-band, in order to obtain a smaller instrument and cover the frequency gap.

The geophysical variables of interest to analyze with SAR imager are iceberg tracking, sea ice cover, sea ice type, sea ice thickness, sea ice drift, sea ice extent, wind speed, ocean surface currents, dominant wave direction, dominant wave period, wind speed, and significant wave height. Nevertheless, single, large SAR satellites are not compatible with the requirements of 3 h of revisit time. Constellations of small SAR Satellites are under development or implementation stages [74]. In contrast, large SAR Satellites have been in orbit for years. Small SAR satellites can replace large SAR, for some specific applications requiring medium resolution imagery and smaller areas covered (due to power limitations). If the frequency band is higher (X-band), the spatial resolution and swath wide can be adjusted, therefore reducing the size and mass of the system.

Table A13. Survey of SAR imager instruments.

Instrument/ Mission	Frequency [GHz]	Spatial Resolution [m] @ Swath [km]	Mass [kg]	Power [W]	Data Rate [Mbps]	Orbit Altitude [km]
L-band SAR/SAOCOM-2 [24]	1.275	10–100 @ 30–320	1500	-	300	620
X-Band SAR/TSX-NG [24]	9.65	1–16 @ 10–100	1230	2400	680	515
SAR/RISAT-1/1A/2 [24]	5.35	1–50 @ 10–220	950	3100	1478	546
C-Band SAR/Sentinel-1 [24]	5.405	9–50 @ 80–400	880	4400	600	693
SAR (CSA)/RADARSAT [24]	5.405	16–100 @ 20–500	705	1650	105	798
SAR RCM/RCM [24]	5.4	3–100 @ 20–500	600	1270	-	592
COSI/KOMPSAT-5 [24]	9.66	1–20 @ 5–100	520	600	310	550
Severjanin-M/Meteor-M N2 [25,83]	9.623	400–1000 @ 600	150	1000	10	830

The background color in the table indicates the type of platform suitable for the instrument according to the power and mass requirements: Gray: mini-platform; black: large-platform.

presents a survey of the representative SAR image missions and classifies each instrument into mini or large according to capabilities of commercial platforms surveyed in the previous chapter.

3.4. Active Optical

Lidar

Active Optical Instruments or Lidars use pulsed laser emissions to measure atmospheric profiles and Earth surface applications such as vegetation height. Due to the short wavelengths, the laser pulse propagation through the atmosphere is scattered and attenuated by air molecules and aerosols. On the Earth’s surface, the vegetation and canopy also cause scattering. A small portion of the scattered light is sent back to the instrument which collects, and detects it. Subsequently, the electric signal is digitized through a Lidar signal numerical processing. Over the ocean, the variables that can be measured with Lidars are sea ice thickness, sea level and ocean dynamic topography.

Lidars can be divided into two broad categories: (i) atmospheric profilers producing also the total column content for atmospheric composition, i.e., particles layers and key trace gases, and (ii) altimeters with decimeter to meter accuracy for topography retrieval and canopy vertical distribution. The objectives of relevant Lidars are:

• Surface topography, ice sheet [75], and canopy [76] (e.g., ICESat-1).
• Climate and Radiation Budget by profiling clouds and aerosols optical and microphysical properties (e.g., NASA CALIPSO since 2006 [77], and ESA/JAXA EarthCARE [78], to be launched in 2021).
• Atmospheric dynamics or horizontal winds, (e.g., ESA Atmospheric Dynamic Mission ADM-Aeolus [79] was launched on 22 August 2018). Lidar instruments present the following main characteristics:
• Operating wavelengths in the UV, VIS, NIR, and SWIR; possible dual-wavelength, polarimetry, and two receivers (for Mie and Rayleigh scattering).
• Spatial resolution in the range of 100 m to a few tens of centimeters for LIDAR altimeters.
• Non-scanning, either nadir-viewing or oblique.

Doppler LIDARs generally operate in the UV to track aerosol and air molecules and it are used for track aerosol and air molecules. Backscatter LIDARs are typically operated at one or two wavelengths (UV or VIS + NIR), often with amount of polarizations cross-talk into a succession of atmospheric backscatter measurements (rotatable half-wave plate) to discriminate between spherical and non spherical particles in the atmosphere, the nadir view brings the capability to measure aerosol profiles, cloud top height and atmospheric discontinuities, and the multi-beam to perform a large swath. Lidars altimeter operated at two wavelengths (VIS + NIR) can measure with very high vertical resolution and horizontal resolution (for sea-ice elevation, and ice boundaries). Differential absorption LIDARs (DIAL) operate at one wavelength centered on the absorption peak of one trace gas (e.g., O${}_3$, H${}_2$O and CO${}_2$). The main limitation of this technology is the narrow swath. The variable with a gap that can be analyzed with Lidar is the sea ice thickness.

Table 5. Mapping of the potential technologies to cover measurements with gaps.

Technology Type			Measurements
Microwave	Passive	Radiometer Imager (X-, K-, Ka-, W-bands)	Wind speed over sea surface (horizontal) ${}^b$ Sea ice cover ${}^b$ Sea ice type ${}^a$ Sea ice drift ${}^a$ Sea surface temperature ${}^a$
		Radiometer Imager (L-band)	Soil moisture at the surface ${}^c$ Sea ice cover ${}^b$ Sea ice thickness ${}^a$ Crop growth & condition
		Radiometer Sounder (50–60 GHz)	Atmospheric pressure (over sea surface) ${}^c$
		Signals Oportunity: GNSS-R	Soil moisture ${}^b$ Sea ice thickness ${}^a$ Dominant wave direction ${}^b$ Wind speed over the sea surface (horizontal) ${}^a$ Significant wave height ${}^b$ Sea ice cover ${}^b$ Ocean surface currents ${}^b$
		Signals Opportunity: Receiver of SoOp (X, Ku-band)	Wind speed over sea surface ${}^a$
		Receiver: Automatic Identification System (AIS)	Monitoring system: vessels ${}^c$
	Active	Real Aperture Radar: Altimeter	Ocean surface currents ${}^c$ Significant wave height ${}^b$ Dominant wave direction ${}^b$ Sea ice thickness ${}^a$ Wind speed over sea surface (horizontal) ${}^a$
		Real Aperture Radar: Scatterometer	Wind speed over sea surface (horizontal) ${}^c$ Sea ice extent ${}^a$ Sea ice cover ${}^a$
		Synthetic Aperture Radar (SAR): Altimeter	Ocean surface currents ${}^c$ Significant wave height ${}^b$ Dominant wave direction ${}^b$ Sea ice type ${}^b$ Sea ice cover ${}^b$ Sea ice thickness ${}^a$ Wind speed over sea surface (horizontal) ${}^a$
		Synthetic Aperture Radar (SAR): Imager	Ocean surface currents ${}^c$ Iceberg tracking ${}^c$ Sea ice drift ${}^c$ Sea ice extent ${}^c$ Sea ice type ${}^c$ Sea ice cover ${}^c$ Dominant wave direction ${}^b$ Dominant wave period ${}^b$ Significant wave height ${}^b$ Sea ice thickness ${}^a$ Wind speed over sea surface ${}^a$ Ocean imagery and water leaving radiance
Optical	Passive	Multispectral radiometer (VIS/NIR/TIR)	Ocean chlorophyll concentration ${}^c$ ($\lambda$: 442.5, 490, 510, 560 nm) Ocean imagery and water leaving radiance ${}^c$ ($\lambda$: 485, 560, 660, 2100 nm) Color Dissolved Organic Matter (CDOM) ${}^c$ ($\lambda$: 442.5, 490, 510, 560, 665 nm) Sea surface temperature ${}^c$ ($\lambda$: 3.7, 4.05, 8.55, 11, 12 $\mathsf{\mu }$m) Sea ice cover ${}^a$ ($\lambda$: 640, 1610 nm) Detection of water stress in crops ${}^c$ Estimation of crop evapotranspiration ${}^c$
		Hyperspectral radiometer (VIS/NIR)	CDOM ${}^c$ Sea ice cover ${}^b$
		Sounder (IR)	Atmospheric pressure over sea surface ${}^c$ Sea surface temperature ${}^c$
	Active	Lidar	Sea ice thickness ${}^b$

