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A spatially explicit Global Reef Island Database (GRID) that captures distribution, diversity and relative vulnerability of the world's low-lying reef islands

Low-lying coral reef islands harbour a distinct, yet highly threatened biological and cultural diversity that is increasingly exposed to climate change impacts. The combination of low elevation, small size, sensitivity to changes in boundary conditions (sea level, waves and currents, locally generated sediment supply) and at some locations high population densities, is why low-lying reef islands (LRIs) are considered among the most vulnerable environments on Earth to climate change. To date, their global distribution and influence of climatic, oceanographic, and geologic setting are only poorly documented or restricted to smaller scales. Here, I present the first detailed global analysis of LRIs utilising freely available global datasets to produce a global reef island database (GRID) and associated intrinsic and extrinsic characteristics that can be used within a coastal vulnerability index (CVI). All datasets used to create the GRID were released between 30 November 2015 and 3 August 2023, while the current version of the GRID database was completed in November 2024. When developing the GRID, LRIs are defined as landmasses <30 km² located on or within 1 km of coral reef and with an elevation of <16 m. Development of the GRID required: 1) the creation of a global shoreline vector file containing the geographic distribution of LRIs and 2) the development of a comprehensive global database of LRIs including eight intrinsic and ten extrinsic variables extracted from global datasets. Intrinsic variables include: 1) human populations, 2) island area, 3) island perimeter, 4) mean elevation, 5) island circularity/shape, 6) underlying reef type, 7) geographic isolation and 8) distance to the nearest neighbouring reef island. Extrinsic variables include: 1) mean water depth, 2) standard deviation of mean water depth, 3) mean annual significant wave height, 4) mean annual wave period, 5) mean spring tidal range, 6) relative tidal range, 7) wave-tide regime, 8) relative wave exposure, 9) relative tropical storm exposure and 10) year-2100 projected median sea level rise rate. The GRID was initially derived from version 2.1 of the UNEP-WCMC Global Island Database, a global shoreline vector file based on geometry data from Open Street Map® (OSM) and released in November 2015. The initial vector file was projected using the Mollweide projection, an equal-area pseudo cylindrical map projection chosen for its accurate derivation of area, especially in regions close to the equator, where most LRIs are located. The final GRID contains 34,404 individual LRIs distributed throughout tropical regions of the world's oceans, amassing a total land area of nearly 11,000 km² with approximately 60,740 km of shoreline and housing around 2.6 million people. While intrinsic variables are typically spatially homogenous, LRIs are generally highly spatially clustered throughout the GRID with respect to extrinsic variables. The spatial distribution of LRIs within the GRID was validated using: 1) published data and 2) quantitative accuracy assessments using satellite imagery. Spatial distributions of LRIs captured in the GRID are extremely consistent with those published in the literature (r² = 0.96) and those derived from independent analysis of satellite imagery (r² = 0.94). Finally, the GRID was used to develop an island vulnerability index (IVI) for each LRI on a scale of 0-1 with 0 representing no vulnerability and 1 representing maximum vulnerability. The GRID database is provided as a tab-delimited text file as well as ESRI shapefiles (points and polygons in WGS84 and Mollweide projection) and a comma-separated value file.

METOP GOME-2 - Sulfur Dioxide (SO2) - Global

Gridded Level 3 SO2 total column densities derived from the Metop/GOME-2-instruments. Volcanoes are the largest soures of SO2 in the atmosphere, depending on the erruption the Sulfurous compounds can be injected into stratosphere but in most cases it stays within the troposphere. Another important source is the coal combustion. Desulfurisation facilities within the power stations have reduced the sulfur emissions around the globe. In the stratosphere sulfur is a key component for building up aerosols, which reflect parts of the solar irradiation. The total SO2 column is retrieved from GOME solar back-scattered measurements in the ultraviolet wavelength region [using the DOAS method]. Depending on the plume SO2 can be a very strong absorber, because of that the ODAS retrieval might have some smaller issues, they can be reduced by choosing different wavelenght ranges depending on the signal. We apply three different fitting windows between 310 and 360nm. For the AMF, we assume a plumeheight of 6 km altitude. The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Three instruments operate on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in 2006, 2012, and 2018, respectively. GOME-2 measures a range of atmospheric trace constituents, with the emphasis on global ozone distribution. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF).

Collection of data sets for the Clouds over cOMPlEX environment - EarthCARE (COMPEX-EC) campaign, carried out in Kiruna in spring 2025

This data collection unites the individual data sets of the COMPEX-EC (Clouds over cOMPlEX environment - EarthCARE) campaign, carried out in Kiruna 2.-16.4.2025. COMPEX-EC has been designed as an EarthCARE validation campaign. For that purpose, Polar 5 (C-GAWI) has been equipped with instrumentation similar to the one operated on EarthCARE (W-band radar, lidar, radiometers, spectral imagers). Seven research flights (summing up to more than 30 flight hours) were conducted each of them underflying the EarthCARE satellite to validate its performance.

