The European Space Agency's (ESA) BIOMASS mission is a pioneering Earth observation satellite mission launched on April 29, 2025. Utilizing a P-band synthetic aperture radar (SAR), the objective of BIOMASS is to deliver estimates of above-ground forest biomass, forest height (FH), and forest disturbance (FD), with unprecedented accuracy. The mission's primary scientific goal is to quantify the distribution and changes in forest biomass, thereby reducing uncertainties in carbon flux estimates and informing climate models. The satellite's advanced instrumentation and innovative approach allow it to penetrate dense forest canopies, capturing data even in challenging environments. The mission will operate in two distinct phases: the tomographic phase and the interferometric phase, which will support polarimetric interferometric SAR (Pol-InSAR) and tomographic SAR (TomoSAR) processing. Additionally, BIOMASS will provide valuable observational data for ice sheets, deserts, the ionosphere, below canopy topography, and other domains.

In this study we present some preliminary achievements on our proposed deep learning framework specifically designed to perform Sentinel-1 polarimetric information reconstruction. In particular, we aim at demonstrating our deep learning framework ability to generate missing polarization information from single-polarization datasets, with a view to supporting the final generation of useful quicklooks also starting from single-polarization Sentinel-1 data. After a robust validation, the deep learning framework may prove effective in both qualitative and quantitative assessments based on reconstructed quicklooks, notably for the Sentinel-1 Wave (WV) Mode acquisitions, generally acquired and delivered at a single polarization mode, thus with no default colorization scheme for quicklooks.

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This work was conceived to analyze the impact of the different instances of the Copernicus DEM (CopDEM) dataset (named: EEA-10, GLO-30, GLO-90) on the orthorectification of Very High Resolution (VHR) optical data (spatial resolution: 2–4 m). Indeed, the CopDEM instances are characterized by different pixel sizes/spatial coverages/licenses (EEA-10: 10&12 m/European/restricted; GLO-30: 30 m/global/public; GLO-90: 90 m/global/public). Findings showed that all the CopDEM instances provided valuable topographic information that allows reaching similar values of geolocation accuracy. The latter is only slightly influenced by the different pixel sizes of the data. Moreover, this research provided valuable insights related to the existing relationships between the geolocation accuracy and: i) the spatial resolution of the VHR input products; ii) the orography and land cover of the target areas. The analysis also highlighted the importance of the GLO-30 instance for orthorectification purposes, as it is freely and globally available.

This work was conceived for assessing the potential of the Copernicus DEM (CopDEM) dataset to identify (flash) flood-prone areas by using a geomorphological approach. This dataset is distributed in different instances (named: EEA-10, GLO-30, GLO-90) characterized by different pixel sizes/spatial coverages/licenses (EEA-10: 10&12 m/European/restricted; GLO-30: 30 m/global/public; GLO- 90: 90 m/global/public). The analysis compared the performances of the different instances for the abovementioned application. An exemplifying Mediterranean catchment located in Italy was used as test area. Results showed that the CopDEM dataset was successfully capable of identifying (flash) flood-prone areas. The best results were obtained by the EEA-10 and GLO-30 instances. The analysis also highlighted the importance of the GLO-30 instance to map flood prone-areas, as it is freely and globally available. Moreover, the GLO-30 instance outperformed other freely available DEMs distributed with a pixel size of 30 m (i.e., ALOS AW3D30, ASTER GDEM, SRTM) that were analyzed for comparative purposes.

In the recent years, the Earth observation (EO) capacity from space has grown with the multiplication of both institutional and commercial missions; in particular the domain of high-resolution optical sensors and SAR (Synthetic Aperture Radar) has dramatically increased. The “NewSpace players” are considered in full in the evolution of the EO international strategy. In this context, ESA and NASA put in place several activities that aim at assessing the data coming from these new missions, like the ESA’ s Earthnet Data Assessment Pilot (EDAP) project and the NASA's Commercial Smallsat Data Acquisition (CSDA) Program. Given the initial success of both of these activities and the multiplication of new missions in the context of the NewSpace, ESA and NASA are proposing to extend these activities with a coordinated approach and the definition of joint guidelines for data quality assessment.