The data relevance of the instrument depends on its ability and limitations to obtain the measurements: ${}^a$ Marginal relevance; ${}^b$ medium relevance; ${}^c$ high relevance.

summarizes all technologies discussed in this section: radiometer imager, radiometer sounder, GNSS-R, AIS, scatterometers, altimeters, altimeter with SAR processing, SARs imager, Passive optical and Lidars. The measurements with gaps that can be measured for each technology are identified. The studied technologies are feasible on small platforms taking into account the survey of the commercial platform addressed in the previous section. Now, the best technology option needs to be analyzed, based on the future observations required by the Copernicus space infrastructure.

4. Potential Instrument, Suitable Platforms, and Technological Limitations

After the survey of the suitable EO technologies in terms of the spatial resolution, swath, mass and power consumption, in this section, the suitable small commercial platforms and technological limitations of the potential sensors are identified.

Table 6. Mapping of potential passive sensors and platforms to meet the user requirements.

Technology Type	Measurements	Instrument Limitations	Instruments Identified
			TMI [25]	SSM/I [84]
			Available commercial platform (Non-exclusive)
Microwave Radiometer Imager (X-, K-, Ka-, W-bands) or (K-, Ka-, W-bands)	Wind speed over sea surface Sea ice cover Sea ice type Sea ice drift Sea surface temperature (at X-band)	Coarse spatial resolution and accuracy	NAUTILUS (NEMO-150) [85] SSTL-150 ESPA [86] BCP-100 [87] TET-XL [13]	SN-50 [21] Altair [20]
Microwave Radiometer Imager (L-band)	Surface soil moisture Sea ice cover Crop growth & condition Sea ice thickness	Coarse spatial resolution	MIRAS [25,88]	SMAP [25,89]	Aquarius [25]
			Available commercial platform (Non-exclusive)
	Sea ice thickness	Accuracy	ELiTeBUS 1000 [10] LEOStart-2 BUS [90]
			ATMS [25]	Miniature microwave sounder EON-MW [33]
			Available commercial platform (Non-exclusive)
Microwave Radiometer sounder (50-60 GHz)	Atmospheric pressure (over sea surface)	Coarse spatial resolution	SSTL-300/-600 [92,93] SN-200 [94] Eagle [90] TET-XL [13]	NEMO / DEFIANT [85] SSTL-12/-X50/-100 [22,91,92] SMALL SAT 27U [12] SN-50 [21] Altair [20] LEOS-30 [95] BCP-50 [96]
	Surface soil moisture Ocean surface currents Sea ice thickness Significant wave height Wind speed over sea surface	Accuracy	SGR-ReSI [57]	GEROS-ISS [80]
Signals of Opportunity (SoOp): GNSS-R	Dominant wave direction Surface soil moisture	Coarse spatial resolution	Available commercial platform (Non-exclusive)
	Sea ice cover	No specific limitation	Endeavour-3U [18] MAI-3000 [17]	ELiTeBUS 1000 [10] LEOStart-2 BUS [90]
			SD AIS Receiver [58]	NAIS [97]
			Available commercial platform (Non-exclusive)
Receiver: AIS	Monitoring system vessels	No specify limitation	GOMX 2U/3U [98] THUNDER (3U), GRYPHON (GNB) [85] Endeavour-3U [18] MAI-3000 [17] SMALL SAT 6U [12]	GOMX 3U [98] SMALL SAT 6U [12] MAI-3000 [17] Endeavour-3U [18]
Multispectral radiometer (VIS/MWIR/TIR)	Ocean chlorophyll concentration Ocean imagery and water leavin radiance CDOM Sea surface temperature Sea ice cover	Cloud sensitivity Day light only	AVHRR/3 [25]	VIRS [25]
			Available commercial platform (Non-exclusive)
	Detection of water stress in crops Estimation of crop evapotranspiration	Coarse spatial resolution Cloud sensitivity Day light only	SSTL-12 [22] SSTL-X50 [91] SN-50 [21] Altair [20]	SN-50 [21] Altair [20]
			CHRIS [25]	COMIS [25]
			Available commercial platform (Non-exclusive)
Hyperspectral radiometer (VIS/NIR)	Sea ice cover CDOM	Cloud sensitivity Day light only	LEOS-50/-100 [95] Small sat 12 U and 27U [12] SSTL-12/-X50/-100 [22,91,92] BCP-50 [96] Altair [20] SN-50 [21]	MAI-6000 [23] NEMO [85] LEOS-30 [95] DEFIANT [85] SMALL SAT 12U [12]
			EON-IR [25]	CrIS [25]
			Available commercial platform (Non-exclusive)
Hyperspectral sounder (IR)	Atmospheric pressure (over sea surface) Sea surface temperature	Cloud sensitivity	MAI-6000 [23] NEMO, DEFIANT [85] LEOS-30/-50/-100 [95] SN-50 [21] Altair [20] SMALL SAT 16U [12] SSTL-X50/-100 [91,92] BCP-50 [96]	DAUNTLESS [85] SN-200 [94] Eagle-1M, LEOStart-2 BUS [90] LEOSTART-500XO [9] SSTL-600 [92] ELiTeBUS 1000 [10]

The background color in the Table indicates the platform suitable for the instrument according to the power and mass requirements: very lightgray: nano-platform; light gray: micro-platform; gray:mini-platform.

and

Table 7. Mapping of potential active sensors and platforms to meet the user requirements.

