Noticeable within the Mexican Caribbean is the Arrecife de Puerto Morelos National Park (APMNP), a marine protected area established as an essential component for managing and protecting coral reefs. In June 2019, we conducted a survey in eight shallow reef sites of the APMNP with the purpose of applying a coral reef assessment method, based on biological indicators of the condition of both benthos and fish communities. In this paper we present tables with data of biological and ecological variables such as: benthos coverage, species composition and abundance of corals, abundance of urchins and coral recruits, bleaching, coral diseases and coral mortality percent, reef relief, and composition and abundance of key commercial and herbivorous fish species. The research article related to these databases was published in the journal Diversity with the title: Puerto Morelos coral reefs, current state and their classification by a scoring system.

Time senes of vegetation index data provide useful information of vegetation activity. These curves can be used for retrieving key phenological stages such as the day of season onset, peak, and end. These parameters allow for better understanding the landscape and, if conducted for several years, its natural variability or human-induced change. This study employs eight years of MODIS vegetation index time series to retrieve above-mentioned phenological parameters. It was found that the EVI shows earlier phenological dates than the NDVI, possibly linked to its susceptibility to subtle changes. A spatial analysis for ecosystems indicated the shifted phasing of the Mediterranean California region with winter ram and suggested a general North-South gradient with increasing growing season length. Only small differences were found for different curve-fitting algorithms if the same parameters were used. However, user-defined parameter changes have a high impact on the retrieval of phenological dates.

Coastal zones around the world are vital for our environment, economy, and communities, highlighting the urgent need to use innovative technologies to address significant environmental challenges. Digital twins, a leading technology in environmental modeling and simulation, offer great potential for improving our understanding and management of these crucial areas, especially blue carbon ecosystems, by using advanced hydrodynamic and morphodynamic modeling.Coastal areas, which embody a diverse range of ecosystems such as mangroves, seagrasses, and salt marshes, generally referred to as blue carbon ecosystems, provide a wealth of ecosystem services and support rich biodiversity. These ecosystems are just as important for the environment as they are for the economy, supporting essential industries and providing livelihoods globally. However, climate change and harmful human activities pose serious risks to coastal zones, making it crucial to develop informed management strategies.Blue carbon habitats are vital to carbon sequestration efforts, playing a critical role in climate regulation. Despite this, they face increasing threats from sea-level rise, pollution, overfishing, and habitat destruction, with alarming loss rates observed in mangroves and seagrasses, which results in the release of stored carbon and degradation of key ecosystem services.To address these challenges, the COASTS (Coastal Observation Advances leveraging Space Technology Services) international initiative, proposes an innovative solution, integrating advanced Earth Observation data with state-of-the-art modeling and monitoring techniques. This integrated approach enables the creation of comprehensive digital twins, simulating coastal processes and blue carbon ecosystem dynamics. By leveraging the capabilities of the Copernicus Marine Service, the initiative combines advanced technological resources with actionable environmental insights.The COASTS project aims to develop a digital twin for coastal ecosystem resilience and blue carbon optimization, enabling stakeholders to develop effective management strategies specifically designed for these habitats. This effort will evaluate both the erosion protection abilities of coastal ecosystems and their ecosystem services, such as carbon sequestration ability. Through the integration of high-resolution EO data, the project will map spatial-temporal dynamics within coastal zones, establishing critical baseline information for conservation and restoration efforts.The project's pilot sites in Germany, Jersey, and the Maldives will provide testbeds for the system, facilitating its eventual application and scalability to other regions. The collaboration with stakeholders enriches the project's collaborative foundation, ensuring it meets the needs and acceptance of end users.