Entwicklung und Einsatz von GNSS-Fernerkundungsverfahren für die Erdbeobachtung

Die Radiookkultations-(RO)-Technik verwendet auf niedrigfliegenden (Low Earth Orbiter, LEO) Satelliten installierte Empfänger, um GPS/GNSS-Signale zu empfangen und Bogenmessungen der Erdatmosphäre und Ionosphäre durchzuführen. Aufgrund des Erfolgs der FormoSat-3/COSMIC- (Constellation Observing System for Meteorology, Ionosphere and Climate, FS3/COSMIC) -Mission, bestehend aus sechs Mikro-LEO-Satelliten, hat das gemeinsame US- und taiwanesische RO-Team beschlossen, eine COSMIC-Folgemission (sog. FS7/COSMIC2) voranzubringen. Die GNSS-RO-Nutzlast mit Namen Tri-G GNSS Radio-occultation System (TGRS) wird mehrkanalige GPS-, GLONASS- und Galileo-Satellitensignale empfangen und in der Lage sein, mehr als 10.000 RO-Beobachtungen täglich zu verfolgen, nachdem sowohl schwache als auch starke Bahnneigungs-Konstellationen vollständig abgedeckt worden sind. Man geht davon aus, die dichteren RO-Szintillationsbeobachtungen zu nutzen, um die Struktur der Erdatmosphäre und -ionosphäre genau zu analysieren und zu modellieren.Zusätzlich könnte die spezielle Art von GNSS-Multipfadverzögerungen, die von der Erdoberfläche reflektiert werden, verwendet werden, um Erdoberflächenumgebungsdaten, wie Ozeanhöhen und Seegang, zu erfassen. Die Empfindlichkeit dieser Signalcharakteristika gegenüber Ausbreitungseffekten ist für verschiedene Arten der Umweltfernerkundung geeignet. Dies hat einen Bedarf deutlich gemacht, geeignete Empfänger zu entwerfen und zu entwickeln, die reflektierte und gestreute GPS/GNSS-Signale in Echtzeit erfassen und verarbeiten können, um die Speicherung riesiger Mengen an Rohdaten zu vermeiden. Wir schlagen auch vor, das feldprogrammierbare Gatterfeld (Field Programmable Gate Array, FPGA) auf die GPS/GNSS-Reflektometrieinstrumente anzuwenden, wobei eine hohe Synchronität und ein größtmöglicher Nutzen aus den verfügbaren Hardware-Ressourcen zu erzielen wäre. Mittels Simulink/Matlab kann das FPGA auch komplexe Delay-Doppler-Map- (DDM) -Daten in Echtzeit durch Korrelation der phasengleichen und Quadraturkomponenten der Basisbandsignale berechnen. Diese Studie wird neue Ziele und Ergebnisse der GNSS-Fernerkundung der Atmosphäre, Ionosphäre, und der Ozeane sowie neue Möglichkeiten für die zukünftige FS7/COSMIC2-Mission aufzeigen.Das Projekt wird am Institut für Geodäsie und Geoinformationstechnik TU Berlin in enger Kooperation mit Wissenschaftlern des GFZ, Potsdam und des GPS Science and Application Research Center (GPSARC) der NCU, Taiwan durchgeführt.Die Ziele des Projekts lassen sich wie folgt zusammenfassen:(1) Nutzung von GPS/GNSS-RO-Atmosphärendaten und Entwicklung hochentwickelter Algorithmen für die untere Troposphäre und klimatologische Untersuchungen,(2) Erfassung und Überwachung der sporadischen E(Es)-Schicht, Szintillationen und damit zusammenhängender Effekte einschließlich vertikaler Kopplungen und(3) Entwicklung eines Echtzeit-FPGA-basierten GPS/GNSS-Reflektometers für Anwendungen im Bereich von Meereshöhen- und Seegangsmessungen.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Paderborn, Germany from 1985 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Schwerpunktprogramm (SPP) 1889: Regional Sea Level Change and Society (SeaLevel), Teilprojekt: Ableitung von Ozeanmassenverteilung und glazial-isostatischem Ausgleich aus Satellitengravimetrie und Satellitenaltimetrie (OMCG-2)