Technology Type	Measurements	Instrument Limitations	Instruments Identified
			RapidScat [24]	SCAT [25,82]
			Available commercial platform (Non-exclusive)
Real Aperture Radar scatterometer	Wind speed over sea surface (horizontal) Sea ice extent Sea ice cover	Accuracy	SSTL-600 [92] LEOSTART-500XO [9] LEOStar-2 BUS [90] EliTeBUS 1000 [10]	DAUNTLES [85] BCP-100 [87] SN-200 [94] Eagle-1M [90] SSTL-600 [92] LEOSTART-500XO [9] LEOStar-2 BUS [90] EliTeBUS 1000 [10]
			Altika [25]	SRAL [24,25]
			Available commercial platform (Non-exclusive)
Real Aperture Radar Altimeter   and/or   SAR Altimeter	Ocean surface currents Significant wave height Dominant wave direction Wind speed over sea surface (horizontal) Sea ice type Sea ice cover Sea ice thickness	Long-time analysis and narrow coverage	SN-50 [21] Altair [20]	DAUNTLESS [85] SSTL-150 ESPA/-300/-600 [86,92,93] BCP-100 [87] SN-200 [94] Eagle-1M, LEOStar-2 BUS [90] TET-XL [13] LEOSTART-500XO [9] ELiTeBUS 1000 [10]
			COSI [24]	Severjamin [25,83]
			Available commercial platform (Non-exclusive)
SAR Imager	Ocean surface currents Wind speed over sea surface Dominant wave direction Dominant wave period Significant wave Height Sea ice type Sea ice cover Sea ice thickness Iceberg tracking Sea ice drift Sea ice extent Ocean imagery and water leaving radiance	Narrow coverage	LEOStar-2 BUS [90]	LEOStar-2 BUS [90] EliTeBUS 1000 [10]
Lidar Altimeter			ATLAS [24]	GEDI lidar [24]
			Available commercial platform (Non-exclusive)
	Sea ice thickness	Cloud sensitivity long time analysis narrow covarage	ELiTeBUS 1000 [10] LEOStart-2 BUS [90]

The background color in the Table indicates the platform suitable for the instrument according to the power and mass requirements: light gray: micro-platform; gray:mini-platform.

show the potential technologies studied in this work, with the suitable platforms and limitations with respect to the needs detected in the horizon 2020–2030. Platforms are selected according to their capacity to support the instrument mass and power consumption (available commercial platforms surveyed,

Table A1. Survey of available nano-satellite platforms for Earth Observation.

Product	Manufacturer	Total Mass [kg]	Size [cm]	Payload Mass [kg]	Payload Volume	Payload Power [W]	Pointing Control	Pointing Knowledge	Communication Downlink	Propulsion
THUNDER (3U) [85]	Space Flight Laboratory	3.5	10 × 10 × 34	1	1000 cm${}^3$	1–2 average	2${}^{\circ }$	-	S-band 32 kbps–2 Mbps	Cold Gas
Endeavour-3U [18]	Tyvak NanoSatellite Technology Inc.	5.99	30 × 10 × 10	-	2U	12 average, 70 peak	3${}^{\circ }$	25 arcsec	UHF, S-band 10 Mbps	Cold gas
GRYPHON (GNB) [85]	Space Flight Laboratory	7	20 × 20 × 20	2	1700 cm${}^3$	3–4 average, 6 peak	2${}^{\circ }$	-	S-band 32 kbps–2 Mbps	Cold gas
GOMX 1U [98]	GomSpace ApS	0.725	1U	-	0.4U	1.33 average	10${}^{\circ }$	5${}^{\circ }$	UHF, VHF	-
GOMX 2U [98]	GomSpace ApS	1.2	2U	-	1.4U	2.48 average	10${}^{\circ }$	5${}^{\circ }$	UHF, VHF	-
GOMX 3U [98]	GomSpace ApS	1.5	3U	-	2.3U	9.4 average	10${}^{\circ }$	5${}^{\circ }$	UHF, VHF, optional X-band	-
SMALL SAT 6U [12]	Nexeya	10	10 × 22 × 34	3	-	7 average, 100 peak	-	-	X-band 100 Mb	Available
XB-12 [19]	Blue Canyon Technologies LLC	-	12U	-	11U	-	1 arcsec	0.002${}^{\circ }$	UHF, S-band, X-band Up to 15 Mbps	Up to 7 thrusters
XB-3 [19]	Blue Canyon Technologies LLC	-	3U	-	2U	-	-	-	UHF, S-band, X-band Up to 15 Mbps	Up to 7 thrusters
XB-6 [19]	Blue Canyon Technologies LLC	-	6U	-	5U	-	1 arcsec	0.002${}^{\circ }$	UHF, S-band, X-band Up to 15 Mbps	Up to 7 thrusters
MAI-3000 [17]	Maryland Aerospace	8	10 × 10 × 30	3	1.5U	12 average	0.1${}^{\circ }$ ${}^a$ or 1.1${}^{\circ }$ ${}^b$	0.01${}^{\circ }$ ${}^a$ or 1${}^{\circ }$ ${}^b$	S-band Up to 2 Mbps, X-band available.	Compatible with existing 3U launch adapters

,

Table A2. Survey of available micro-satellite platforms for Earth Observation.