The accelerating evolution of remote sensing technologies offers unprecedented opportunities to assess biodiversity across ecosystem structure, composition, and function. Within this landscape, our BlueMAP (Blue Carbon Market Acceleration Potential by EnMAP) project demonstrates how advanced multi-sensor Earth Observation combining hyperspectral EnMAP data with multispectral Sentinel-2 and PlanetScope imagery can substantially enhance biodiversity monitoring in dynamic coastal ecosystems such as mangroves and seagrass meadows. These habitats are globally significant for biodiversity and carbon sequestration, yet remain challenging to monitor due to their fine-scale spatial heterogeneity, water-column effects, and rapid ecological dynamics.BlueMAP develops and tests new remote-sensing workflows that translate multi-sensor EO-derived information into biologically meaningful metrics. Through hyperspectral unmixing, data fusion, and machine-learning methods, the project improves discrimination of benthic and wetland habitat classes, enabling enhanced mapping of ecosystem extent, structural traits (e.g., canopy density, seagrass cover), and indicators of ecosystem condition. The integration of EnMAP’s hyperspectral richness with the temporal frequency of Sentinel-2 and PlanetScope enables identification of subtle ecological patterns such as degradation signals in mangroves or annual density shifts in seagrass beds supporting more accurate derivation of biodiversity-relevant variables including ecosystem structure, health, and functional proxies.A key innovation of BlueMAP is its direct alignment with the needs of emerging blue-carbon markets, providing robust, transparent, and scalable ecosystem monitoring products that reduce uncertainty in carbon credit generation and verification. By integrating hyperspectral EnMAP data with high-resolution multisensor imagery, BlueMAP delivers consistent measurements of ecosystem extent, condition, and above-ground biomass, critical inputs for Tier-2 carbon stock estimation and MRV workflows. This EO-based approach improves the ability to separate intact from degraded habitats, monitor ecological change, and quantify biomass dynamics. In doing so, it tackles key challenges in biodiversity remote sensing, such as ensuring consistency across sensors, reducing uncertainties, and turning satellite derived information into ecosystem metrics that are ready for policy use and blue-carbon markets.BlueMAP illustrates how next-generation EO missions and multi-sensor integration can strengthen biodiversity monitoring frameworks that underpin credible blue-carbon markets and emerging nature-based climate finance, while also aligning with broader policy agendas such as the Kunming–Montreal Global Biodiversity Framework and the SDGs.

Coastal zones host some of the planet’s most biodiverse and productive ecosystems, including mangroves, seagrasses, and salt marshes, “blue carbon” habitats that provide essential ecosystem services such as shoreline protection, fisheries support, and substantial carbon sequestration. Yet these ecosystems are under increasing pressure from climate change, sea-level rise, pollution, and habitat degradation. Effective biodiversity monitoring and management therefore require approaches that integrate ecological processes with the complex physical dynamics of coastal environments.The COASTS (Coastal Observation Advances Leveraging Space Technology Services) project addresses this challenge by combining multi-scale Earth observation (EO) data, advanced modelling, and process-based morphodynamic simulations to map, model, and monitor coastal biodiversity and blue carbon ecosystem dynamics. COASTS brings together European partners to close knowledge gaps through the integration of EO, ecological surveying, and digital analysis tools. Working closely with local stakeholders at three pilot sites in Germany, Jersey/Chausey, and the Maldives, the project co-designs fit-for-purpose solutions tailored to regional management needs.A central goal of COASTS is the development of a downstream service that leverages Copernicus Marine data and other EO initiatives to provide decision-ready environmental information. This includes spatial-temporal mapping of blue carbon habitats, assessments of ecosystem services, and quantification of coastal resilience functions such as erosion protection. The project further examines how EO-derived indicators can support identify priority areas for restoration and conservation.A key component of COASTS is its nested hydro-morphodynamic modelling framework, which captures coastal processes across scales relevant to biodiversity and ecosystem functioning. The workflow downscales Copernicus Marine global or regional data to local, high-resolution simulations through a sequence of nested models. Delft3D Flexible Mesh (FM) provides detailed hydrodynamics and wave–flow interactions, incorporating bathymetry, seabed roughness, wind forcing and sediment transport. These outputs drive site-specific XBeach models that resolve nearshore morphodynamics, sediment exchange and storm-driven change at meter-scale resolution. Using satellite-derived bathymetry, seabed classification, ERA5 winds and CMEMS ocean products, this modelling chain reconstructs past coastal behaviour and generates future scenarios relevant for habitat stability, erosion risk and blue carbon ecosystem resilience.The project will deliver a web-based decision-support tool enabling stakeholders to visualise, analyse, and report on coastal ecosystem dynamics.