In order to help scientists in the above ground biomass community and to support the science behind the upcoming BIOMASS satellite missions, ESA is building a cloud-computing platform called Multi-Mission Algorithm and Analysis Platform (MAAP). The MAAP is jointly developed and implemented with NASA and will include not only data (satellite, airborne, in situ data and products), but also high performing computing capabilities and tools and algorithms developed to support this specific field of research. To best ensure that users are able to collaborate across the platform and to access needed resources, the MAAP requires all data, algorithms, and software to conform to open access and open-source policies. As one such example of best collaborative and open-source practices, the BIOMASS data processing algorithms are developed on MAAP under the umbrella of an open-source scientific software project called BioPAL. In addition to aiding researchers, the MAAP will focus on sharing data, science algorithms and compute resources in order to foster and accelerate scientific research.

The Copernicus Coordinated data Quality Control (CQC) service is in charge of monitoring the quality of Earth Observation (EO) products and datasets generated by the Copernicus Contributing Missions (CCMs) and distributed within the Copernicus programme. To this aim, it develops and applies rigorous quality assessment procedures. Within this context, this paper describes the workflow designed by the CQC service for evaluating the quality of EO-derived Digital Elevation Models (DEMs). The paper also summarizes the outcome of the quality analysis performed on the Copernicus DEM dataset to assess its absolute vertical accuracy in Spain. This location was selected because of the availability of reliable reference elevation data to use for the assessment in areas characterised by different land cover and slope classes. Results showed that the dataset is compliant with respect to its nominal quality specifications.

Radio Frequency Interference (RFI) is a well-known issue since the early days of telecommunications. Traditionally considered an occasional event in the Earth Observation domain, RFI is becoming a severe problem due to the surge of wireless LANs and the increasing number of operational EO missions. In the near future, RFI will eventually be treated as an additional source of noise, to be addressed not only for mitigation, but also during mission design. Sentinel-1 (S-1) is a constellation of two spaceborne C-band synthetic aperture radar (SAR) sensors developed and operated by the European Space Agency under the Copernicus programme. In this paper, S-1 thermal noise measurements are used to create an automatic monitoring system generating world RFI maps with a periodicity of 12 days. For tuning the system, the RFI power is calibrated against a radiometer operating at the same range of frequencies. Analysing the strength and geographical distribution of the RFI, the most affected regions are identified and probability maps are extracted.

Presented is a new quality assurance (QA) framework for Earth Observation missions that has been developed as a joint initiative between ESA and NASA. It aims ensure the rigorous assessment of all aspects of relevant aspects of mission quality, verifying claimed mission performance and, where applicable, reviewing the extent to which the mission follows community best practice in a manner that is “fit for purpose”. The QA framework has potential for more general use in both institutional and commercial Earth Observation – helping mission providers to understand the information their users' needs and empowering users to make informed decisions about which data is fit for their purpose.

Recent availability of low-cost small satellites and innovation of constellations have resulted in an increasing number of commercial companies having established information services fed by their own satellite systems. ESA aims to foster cooperation and collaboration with not only other national agencies, but also these New Space players, inviting some missions as potential candidates for ESA's long standing Earthnet Programme. The Earthnet Data Assessment Pilot (EDAP), headed by Telespazio UK, provides a consortium of expertise to assess data quality and suitability of individual missions for this purpose. The service framework has developed a common quality assessment methodology adapted for instrument-specific domains covering Optical, Synthetic Aperture Radar (SAR) and Atmospheric missions, with emphasis on multi-mission studies. This paper describes the EDAP framework and provides a summary of specific tasks performed by the service to assist the ESA Earthnet programme in supporting various commercial mission providers in preparation for future EO missions.

In the context of innovative sensors and a changing ground segments, the concept of ESA-NASA multi-Mission Analysis Platform dedicated to the NISAR, GEDI and Biomass missions is proposed. This analysis platform will be a virtual open and collaborative environment. The goal is to bring together data centre (Earth Observation and non-Earth Observation data), computing resources and hosted processing, collaborative tools (processing tools, data mining tools, user tools, ...), concurrent design and test bench functions, application shops and market place functionalities, accounting tools to manage resource utilisation, communication tools (social network) and documentation.