Product	Manufacturer	Total Mass [kg]	Size [cm]	Payload Mass [kg]	Payload Volume	Payload Power Average/Peak [W]	Pointing Control	Pointing Knowledge	Communication	Propulsion
MAI-6000 [23]	Maryland Aerospace	29	10 × 20 × 30	12	4U	20	0.1${}^{\circ }$	0.01${}^{\circ }$	S-band Up to 2 Mbps and X-band available.	Compatible with existing launch dispensers
SN-50 [21]	Sierra Nevada Corporation Space Systems	-	-	50	40 × 40 ${}^a$ cm	100	0.03${}^{\circ }$	0.024${}^{\circ }$	3.5 Mbps	Optional green propulsion capability
Altair [20]	Millennium Space Systems	-	30 × 30 × 30	50	-	90/250	20 arcsec	10 arcsec	S-Band—2 Mbps downlink	-
LEOS-30 ${}^b$ [95]	Berlin Space Technologies GmbH	30	30 × 30 × 50	8	-	15/60	-	-	S-Band—2 Mbps downlink	-
LEOS-50 ${}^b$ [95]	Berlin Space Technologies GmbH	60	50 × 50 × 30	15	-	20/140	-	-	X-band—100 Mbps downlink	-
NEMO [85]	Space Flight Laboratory	15	20 × 30 × 40	6	8000 cm${}^3$	45	2	-	S-band 32 kbps–2 Mbps downlink	Cold gas, resistojet, monopropulsion
DEFIANT [85]	Space Flight Laboratory	20–30	30 × 30 × 40	6–10	11,000 cm${}^3$	45	2	-	32 kbps–50 Mbps downlink	Cold gas, resistojet, monopropulsion
SMALL SAT 12U [12]	Nexeya	20	22 × 22 × 34	30	-	12/100	-	-	S-band 2.5 Mbps downlink, 256 kbps uplink, Optional X-band 100 Mbps downlink	Available
SMALL SAT 16U [12]	Nexeya	-	46 × 22 × 22	13	-	16/150	-	-	-	Available
SMALL SAT 27U [12]	Nexeya	40	35 × 35 × 34	25	-	30/200	-	-	-	Available
SSTL-12 [22]	Surrey Satellite Technology Limited	40–75	39 × 39 × 47	Up 45	39 × 39 × 37 cm${}^3$	10–30	2${}^{\circ }$	0.007${}^{\circ }$	Up to 160 Mbps (X-band)	Available
SSTL-X50 Platform [91]	Surrey Satellite Technology Limited	75	-	Up 45	53 × 43 × 40 cm${}^3$	35/85	0.07${}^{\circ }$	10 arcsec	-	Available
SSTL-100 [92]	Surrey Satellite Technology Limited	Up 100	-	15	32.1 × 30.3 × 24.6 ${}^c$ cm${}^3$ 17.9 × 21.6 × 39 ${}^d$ cm${}^3$	24/48	2880 arcsec	2520 arcsec	Up 80 Mbps	Liquefied Butane Gas
XB Microsat [19]	Blue Canyon Technologies LLC	75	-	-	45 × 45 × 80 cm${}^3$	-	0.002${}^{\circ }$	1 arcsec	UHF, S-band, X-band Up to 150 Mbps downlink	Up to 7 thrusters
BCP-50 [96]	Ball Aerospace Commercial Technologies Corp.	80	-	30	30 × 30 × 55 cm${}^3$	30 e, 100 ${}^f$	0.03${}^{\circ }$–0.10${}^{\circ }$	0.03${}^{\circ }$	2 Mbps downlink,	-
LEOS-100 ${}^f$ [95]	Berlin Space Technologies GmbH	90	60 × 60 × 82.5	30	-	60/140	-	-	X-band—100 Mbps downlink	-

${}^a$ Height limited by LV Fairing; ${}^b$ Integrated payload. Carry optical payload; ${}^c$ Main payload; ${}^d$ Secondary payload; ^e Worse case; ${}^f$ Best case.

and

Table A3. Survey of available mini-platforms for Earth Observation.

Product	Manufacturer	Total Mass [kg]	Size [cm${}^3$]	Payload Mass [kg]	Payload Volume [cm${}^3$]	Payload Power Average/Peak [W]	Pointing Control	Pointing Knowledge	Payload Data [Downlink]	Propulsion
NAUTILUS (NEMO-150) [85]	Space Flight Laboratory	Up 150	60 × 60 × 60	Up 70	Up 108000	50/500	2${}^{\circ }$	-	up to 50 Mbps	Cold gas, resistojet, monopropulsion, Hall thruster.
DAUNTLESS [85]	Space Flight Laboratory	Up 500	100 × 100 × 100	Up 250	Up 500000	200/1000	2${}^{\circ }$	-	up to 200 Mbps	Cold gas, resistojet, monopropulsion, Hall thruster.
SSTL-150 [92]	Surrey Satellite Technology Limited	Up 150	60 × 60 × 30	50	27.95 × 23.15 × 25.25	50 average, 100 peak.	36 arcsec	25 arcsec	80 Mbps	Hot gas Xenon resistojet.
SSTL-150 ESPA [86]	Surrey Satellite Technology Limited	-	60 × 60 × 80	65	47.5 × 50.5 × 21.1 41 × 54.7 × 24.4	120	1 arcmin	2.5 arcsec	2 Mbps	Available
SSTL-300 [92,93]	Surrey Satellite Technology Limited	368	89.9 × 81.5 × 106.1	150	27.95 × 23.15 × 25.25	140	360 arcsec	72 arcsec	S-Band	Hot gas Xenon resistojet
TET-1 [111]	Astro- und Feinwerktechnik Adlershof	120	67 × 58 × 88	50	460 × 460 × 428	20 to 80 average, 160 peak for 20 min	2 arcmin	10 arcsec	S-band—2.2 Mbps	-
BCP-100 [87]	Ball Aerospace Commercial Technologies Corp.	180	60.9 × 71.1 × 96.5	70	140,000	100–200	0.03${}^{\circ }$– 0.10${}^{\circ }$	0.03${}^{\circ }$	2 Mbps for each payload${}^a$	Green Propellant, Hydrazine options
SN- 200 [94]	Sierra Nevada Corporation Space Systems	Up 355	-	200	-	200	0.1${}^{\circ }$	0.05${}^{\circ }$	274 Mbps (X-band)	Xenon HET (TacSat), 4.5
SSTL-600 [92]	Surrey Satellite Technology Limited	Up 429	190 × 140 × 47.6	200	90.1 × 90.8 × 26	386 average, 450 peak	605 arcsec	360 arcsec	500 Mbps (X-band)	Liquefied butane gas
Eagle-1M [90]	Northrop Grumman	-	-	>175	-	500 average, 1200 peak.	0.05${}^{\circ }$	90 arcsec	-	200 m/s modular
TET-X [13]	OHB	120	58 × 88 × 67	50	1700	Max. 80, 160 peak for 25 min	-	10 arcsec	100 Mbit/s (X-Band)	Micro propulsion system
TET-XL [13]	OHB	200	80 × 84.5 × 80	80	900	Max. 150, 460 peak for 25 min.	-	10 arcsec	400 Mbit/s (X-Band), or 1.2 Gbit/s (Ka-Band)	Micro propulsion system
LEOStar-2 BUS [90]	Northrop Grumman	150–500	-	210–550	1,388,000	up to 2k (optional)	15 arcsec	6 arcsec	2 Mbps (S-Band), 150 Mbps (X-band)	Blowdown monopropellant hydrazine;
LEOSTART-500XO [9]	Astrium	500–1000	-	150–600	-	250 average, 450 peak	0.35${}^{\circ }$	0.24 deg	1.6 Mbps (downlink),	Available
ELiTeBUS 1000 [10]	Thales Alenia Space	-	-	350	38 × 27.12 × 14.25	1000–1500	360 arcsec	22 arcsec	-	Mono-prop (N2H4)