Massenbedingte Veränderungen des Meeresspiegels (MVM) sind eine wichtige Komponente des Meeresspiegelbudgets. Ist die MVM bekannt, ist es möglich aus der Kombination mit Daten der Satellitenaltimetrie Informationen zum Wärmehaushalt des Ozeans und damit zum globalen Energiehaushalt zu gewinnen. Neuere MVM Schätzungen basieren maßgeblich auf der Schwerefeld-Satellitenmission GRACE. Diese findet zunehmend auch Anwendung für regionale Studien. Allerdings bestehen zwischen publizierten MVM-Schätzungen aus praktisch identischen GRACE-Daten Diskrepanzen selbst auf der globalen Skale. Jüngere Studien veröffentlichen MVM-Trends zwischen 1,2 und 2,0 mm/a mit unrealistischen Fehlern und beanspruchen die Schließung des Meeresspiegelbudgets im Bereich 0,1-0,2 mm/a. Diese ungeklärten Diskrepanzen beeinträchtigen die Ermittlung gegenwärtiger Änderungen des Ozeanwärmegehalts aus Altimetrie, und in der Folge z. B. die Lokalisierung von Wärmesenken und Wärmetransport. Das Problem ist ebenfalls für das Verständnis und die Prädiktion regionaler Meeresspiegeländerungen in Südost-Asien besonders kritisch. Die zentrale Hypothese dieses Projekts, wie auch bei der ersten Phase des SPP, besteht darin, dass diese Diskrepanzen vor allem aus zwei Ursachen entstehen: (1) methodische Probleme in der Analyse der GRACE-Daten und (2) das ungelöste Problem, glazial-isostatische Ausgleichsbewegungen (GIA) aus den GRACE-Daten zu korrigieren. In der ersten Phase (OMCG-1) wurden zentrale methodische Unterschiede zwischen direkten und inversen MVM Schätzern untersucht. Darüber hinaus hat OMCG-1 das Verständnis über die wichtigsten Schritte zur Trennung des regionalen GIA-Effekts aus der Kombination satellitengeodätischer Verfahren verbessert. OMCG-1 wird den globalen Inversionsansatz weiterentwickeln und beginnen, die Ergebnisse der regionalen GIA-Separation in den globalen Rahmen einzubinden. Die zweite Phase (OMCG-2) soll a) verbesserte Methoden zur Definition von räumlichen Mustern aus Modellensembles untersuchen, b) die unabhängige Schätzung flacher sowie tiefer sterischer Komponenten untersuchen, c) den möglichen Zugewinn durch Einbindung von In-situ-Argo-Daten untersuchen, d) einen zeitreihenbasierten Parameterschätzungsansatz für die regionale Trennung von GIA und Eismassenänderungen implementieren, f) mögliche Biase in regionalen GIA-Schätzungen erklären sowie beheben unter Verwendung zusätzlicher GNSS-Beobachtungen und g) schließlich die Altimetrie über Eisschilden in die globale Inversion einbinden, um die Bestimmung von GIA zu verbessern. OMCG-2 wird physikalische Prozesse direkt quantifizieren, die zur Meeresspiegeländerung auf globaler und regionaler Skale beitragen. Außerdem werden Datensätze für die Modellierung für Projekte innerhalb und außerhalb des SPP bereitgestellt. Insbesondere unsere regionalisierten Daten für Nordeuropa und Südost-Asien werden helfen, Vorhersagen zu verbessern.

Nachtaufnahme Hamburg

Bei dieser Nachtaufnahme handelt es sich um ein Mosaik, welches aus zwei unterschiedlichen Datensätzen besteht. Datensatz 1 [Zentrum und Randgebiete] - Satellitenaufnahmen: Jilin-1 - Spektrale Auflösung: RGB - Aufnahmezeitraum: 12/21 – 01/22 - Quelle: Chang Guang Satellite Technology CO., LTD (CGSTL)/Veritas Imagery Services Ltd Datensatz 2 [vereinzelte Randgebiete] - Astronautenphotographie: NASA - Spektrale Auflösung: RGB - Aufnahmezeitraum: 03/22 - Quelle: Earth Science and Remote Sensing Unit, NASA Johnson Space Center; https://eol.jsc.nasa.gov/ Hinweise: Die Datensätze unterscheiden sich hinsichtlich ihrer geometrischen Auflösung. Die Datensätze sind spektral nicht zueinander kalibriert. Verwendung nur zu Visualisierungszwecken.

Sentinel-5P TROPOMI Surface Nitrogendioxide (NO2), Level 4 – Regional (Germany and neighboring countries)

The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product displays the Nitrogen Dioxide (NO2) near surface concentration for Germany and neighboring countries as derived from the POLYPHEMUS/DLR air quality model. Surface NO2 is mainly generated by anthropogenic sources, e.g. transport and industry. POLYPHEMUS/DLR is a state-of-the-art air quality model taking into consideration - meteorological conditions, - photochemistry, - anthropogenic and natural (biogenic) emissions, - TROPOMI NO2 observations for data assimilation. This Level 4 air quality product (surface NO2 at 15:00 UTC) is based on innovative algorithms, processors, data assimilation schemes and operational processing and dissemination chain developed in the framework of the INPULS project. The DLR project INPULS develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.

Sentinel-5P TROPOMI - Aerosol Optical Depth (AOD), Level 3 - Global

Aerosol optical depth (AOD) as derived from TROPOMI observations. AOD describes the attenuation of the transmitted radiant power by the absence of aerosols. Attenuation can be caused by absorption and/or scattering. AOD is the primary parameter to evaluate the impact of aerosols on weather and climate. Daily AOD observations are binned onto a regular latitude-longitude grid. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.

Sentinel-5P TROPOMI - Aerosol Single-Scattering Albedo (ASSA), Level 3 - Global

Aerosol single-scattering albedo (ASSA) as derived from TROPOMI observations. ASSA is a measure of how much light is scattered by aerosols compared to how much is absorbed. It is important for understanding the impact of aerosols on climate and radiative forcing. ASSA is unitless; a value of unity implies that extinction is completely due to scattering; conversely, a single-scattering albedo of zero implies that extinction is completely due to absorption. Daily ASSA observations are binned onto a regular latitude-longitude grid. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.

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