About – Panorama

Enhancing Earth Observation

Multi-sensor synergies and AI-driven insight for a resilient, sustainable Europe

Introducing PANORAMA

By harnessing data from next-generation satellite constellations and advancing AI-powered analysis, PANORAMA enables better decision-making in key domains such as climate action, disaster risk reduction, and sustainable development. The project directly supports the European Green Deal and contributes to modernizing environmental and climate services across Europe.

Our approach

At the heart of PANORAMA is the integration of multi-sensor data from the Copernicus Sentinels, MTG, and EPS-SG constellations. The project fuses atmospheric, radiative, and surface-level data using advanced techniques like data assimilation, machine learning, and top-down emissions estimation. These enhanced EO products are tested in real-world pilot applications addressing air quality, weather extremes, floods, and energy forecasting.

Our vision

PANORAMA envisions a future where Earth Observation is seamlessly embedded in European services — from climate and air quality monitoring to energy and emergency response. By making pre-operational tools available via Copernicus DIAS platforms, the project aims to empower researchers, policy makers, and service developers with robust, interoperable, and user-ready applications.

Planned developments

PANORAMA aims to multiply the value of observations by the next generation of Copernicus Sentinels and EUMETSAT MTG and EPS-SG satellite by realising multi-sensor synergies and to provide advanced aerosol products

PANORAMA plans to demonstrate the improved applications on atmospheric composition and NWP (e.g., motion estimation of aerosols & clouds, fast radiative transfer calculations, top-down emission estimations through ML/AI, data assimilation, and new physical parameterisations).

PANORAMA products and applications will be tested and fine-tuned in 6 pilot demonstrators to assess the impact of the new EO data on the representation and prediction of extreme weather, floods, energy, and air pollution.

Multi-Platform Synergy developments - Data Fusions

Visible + TIR observations (3MI + IASI): Inversion of 3MI observations (with very high information about aerosol properties in the visible), together with IASI observations (with high sensitivity to coarse particles properties) to provide strongly enhanced aerosol products for a wide range of aerosol particle sizes, from very fine to very coarse, with high significance for desert dust research.

GEO + LEO (FCI + 3MI + TROPOMI+S-5): Inversion of GEO (with high temporal coverage) together with LEO observations (with high sensitivity to detailed aerosol properties), to provide strongly improved products, with detailed aerosol information at high temporal coverage.

UV + spectral + polarization + TIR (TROPOMI +S-5+ 3MI + IASI): The observations in the UV, the spectral observations in the Oxygen band, the polarization observations in the visible, and the observations in the TIR, have substantial sensitivity to the vertical variability of the aerosols. Therefore, their synergy is expected to provide highly reliable estimations of Aerosol Lyer Hight (ALH) and other parameters characterising aerosol vertical variability.

Illustration of the extended set of atmosphere and surface products from planned deep synergy processing of MTG, EPS-SG, S-3 and -5P platforms.

Methodology

combining non-coincident satellite observations using the multi-pixel concept is another novelty to be used in the PANORAMA project.

The multi-pixel GRASP concept implements a statistically optimised retrieval simultaneously for a large group of pixels forming spatial-temporal data segments (Dubovik et al., 2011; 2021). This feature brings additional possibilities for improving the accuracy of retrievals by using known constraints on the inter-pixel variability in space and time of aerosol and surface reflectance parameters. This approach is quite suitable for handling the combination of diverse remote sensing measurements and performing their synergetic retrieval, and will be the core concept in realising deep synergy processing in PANORAMA. In the multi-pixel concept the inverted group of pixels includes observations from different locations and times.