). Additionally, it takes in to account the platforms with minor categorization (e.g., nano-, micro-, or mini-platforms), that satisfy both requirements. Special attention has been paid to the possibility to use new techniques and smaller platforms, focusing on the quality of the measurements as compared to the ones generated by full-fledged payloads onboard large spacecrafts. Indeed, since a small platform also means less volume, mass, power and data rate for the payload, the measurements are usually of reduced quality. Depending on the mission (i.e., environmental data), this may be compensated by more frequent data acquisitions (exchange between measurement quality and revisit time), yet to be evaluated on a case-by-case basis. A brief the potential instruments, suitable platforms, and technological limitations are explained below:

• GNSS-R (1.4 kg, 12 W) instruments are suitable for nanosatellites (3U or 6U). Table 6 presents sample available commercial platforms for the SGR-ReSi [57], such as the Endeavour-3U [18] and the MAI-3000 [17]. Endeavour by Tyvak Nanosatellite Technology Inc. (San Luis Obispo, CA. United States of America), is a 3U platform with 15 W of average payload power, 3 deg of pointing control. MAI-3000 by Maryland Aerospace, is a 3U platform with 12 W of payload power and 3 kg of available payload mass. The main limitation of GNSS-R altimetry data is the poorer (decimetric) resolution and accuracy (∼20 cm for SSH, and 2 m/s for wind speed) are offset by the much larger number of simultaneous observations from different specular reflection points [80].
• Another good example are microwave sounders on small-platforms such as EON-MW [33], for measuring the atmospheric pressure over the sea surface. However, the antenna system must be redesigned to achieve the spatial resolution required. For a 10 km spatial resolution, at 50 GHz, the require antenna aperture is 36 cm, from an altitude of 600 km. Table 6 summarizes a list of the available commercial micro-platforms suitable for this instrument.
• Microwave imagers at X-, K-, Ka-, and W- bands are particularly well suited for implementation on small platforms (Table 6). TMI is a light instrument suitable for mini-satellites, with X-, K-, Ka-, and W- bands capable of measuring and covering the gaps for wind speed, sea ice cover, sea ice type, and sea surface temperature variables. For sea surface temperature, microwave radiometers improve the coverage in polar regions because of their all weather capabilities. In order to obtain a spatial resolution of 10 km at 18.7 GHz from 600 km height, a 2.2 m antenna is required. On the other hand, an SSM/I type of instrument with a modified antenna, could be implemented in a micro-platform in order to cover wind speed over the sea surface, sea ice cover, and sea ice measurements, with the required performance. L-band radiometers contribute to sea ice thickness monitoring, agriculture (soil moisture) and forestry measurements. Those instruments are suitable for mini-platforms (Table 6). The main limitation is their coarse resolution. Inflatable antennas must be used to reduce the footprint size, or aperture synthesis techniques could be implemented [81]. ELiTeBUS 1000 [10] by Thales Alenia Space (Cannes, France) is an available commercial small-platform suitable for this instrument. ELiTeBUS 1000 is a platform for Medium Earth Orbit (MEO) and Low Earth Orbit (LEO) orbit with 1000 to 1500 W of available payload power.
• Scatterometers contribute to the Marine for Weather Forecast and Sea Ice Monitoring use cases. The instrument taken as a reference is the SCAT on board the CFOSAT mission [25,82], the power consumption of this sensor is less than 200 W, and the mass less than 200 kg. According to the power consumption and mass requirements, this payload can be carried on board mini-platforms (Table 7). Scatterometers are valuable sensors for wind measurements. However, the main limitations are the coarse accuracy and spatial resolution of the data. However, their wide swath and the possibility of scatterometer constellations open the door to improve the accuracy and spatial resolution, combining the data from multiple passes of different satellites.
• For radar altimeters, the accuracy of the measurements depends on the Pulse Repetition Frequency (PRF), which is directly driven by the power available on-board to the payload. Since the power available on-board decreases with solar panel size, the accuracy of the measurements on a small satellite is also expected to be degraded as compared to that of large satellites. For example, if the power consumption is reduced by a factor of 4, the PRF is reduced roughly by the same factor, and the Root-Mean-Square (RMS) error increases by a factor of 2. For the Jason-2 altimeter (power consumption ∼70 W), a reduction of its power consumption to 1 W, would increase the sensor error level from 2 cm to ∼16.7 cm, which is actually comparable to GNSS-R [55,82]. It is easy to understand that the types of products that can be generated with this accuracy are different from the ones generated with an SRAL radar altimeter, but one must also consider that the number of radar altimeters with a transmitted power of 1 W that can be manufactured and launched at the same cost as for a high accuracy radar altimeter is much larger. These few examples illustrate the fact that the quality and frequency of the measurements have to be considered in the overall comparison process. In some cases, the concept of operations may partially be compensated by the degradation of the quality of the individual measurements (e.g., part-time measurement instead of systematic measurement if the power available on board is the main parameter driving the performance of the measurement).
• SAR sensors are one of the most effective instruments for ocean, land, and ice observation. A good example of miniaturization of this technology is the Severjamin-M instrument (Meteor-M N missions) [83], an X-band SAR with power consumption of 1 kW and a mass of 150 kg, including the mass of the antenna of 40 kg. The main technological limitation is the narrow swath, but this could be compensated with a constellation of SAR satellites.
• Optical payloads are characterized in terms of image quality such as the Ground Sampling Distance (GSD), the Modulation Transfer Function (MTF), and the Signal-to-Noise Ratio (SNR). To be able to interpret an image (e.g., in the maritime surveillance, the capability to estimate the type of a boat), the GSD is not sufficient, since a degraded MTF (i.e., blurred image) or a degraded SNR (noisier image) would prevent it. Ensuring a good MTF and SNR for a given GSD requires a minimum aperture for the optical instrument, and reducing it below this minimum value will limit the type of applications. Image quality is also limited by the platform’s attitude control system, i.e, any jitter in the pointing will blur the image. This has also to be taken into account as smaller platforms exhibit poorer performances.

5. Reference Instrument Selection

The main requests of any satellite monitoring mission can be summarized as follows: (1) that observations are acquired with the required revisit time; (2) preferably in all weather conditions (clouds, rain, haze, and fog) and in all illumination conditions; (3) with a large swath to reduce the revisit time; (4) with the required radiometric and spatial resolutions; (5) with low manufacturing and launch costs, and with minimum deployment time in case of failure; and (6) keeping these parameters in mind, the reference instruments can be selected. In this way, the identification of instruments is based on the state-of-the-art at the payload level and the need to fulfill the gaps of the current Copernicus infrastructure.