The objective of this paper is to provide a better understanding of tomographic capabilities to estimate above ground biomass (AGB) in dense forested areas at P-band. The analysis is carried out on airborne data acquired over sites in French Guyana and in Gabon during the ESA campaigns TropiSAR and AfriSAR 2015, respectively. Over both sites, P-band tomography allows us to retrieve the vertical structure of the forest, to better characterize the ground and/or volume scattering mechanisms and to provide a unique solution for the AGB retrieval over the full range of biomass. The relationship between AGB and tomography data was found to be highly similar for forests across continents and sites: Paracou (French Guiana), Lope, Rabi and Mondah (Gabon). The developed metrics derived from the tomographic data have been found highly correlated to reference in situ AGB estimates (R2=0.85) and the root mean square error was 16% (for AGB ranging from 0 to 500 t/ha). These results have strong implications for the tomographic phase of the BIOMASS spaceborne mission.

Temporal decorrelation is a critical parameter for repeat-pass coherent radar processing, including many advanced techniques such as polarimetric SAR interferometry (PolInSAR) and SAR tomography (TomoSAR). Given the multifactorial and unpredictable causes of temporal decorrelation, statistical analysis of long time series of measurements from tower-based scatterometers is the most appropriate method for characterizing how rapidly a specific scene decorrelates. Based on the TropiScat experiment that occurred in a tropical dense forest in French Guiana, this letter proposes a comparative analysis between temporal decorrelation at P-band and at higher frequencies in the range of 800-1000 MHz (the low end of the L-band). This letter aims to support the design of future repeat-pass spaceborne missions and to offer a better understanding of the physics behind temporal decorrelation. Beyond the expected lower values that are found and quantified at the low L-band compared with the P-band, similar decorrelation patterns related to rainy and dry periods are emphasized in addition to the critical impacts of acquisition time during the day.

This paper deals with a ground experiment based on a P-band scatterometer that measured the evolution of the radar cross section (RCS) and coherence of a temperate tree in HV polarization, during four periods spread over nine months, over a cedar tree. Watering of the tree has limited influence in time on the RCS, i.e., limited to around 30 min, but impacts the coherence over a longer period of time. Analysis of the series shows that according to the season considered, clear daily cycles from 1 to 2 dB may appear on the coherence only (autumn) or on both coherence and RCS (spring), whereas in winter, they are absent on both results. It was analyzed in the literature that the variations in RCS are strongly correlated to the variations in the dielectric constant in trunks and branches. In addition, it was shown that the HV RCS presents seasonal trends with a yearly cycle of roughly 3 dB following similar trends reported for trunk moisture content time series.

This paper deals with AfriScat, a long-term tower-based scatterometer measurements experiment which will take place over the Ankasa forest in Ghana, an African tropical rain forest.

In this letter, the temporal coherence of tropical forest scattering at P-band is addressed by means of a ground-based experiment. The study is based on the TropiScat campaign in French Guiana, designed to support the Biomass mission, which will be the ESA 7th Earth Explorer mission. For Biomass, temporal coherence is a crucial parameter for coherent processing of polarimetric synthetic aperture radar (SAR) interferometry and SAR tomography in repeat-pass acquisitions. During the experiment, data were continuously collected for six months during both the rainy and dry seasons. For the rain-free days in both seasons, the coherence exhibits a daily cycle showing a high decorrelation during daytime, which is likely due to motion in the canopy. Up to a 20-day baseline, the coherence is much higher in the dry season than in the rainy season (> 0.8). From 20 to 40 days, it presents the same order of magnitude in both seasons [0.6, 0.7]. For larger temporal baselines, it becomes lower in the dry season. The results can be used to assess the long-term coherence of repeat-pass observations over a tropical forest. However, an extension of this study to several years and over other forest spots would be necessary to draw more general conclusions.

This paper deals with the overview of three ground based radar experiments: two scatterometers continuously measuring the backscattering of a temperate tree and of a tropical forest plot and a campaign imaging 10 forest plots with high resolution tomography. The results exhibited some common trends with the presence of diurnal cycles for the Radar Cross Section (RCS) and for the coherence in both temperate and tropical region. The comparison of scatterometers time series and the tomographic campaign showed a higher influence of the geometrical parameters compared with the biophysical parameters.

