This article presents the burned area (BA) product of the Copernicus Climate Change Service (C3S) of the European Commission. This product, named C3SBA10, is based on the adaptation to Sentinel-3 OLCI images of a BA algorithm developed within the Fire Climate Change Initiative (FireCCI) project, which used MODIS data. We first reviewed the adaptation process and then analysed the results of both products for common years (2017–2019). Comparisons were performed using four different grid sizes (0.05°, 0.10°, 0.25°, and 0.50°). Annual correlations between the two products ranged from 0.94 to 0.99. Global BA estimates were found to be more similar when the two Sentinel-3 satellites were active (2019), as the temporal resolution was closer to that of the MODIS sensor. Global validation was performed using reference data derived from Landsat-8 images, following a stratified random sampling design. The C3SBA10 showed commission errors between 16 and 21% and omission errors from 48 to 50%, similar to those found in the FireCCI product. The temporal reporting accuracy was also validated using 19 million active fires. In total, 87% of the detections were made within 10 days after the fire by both products. The high consistency between both products ensures global BA data provision from 2001 to the present. The datasets are freely available through the Copernicus Climate Data Store (CDS) repository.

This article describes the principles used to generate global gap-free Leaf Area Index (LAI) time series from 2002–2012, based on MERIS (MEdium Resolution Imaging Spectrometer) full-resolution Level1B data. It is produced as a series of 10-day composites in geographic projection at 300-m spatial resolution. The processing chain comprises geometric correction, radiometric correction, pixel identification, LAI calculation with the BEAM (Basic ERS & Envisat (A)ATSR and MERIS Toolbox) MERIS vegetation processor, re-projection to a global grid and temporal aggregation selecting the measurement closest to the mean value. After the LAI pre-processing, we applied time series analysis to fill data gaps and to filter outliers using the technique of harmonic analysis (HA) in combination with mean annual and multiannual phenological data. Data gaps are caused by clouds, sensor limitations due to the solar zenith angle (<10°), topography and intermittent data reception. We applied our technique for the whole period of observation (July 2002–March 2012). Validation, carried out with VALERI (Validation of Land European Remote Sensing Instruments) and BigFoot data, revealed a high degree (R² : 0.88) of agreement on a global scale.

Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.

The Ocean Colour Thematic Assembly Centre (OCTAC) of the Copernicus Marine Service delivers state-of-the-art Ocean Colour core products for both global oceans and European seas, derived from multiple satellite missions. Since 2015, the OCTAC has provided global and regional high-level merged products that offer value-added information not directly available from space agencies. This is achieved by integrating observations from various missions, resulting in homogenized, inter-calibrated datasets with broader spatial coverage than single-sensor data streams. OCTAC enhanced continuously the basin-level accuracy of essential ocean variables (EOVs) across the global ocean and European regional seas, including the Atlantic, Arctic, Baltic, Mediterranean, and Black seas. From 2019 onwards, new EOVs have been introduced, focusing on phytoplankton functional groups, community structure, and primary production. This paper provides an overview of the evolution of the OCTAC catalogue from 2015 to date, evaluates the accuracy of global and regional products, and outlines plans for future product development.

Urbanization is among the most relevant global trends that affects climate, environment, as well as health and socio-economic development of a majority of the global population. As such, it poses a major challenge for the current urban population and the well-being of the next generation. To understand how to take advantage of opportunities and properly mitigate to the negative impacts of this change, we need precise and up-to-date information of the urban areas. The Urban Thematic Exploitation Platform (UrbanTEP) is a collaborative system, which focuses on the processing of earth observation (EO) data and delivering multi-source information on trans-sectoral urban challenges. The U-TEP is developed to provide end-to-end and ready-to-use solutions for a broad spectrum of users (service providers, experts and non-experts) to extract unique information/ indicators required for urban management and sustainability. Key components of the system are an open, web-based portal connected to distributed high-level computing infrastructures and providing key functionalities for i) high-performance data access and processing, ii) modular and generic state-of-the art pre-processing, analysis, and visualization, iii) customized development and sharing of algorithms, products and services, and iv) networking and communication. The service and product portfolio provides access to the archives of Copernicus and Landsat missions, Datacube technology, DIAS processing environments, as well as premium products like the World Settlement Footprint (WSF). External service providers, as well as researchers can make use of on-demand processing of new data products and the possibility of developing and deploying new processors. The onboarding of service providers, developers and researchers is supported by the Network of Resources program of the European Space Agency (ESA) and the OCRE initiative of the European Commission. In order to provide end-to-end solutions, the VISAT tool on UrbanTEP allows analyzing and visualizing project-related geospatial content and to develop storylines to enhance the transport of research output to customers and stakeholders effectively. Multiple visualizations (scopes) are already predefined. One available scope exemplary illustrates the exploitation of the WSF-Evolution dataset by analyzing the settlement and population development for South-East Asian countries from 1985 to 2015 in the context of the Sustainable Development Goal (SDG) 11.3.1 indicator. Other open scopes focus on urban green, functional urban areas, land-use and urban heat island modelling (e.g.).