Reference instruments and small platforms have been selected in the previous chapter. In this way, it has as strategy been implemented a significant reduction of the development time and cost, thanks to the adoption of commercial technologies, but it requires that these have a good performance of the measurement capabilities. In this regard, the capability of the instrument technologies is evaluated according to the trends in the design for small satellites. For each instrument, the mass and power consumption constraints, and data quality (spatial resolution, swath, and accuracy) are taken as a reference. This chapter evaluates if the instruments selected to meet the requirements (defined in [6]) in terms of spatial resolution and accuracy.

Table 8. Reference instruments selected to cover the measurements with gaps.

Instrument	Measurements	Requirements [109]
		Accuracy	Spatial Resolution
SGR-ReSI [57]	Soil Moisture at the surface	<0.01 m ${}^3$/m ${}^3$	10 km
	Sea ice thickness	1 cm	1 cm (vertical)
	Dominant wave direction	10${}^{\circ }$	1–15 km
	Wind speed over the sea surface	0.5 m/s	1–10 km
	Significant wave height	0.1 m	1–25 km
	Sea ice cover	5 %	12 km–10 m
	Ocean surface currents	0.5 m/s 10${}^{\circ }$	1–25 km
EON- Microwave [33] (Ka-, U-, D-bands) (22 channels)	Atmospheric pressure over sea surface	5 %	1–25 km
MIRAS [25,88] (L- band)	Soil Moisture at the surface	<0.01 m ${}^3$/m ${}^3$	10 km
	Sea ice thickness	1 cm	1 cm (vertical)
	Crop grow & condition	-	2 km
	Sea ice cover	5 %	12 km–10 m
SSM/I ${}^a$ [84] (K, Ka, W)	Wind speed over sea surface	0.5 m/s	1–10 km
	Sea ice cover	5 %	12 km–10 m
	Sea ice type	0.25/classes	10 m
	Sea ice drift	0.5 m/s 10${}^{\circ }$	10 m
TMI ${}^b$ [24] (X, K, Ka, W)	Wind speed over sea surface	0.5 m/s	1–10 km
	Sea ice cover	5 %	12 km–10 m
	Sea ice type	0.25/classes	10 m
	Sea ice drift	0.5 m/s 10${}^{\circ }$	10 m
	Sea surface temperatture	0.3 K	1–10 km
AVHRR/3 [61] (VIS, NIR, MWIR, TIR)	Ocean chlorophyll concentration	0.05 mg/m ${}^3$	1 km
	Ocean imagery and water leaving radiance	5%	1 km
	Color Dissolved Organic Mater (CDOM)	5%	1 km
	Sea Surface Temperature (SST)	0.3 K	1–10 km
	Detection of water stress in crops	5%	2–7 m
	Estimation of crop evapotranspiration	-	1–10 m
	Sea Ice Cover	5 %	12 km–10 m
COMIS [24] (VIS, NIR)	CDOM	5%	1 km
	Sea Ice Cover	5 %	12 km–10 m
EON-IR	Sea Surface Temperature (SST)	0.3 K	1–10 km
	Atmospheric pressure over sea surface	5 %	1 km–25 km
SCAT [24] (Ku-band)	Wind speed over the sea surface	0.5 m/s	1–10 km
	Sea ice extent	5%	12 km–10 m
	Sea ice cover	5 %	12 km–10 m
SRAL [24,25] (C- & Ku-bands)	Ocean surface currents	0.5 m/s 10${}^{\circ }$	1–25 km
	Significant wave height	0.1 m	1–25 km
	Dominant wave direction	10${}^{\circ }$	1–15 km
	Sea ice type	0.25/classes	10 m
	Sea ice thickness	1 cm	1 cm (vertical)
	Sea ice cover	5 %	12 km–10 m
	Wind speed over the sea surface	0.5 m/s	1–10 km
Severjamin [25,83] (X-band)	Ocean surface currents	0.5 m/s 10${}^{\circ }$	1–25 km
	Iceberg tracking	5%	10 m
	Sea ice drift	0.5 m/s 10${}^{\circ }$	10 m
	Sea ice extent	5%	12 km–10 m
	Sea ice type	0.25/classes	10 m
	Sea ice cover	5 %	12 km–10 m
	Dominant wave direction	10${}^{\circ }$	1–15 km
	Significant wave height	0.1 m	1–25 km
	Sea ice thickness	1 cm	1 cm (vertical)
	Ocean Imagery and water leaving radiance	5%	1 km
	Wind speed over the sea surface	0.5 m/s	1–10 km
ATLAS [24] (VIS & NIR)	Sea ice thickness	1 cm	1 cm (vertical)

^a antenna size of 2.2 m. ^b antenna size 3.4 m. The background color in the requirements denotes: Green: Requirement met or is better; Yellow: Minimum requirement met; Red: Have worst performance that the minimum requirement. The background color in the instrument indicates the platform suitable according to the power and mass requirements: Very light gray: Nano-platform; Light gray: Micro-platform; Gray: Mini-Platform.

summarizes the performance requirements over each instrument:

• SGR-ReSI instrument presents a good performance for sea ice cover [99] because it satisfies the minimum requirement for spatial resolution and accuracy. For ocean surface currents, and significant wave height measurements satisfy the minimum requirement of spatial resolution at 25 km [100]. For other measurements, such as sea ice thickness [46], soil moisture [101], and wind speed [80] present worse performance than the minimum spatial resolution and accuracy requirements.
• EON-MW is a satellite project under development and presents an approximate performance that the Advanced Technology Microwave Sounder (ATMS) [33], in this way, it will be expected that the instrument satisfies the minimum requirements for accuracy of 5% and spatial resolution at 23 km for atmospheric pressure over sea surface measurements (channel from 50 to 60 GHz).
• MIRAS instrument presents a coarse spatial resolution ∼35 × 50 km for horizontal- and vertical- polarization. This instrument has an accuracy of 0.04 m${}^3$/m${}^3$ for soil moisture measurements [102] that is worse than 0.01 m${}^3$/m${}^3$ required. For sea ice thickness, the accuracy is worse than the 1 cm required [103], but it can have an accuracy of 5% for sea ice cover.
• SSM/I using an antenna (inflatable) of 2.2 m from 600 km orbit altitude can obtain a spatial resolution of 10 km and satisfy the minimal spatial resolution requirement for wind speed, and sea ice cover measurements. The accuracy for wind speed measurement can be until 1.5 m/s [104], and for sea ice data from 10% to 20% [105].
• TMI in order to meet the minimal spatial resolution requirement of 10 km (at 10.65 GHz) was proposed the modification of the aperture size of the antenna at 3.4 m (inflatable antenna). The accuracy for SST is of 0.5 K [104]. The accuracy is between 10% and 20% for sea ice data [105].
• AVHRR/3 presents a spatial resolution ∼1 km, and computes an accuracy better than 0.1 K [106].
• EON-IR is expected to be better than 0.25 K and present, with spatial resolution at 13.5 km.
• SCAT—the accuracy for wind speed monitoring is 2 m/s, and for sea ice monitoring is 5%.
• SRAL in SAR mode has a spatial resolution of 300 m, the accuracy for wind speed measurements is of 2 m/s [107]; for significant wave height, the accuracy is between 2 cm to 8 cm [108].
• Severjamin has a spatial resolution from 400 m to 1 km depending on the operation mode can satisfy many minimal requirements for some measurements.
• GLAS acquires the geophysical variables with a vertical spatial resolution of 10 cm, which does not satisfy the user requirement for sea ice thickness measurements.