Once a group of different observations is inverted together even if they are not fully co-incident the a priori information about known limitations on time and/or in space variability of the retrieved parameters can be applied rather efficiently. In this respect, the fact that the variabilities of different parameters are very different can be very beneficial once the multi-pixel concept is used. For example, the temporal variability of land surface reflectance is very limited while aerosol properties do not change much within only hours, showtime days. On the other hand, the aerosol properties do not change strongly within kilometres, while the land surface reflectance can be highly spatially heterogeneous, with this concept to be very helpful for synergistic processing of observations from MTG, EPS-SG and Sentinel satellite platforms.

The multi-pixel concept for multi-instrument synergy retrieval has been already realised and tested by studies of Litvinov et al. (2025): a synergetic multi-instrument retrieval approach was developed for the aerosol and surface properties using combinations of S-3A,B, S-5p and HIMAWARI instruments and it was demonstrated that the combined retrieval brings the improvement in retrieved properties from every sensor. For example, all parameters, including AE and SSA, were retrieved from OLCI and HIMAWARI observations with reasonable accuracy, while each sensor separately cannot provide these parameters.

Illustration of the GRASP multi-pixel retrieval concept

Partners

Centre National de la Recherche Scientifique (CNRS) - Université de Lille

The Centre National de la Recherche Scientifique (CNRS) is France’s largest public research organization. As PANORAMA’s coordinator, CNRS leads project management, contributes to synergy product development, supports pilot studies, and validates results via ACTRIS data. It also drives dissemination through its extensive atmospheric science and EO research networks.

Université de Lille is a leading French public research university. Through its Laboratoire d’Optique Atmosphérique (LOA), where its main areas of research lie on atmospheric radiative transfer, aerosol and cloud remote sensing and climate, supports PANORAMA by developing synergy retrievals using visible and TIR (IASI) data, and by validating them through AERONET and ACTRIS observations as part of its atmospheric remote sensing expertise.

Generalized Retrieval of Atmosphere and Surface Properties En Abrege (GRASP)

GRASP SAS develops algorithms for atmosphere and surface analysis from EO data and supports the GRASP open-source platform. In PANORAMA, it leads synergy product development, supports pilots, contributes to validation using AERONET/ACTRIS data, and promotes results to scientific, institutional, and business communities through its global partnerships.

Universite Paris Xii Val De Marne (UPEC)

LISA, part of Université Paris-Est Créteil (UPEC), is a leading French laboratory specializing in atmospheric composition and pollution monitoring. In PANORAMA, it leads the synergy of TIR spectrometers and polarimetric sensors, contributing to advanced multi-instrument aerosol retrievals using data from IASI, POLDER, and upcoming EO missions.

Physikalisch-Meteorologisches Observatorium Davos / World Radiation Center

PMOD/WRC is Switzerland’s national reference institute for solar radiation calibration and atmospheric observations. In PANORAMA, it contributes to product validation and demonstrates improvements in solar energy forecasting. As a key player in global calibration networks and EuroGEO energy initiatives, PMOD/WRC bridges scientific excellence with user-driven applications.

National Observatory of Athens (NOA)

The National Observatory of Athens (NOA) is Greece’s oldest research institution, specializing in atmospheric remote sensing and modeling. In PANORAMA, NOA leads the pilot phase, validates EO products using LIVAS and ACTRIS data, and leverages its active role in EuroGEO and Destination Earth to promote broader adoption.

EDGE in Earth Observation Sciences

EDGE is a specialized Earth Observation company based in Greece, delivering innovative services across climate, disaster management, and energy. In PANORAMA, EDGE contributes technical expertise in data analysis and EO integration, while leading the project’s dissemination, communication, and exploitation strategy to ensure impactful outreach and engagement across key stakeholder groups.

Institutul National De Cercetare Dezvoltare Pentru Optoelectronica Inoe 2000 (INOE)

The National Institute for R&D in Optoelectronics (INOE) is a Romanian research institute with expertise in atmospheric remote sensing and EO applications. In PANORAMA, INOE leads product validation using ACTRIS and campaign data, supports product refinement, contributes to pilots, and promotes outcomes across in situ and aerosol monitoring networks.