In this letter, we present the results from the ground-based European Space Agency campaign TropiScat, which is aimed at evaluating the temporal coherence at P-band in a tropical forest in all polarizations and at different heights within the vegetation layers. The TropiScat equipment has been operated since October 2011 at the Paracou field station, French Guiana, to continuously produce height-range images of the forest with a temporal sampling of 15 min. The forest temporal behavior can be then captured by analyzing the interferometric coherence between the images gathered at different times, considering time scales on the order of hours, days, and months. The results indicate that the vegetation is likely to undergo a significant motion during day hours due to wind and temperature changes, whereas it appears to be definitively more stable during night hours. This result appears to provide a very useful input to the Biomass Monitoring Mission for Carbon Assessment (BIOMASS), as it suggests that the performance over a tropical forest could be optimized by gathering acquisitions in early morning or night hours. The long-term temporal decorrelation has been then evaluated by considering dawn-dawn acquisitions to minimize the impact of wind gusts and by excluding rainy days in order to not confuse forest and system decorrelation. As a result, the temporal coherence at the ground level was found to stay high at about 0.8 at 27 days, whereas the temporal coherence at the canopy height was found to be about 0.8 at 4 days and about 0.65 at 27 days, indicating coherence sensitivity to height.

This paper deals with the temporal survey of the tropical forest electromagnetic scattering with a ground-based radar equipment. Installed on the top of a 55 m flux tower overlooking the Paracou forest in French Guiana, a dense primary tropical forest, the radar system uses a vertical antenna array and it is able to provide every 15 minutes P-band complex scattering matrix coefficients. The experiment has been successfully set up and it is operating since October 2011. The main goal of this campaign is to investigate the evolution of the backscattering coefficient and the temporal coherence of the tropical forest at different time scales range. Data are calibrated in relative and processed to take advantage of the largest number of independent looks. Three months of data are exploited in terms of polarimetric temporal coherence and backscattering coefficient in the rainy season and about two months in the dry period. The temporal coherence exhibits daily cycles during the consecutive dry days, whatever the period, and these cycles are perturbed by the presence of rain. Its overall time series appear clearly dependent on the period, dry or rainy, and also on the polarization. The backscattering coefficient time series exhibit also a daily cycle during consecutive dry days, very clearly in the dry period but less pronounced or absent during the rainy period. The backscattering coefficient presents an overall relatively high stability over the full period.

This paper describes a field campaign performed with a ground-based polarimetric tomographic imager designed to measure the vertical response of several forest plots in order to better understand the mechanisms contributing to the total radar response. The campaign took place in the Mende forest, an artificial forest of European Black Pines, in South of France. The objective is to perform a sensitivity study on the radar observables based on biophysical parameters. This paper presents a description of the experiment hardware and procedure, the results obtained for all sites, and a discussion of the results in the light of the ground truth. The results show vertical backscattered energy profiles as a function of tree density, forest growth, presence of undergrowth and ground slope. The evolution of the energy backscattered by the soil, the volume, and the whole scene is also displayed. These results have shown the interest of such a campaign to improve understanding of the distribution of radar mechanism along the vertical axis.

In this paper we present results from the ground-based ESA campaign TropiScat, aimed at evaluating the temporal coherence at P-band in a tropical forest in all polarizations and at different heights within the vegetation layers. The TropiScat equipment has been operated since October 2011 at the Paracou field station, French Guiana, to continuously produce height-range images of the forest below with a temporal sampling of 15 minutes. The forest temporal behaviour can then be captured by analyzing the interferometric coherence between images gathered at different times, considering time scales on the order of hours, days, and months. Temporal coherence at the ground level was found to be higher than 0.8 at 27 days in all polarimetric channels, whereas temporal coherence at canopy height was found to be about 0.8 at 4 days and about 0.65 at 27 days, witnessing coherence sensitivity to height.