6. Quantitative Method to Identify the Potential Technologies to Cover the Future Copernicus Gaps

In order to identify the potential technologies to cover future gaps over Copernicus infrastructure, a quantitative method has been defined starting from the perspective of the instrument technologies and the variables with gaps. The analysis is centered on the list of the top 10 use cases and 20 variables detected with gaps, and the potential instruments which have been proposed in Table 8. A quantitative method has been applied to rank the technologies suitable to measure the variables with gaps, and identify which technologies cover most of the requirements. The rank order weights used is based on the user requirements, and measurements priorities.

A weighting system for the instrument performance parameter has been implemented. First, it defined the numerical score for each instrument capability based on user requirements (

Table 9. Definition of the numerical score for the criteria and result of the weights.

Instrument Capabilities	Weight	Numerical Score
		1	2	3
Latency	19.2%	>3 h	2–1 h	<1 h
Spatial Resolution	15.4%	>1 km	1 km	<1 km
Revisit time	15.4%	Revisit time >24 h	Revisit time: 3–24 h	Revisit time <3 h
Accuracy	14.1%	Worse that state of the art	Equal to state of the art	better that state of the art
Payload mass	12.8%	large	mini	nano-micro
Payload power Consumption	12.8%	large	mini	nano-micro
Measurements relevance	10.3%	Low	Medium	High

). Then, these numerical scores are evaluated for each measurement with gaps and each factor. In this way, the numerical score for latency is assigned for measurement that required latency time <1 h; for spatial resolution, a high score is assigned for measurement that required spatial resolution <1 km; for the revisit time, a high score for geophysical variables that required <3 h is assigned; for accuracy, a high score for measurements that require accuracy better than the state of the art is assigned. For payload mass and power consumption, the corresponding score for mini and micro platform is assigned; the measurement relevance was assigned taking the following:

• High relevance measurements: ocean surface currents, wind speed over sea surface, dominant wave direction, and significant wave height measurements.
• Medium relevance measurements: sea ice cover, sea ice type, sea surface temperature, and atmospheric pressure over the sea surface.
• Low relevance measurements: Ocean chlorophyll concentration, ocean imagery and weather leaving radiance, CDOM, monitoring system vessels, sea ice extent, sea ice thickness, iceberg tracking, sea ice drift, estimation of crop evapotranspiration, detection of water stress in crops, crop grow and conditions.

Then, the weights for each factor (latency, revisit time, spatial resolution, accuracy, payload mass, payload power, and measurement relevance) are derived by the normalization of the average of the numerical score assigned for each measurement:

$$W_j={\displaystyle \frac{{\displaystyle \frac{1}{n}}{\sum }_i^{n}Numerica{l}_{scor{e}_i}}{{\sum }_j^m{\displaystyle \frac{1}{n}}{\sum }_i^{n}Numerica{l}_{scor{e}_i}}},$$

(1)

where i represents each measurement, and j represents each factor. In order to identify the potential technologies, new numerical scores are assigned based on the instrument capabilities to measure the variables with gaps and how those meet the user requirements. Instrument attributes are defined in

Table 10. Instrument technologies’ attributes and related numerical scores.

Instrument Capabilities	Numerical Score
	0	1	2	3
Latency	N/A	high	medium	low
Spatial Resolution	N/A	worse than required	minimun requirement met	requirement meet or better
Swath	N/A	Narrow swath <400 km	Moderate swath <1000 km	Wide swath >1000
Accuracy	N/A	Worse than required	Equal to requirement	Requirement meet or better
Payload mass	N/A	large	mini	nano-micro
Payload power Consumption	N/A	>150 W	25–150 W	≤25 W
Data relevance	N/A	Marginal	High	Primary

. The requirements for the geophysical variables are evaluated in terms of seven criteria (factors) or instrument capabilities:

• Latency is referred the time to be processed the data to obtain the product.
• Swath is related to the ability of the instrument in order to cover an area, a wide swath indicates minor revisit time.
• Spatial resolution is evaluated for the reference instruments according to the user requirements for each measurement.
• Accuracy is a component of the data quality; it is evaluated according to it being closed to the user requirements for each reference instrument.
• Payload mass is evaluated for each reference instrument, giving priority to the instruments that are best suited to smaller platforms.
• Payload power is related to the power consumption of the payload; it also brings priority to the instruments that are best suited to smaller platforms.
• Data relevance is the potential of the sensor to provide the measure based on sensing constraints (e.g., long time to analyze the data, data limited by cloud cover, and daylight only)

This scoring method assigns a lower score to the technologies that require a large instrument (large mass and high power consumption), and the technologies that present low data quality (low coverage, low spatial resolution, high latency, low accuracy, and low relevance for specific measurement). The score for each instrument is expressed in the following equation:

$$Instrumen{t}_{score-by-mensurement}=\sum _j^m({\displaystyle \frac{Numerica{l}_{score}}{3}}\ast W_j),$$

(2)

where j represents each technology performances’ parameters such as latency, spatial resolution, swath, accuracy, payload mass, payload power consumption, and data relevance for each potential instrument; Numerical${}_{score}$ is assigned to each instrument by measurement (0, 1, 2 or 3); and $W_k$, is the weight assigned for each factor obtained of Equation (1) (Table 9, second column).

Four critical use cases were evaluated, such as Marine for Weather forecast, Sea Ice Monitoring, Agriculture and Forestry: Hydric Stress, and Fishing Pressure (

Table 11. The priority level of the measurement according to the use case priority.

Use Case Priority	Marine for Weather Forecast		Sea Ice Monitoring		Agriculture and Forestry: Hydric Stress		Fishing Pressure
Measurements	Priority Level	Weight [%]	Priority Level	Weight [%]	Priority Level	Weight [%]	Priority Level	Weight [%]
Ocean Surface currents	H	9.375	M	5.000	L	3.570	M	5.410
Wind speed over sea surface	H	9.375	M	5.000	L	3.570	M	5.410
Dominant wave direction	H	9.375	M	5.000	L	3.570	M	5.410
Significant wave height	H	9.375	M	5.000	L	3.570	M	5.410
Sea Surface temperature	M	6.250	H	7.500	L	3.570	H	8.110
Atmospheric pressure over sea surface	M	6.250	L	2.500	L	3.570	M	5.410
Sea ice cover	M	6.250	H	7.500	L	3.570	L	2.700
Sea ice type	M	6.250	H	7.500	L	3.570	L	2.700
Sea ice thickness	L	3.125	H	7.500	L	3.570	M	5.410
Iceberg tracking	L	3.125	H	7.500	L	3.570	M	5.410
Sea ice drift	L	3.125	H	7.500	L	3.570	L	2.700
Sea ice extent	L	3.125	H	7.500	L	3.570	L	2.700
Surface soil moisture	L	3.125	L	2.500	H	10.710	L	2.700
Ocean chlorophyll concentration	L	3.125	L	2.500	L	3.570	H	8.110
Ocean imagery and weather leaving radiance	L	3.125	M	5.000	L	3.570	H	8.110
Color dissolved organic mater	L	3.125	L	2.500	L	3.570	H	8.110
Estimation of crop evapotranspiration	L	3.125	L	2.500	H	10.710	L	2.700
Detection of water stress in crops	L	3.125	L	2.500	H	10.710	L	2.700
Crop growth & condition	L	3.125	L	2.500	H	10.710	L	2.700
Monitoring system vessels	L	3.125	M	5.000	L	3.570	H	8.110

Priority level and numerical score: L: Low = 1; M: Medium = 2; H: High = 3.

). Subsequently, high, medium, and low priority measurements were defined and its weights were assigned according to the use case to evaluate:

$$W_i={\displaystyle \frac{Numerica{l}_{scor{e}_i}}{{\sum }_i^{n}Numerica{l}_{scor{e}_i}}}.$$

(3)

When the instrument score by measurement is defined, the ranking of the instruments is obtained. The instrument ranking (

Table 12. Ranking results for each technology for each use case.

Instrument/Technology	Ranking Results [%]
	Marine for Weather Forecast	Sea Ice Monitoring	Agriculture and Forestry: Hydric Stress	Fishing Pressure
Multispectral Radiometer	21.6	23.1	30.1	31.2
Hyperspectral Radiometer	11.2	10.7	19.9	11.8
Hyperspectral. Sounder (IR)	10.6	8.5	6.1	11.4
L-Microwave Radiometer	8.5	10.6	19.4	8.1
Ka, K, W-Microwave Radiometer	19.3	21.6	11.2	10.4
GNSS-R	39.4	29.6	24.8	25.3
X-, Ka, K, W-Microwave Radiometer	21.2	23.7	12.1	14.6
Ka-, U-, D-Microwave Sounder	5.9	2.37	3.4	5.1
Automatic Identification System (AIS)	3.1	5.0	3.6	8.1
Radar Scatterometer	11.9	12.7	6.8	6.8
Lidar	1.04	2.5	1.2	1.8
Synthetic Aperture Radar (SAR) Altimeter	27.9	21.4	12.7	16.3
X-SAR Imager	30.8	32.5	18.23	23.56

) is computed as:

$$Rankin{g}_{instrument}=\sum _i^n(instrumen{t}_{score-by-measurement}\ast W_i).$$

(4)

In order to evaluate the robustness of the methodology implemented, a sensitivity analysis at 25% has been performed to estimate the impact of the weights over the ranking of the technologies. Figure 3 shows the same trend in the rank of the technologies by varying randomly 100 times all weights at the same time for each use case prioritized. In this model, the priority level of the measurements and the number of measurements that can measure the sensors are the critical parameters to rank the technologies.

When the priority use case is Marine for Weather Forecast, the key technologies in ranked order are GNSS-R, X- band SAR imager, and Radar Altimeter with SAR processing (Table 12, columns 1 and 2). The sensitivity analysis is summarized in Figure 3a. The simultaneously random weights defined a clear trend in each technology. Columns 1 and 3 of the Table 12 shows the relevant technologies when selecting the Sea Ice Monitoring use case as the priority. They are X-band SAR, GNSS-R, X-, K-, Ka-, W-band MWIm, and Radar Altimeter (SAR). Figure 3b presents a similar tendency in the results when the weights are varying randomly.

The valuable technologies for the Agriculture- Hydric stress use case in ranked order are Multispectral sensors, GNSS-R, Hyperspectral, and L-band MW; the same distribution has been found in the sensitivity analysis (Figure 3c). Figure 3d shows the sensitivity analysis of the technology rank when the Fishing Pressure use case is the priority. The most important technology also is the Multispectral sensor.

In general, the prioritized list of the main technologies to ensure that the gaps are covered taking into account the priority level of different use cases in the time frame 2020–2030 are GNSS-R, imaging X-band SAR, with 1 km of spatial resolution, and Multispectral sensor. GNSS-R provides support to marine and land services of Copernicus and can collaborate with other technologies to improve the measurements. SAR can provide several data from the ocean and can collaborate with the land data. The best ranked optical payload to support multiple services of Copernicus program is a Multispectral sensor with bands in the VIS (442.5, 485, 490, 510, 560, 640, 660, 665 nm), NIR (1610 nm), MWIR (3.7, and 4.05 $\mathsf{\mu }$m) and TIR (8.55, 11, and 12 $\mathsf{\mu }$m).

7. Conclusions

This study has reviewed the state of the art in EO sensors and platforms and has presented a methodology to select the best instruments’ technologies and platforms required to complement the Copernicus system in the time frame 2020–2030. Suitable instruments for small platforms have been analyzed using several attributes, and they have been ranked using a quantitative scoring method. Results show that the most relevant payloads capable of filling the measurements gaps are: GNSS-R at 10 km spatial resolution, X-band imaging SAR at 1 km spatial resolution, and multispectral Optical instrument with bands in the VIS (10 m of spatial resolution), NIR (10 m), MWIR (1 km), and TIR (1 km).

The high temporal resolution of one hour required can only be achieved if a sufficiently large number of spacecrafts are used; then, the architecture selection could be analyzed and optimized [31,71]. A distributed or Federated Satellite System (FSS) will help to reduce the temporal gaps. The possibility to create strategic alliances to establish distributed or federated architectures between different missions and agencies must be carefully evaluated to safe costs. Federated Satellite System (FSS) concepts could also be applied to future instrument technologies to cover the gaps, taking into account different satellites program and space agencies.