In this paper we discuss the design concepts and preliminary results relating to the European Space Agency's ground-based campaign TropiScat, whose main goal is to evaluate temporal coherence at P-band in a tropical forest in quad-polarization, considering temporal lags ranging from hours to months and at different heights within the vegetation layer. The experiment has been successfully set up and operated since October 2011 at the Paracou field station, French Guiana, where the equipment was installed on top of the 55-m high Guyaflux Tower to illuminate the forest below. The system consists of a vector network analyzer connected to 20 antennas through a switchbox, which allows the use of any of them either as a transmitter or as a receiver. Vertical imaging and fully polarimetric capabilities are achieved by operating the 20 antennas in a multistatic fashion, resulting in an equivalent monostatic array consisting of 15 phase centers displaced along the vertical direction in each polarization. Such a design allows unambiguous imaging of the vegetation while yielding a minimum distance between nearby antennas on the order of 0.8 m, so as to minimize coupling effects. The equipment allows the gathering of signals with the tomographic array within a few minutes, resulting in the possibility to produce a tomographic image of the forest with a temporal sampling of 15 min. System calibration and validation was performed by employing a 2-m trihedral reflector and a rotating dihedral reflector. This allowed the evaluation of the system pulse response in all polarizations and also assessment of the extent of tower motions. As a result, tomographic images have been generated from 500 (P-band) to 900 MHz in all polarizations. Results from real data acquired in Fall 2011 confirm the feasibility of carrying out reliable coherence measurements for the whole duration of the campaign.

This paper describes a parallel model which goal is to carry out sensibility studies on simulated radar and optical remote sensing forest data. It presents how the model has been set up, with a forest growth model as an input of an optical hyperspectral model and a Synthetic Aperture Radar (SAR) model. The first results obtained by both models outputs are presented and a fusion of these output has been made and shows a complementarity of radar and optical data for biomass and moisture content inversions of forests.

This paper deals with the modelling of forest pine scattering at P Band. A growth model for forest description and an electromagnetic model for the scattering are used. First, canonical studies are carried out about single and multiple branches scattering behaviour with the goal of highlighting further results. Then, a sensitivity study is carried out on the influence of scene description parameters and system ones on the relationship between polarimetric intensity and biomass. It has been shown that the most influent parameters are branches moisture content and branches orientation, the other parameters playing an important role but limited to some observables.

In this paper we present preliminary results from the ground-based ESA campaign TropiScat, aimed at evaluating the temporal coherence at P-band in a tropical forest in quad-polarization and at different heights within the vegetation layer. The TropiScat equipment allows to gather the signal with a multistatic array within few minutes, resulting in the possibility to produce a tomographic image of the forest with a temporal sampling of 15 minutes. Concerning short term temporal decorrelation, the most relevant phenomenon is the coherence drop during daytime, due to the action of wind moving the forest canopy. This result appears to provide a very useful input concerning the BIOMASS mission, as it suggests that performance over tropical forest could be optimized by gathering acquisitions in the early morning or night hours. A diurnal motion along the vertical direction is observed to characterize the forest phase center. Studies are being carried out to evaluate whether this variation can be imputed to forest evapotranspiration phenomena.

This paper deals with a radar ground experiment dedicated to tropical forest backscattering at P band. With polarimetric and tomographic capabilities, this system is able to provide long-term radar data over a dense tropical forest. These data will be use to improve our comprehension of backscattering mechanisms and their evolution over long periods.

This paper deals with a ground experiment and its modelization, related to the future spaceborne BIOMASS mission for global forest biomass estimation.

Ground topography under vegetated area is liable to bring significant changes on radar backscattering and thereby on the associated standard retrieval algorithms dedicated to forest biomass. Within the framework of the ESA BIOMASS mission, this paper evinces the evolution of P-band polarimetric intensities with a tilted underlying ground. For that purpose, electromagnetic simulations have been achieved using our model MIPERS which theoretical specificities accounting for the topographic effects are herein described. Its originality lies mainly in the 3D characterization of the ground and the volume, as well as the coupling effects between both. This description is followed by a sensitivity analysis in order to further-on quantify the possible consequences on biomass retrieval, conducted with the two standard approaches, namely the P-HV intensity technique and the Pol-InSAR one assuming the RVoG model. This investigation have been also undertaken for a better understanding of experimental data, particularly with the BioSAR and the TropiSAR airborne campaigns over boreal and tropical forests.