Der CODE-DE-Projekt Marktplatz bietet einen Überblick über alle Aktivitäten von CODE-DE. Hauptkategorien sind DATENSÄTZE, DIENSTE, PROJEKTE, WERKZEUGE, and PROZESSOREN.

Technisch gesehen ist der Markt nur eine Zusammenfassung der Inhalte aus dem CODE-DE-Portal, die vom Content Management System (CMS) verwaltet werden. Die Übersicht soll dem Leser schnell und einfach alle relevanten CODE-DE-Komponenten zur Verfügung stellen. Die einzelnen Komponenten bieten eigene Web-basierte Management-Schnittstellen. Der Service-Marktplace verlinkt zu diesen. Da Single Sign-On verwendet wird, kann der Benutzer seine Aufgaben ohne Unterbrechung fortsetzen.

Zusätzlich zu den Daten, die auf der CODE-DE-Plattform zur Verfügung stehen, liefern die Geodateninfrastruktur Deutschland (GDI-DE) und das Geoportal.DE weitere relevante Geodaten. Weitere Informationen zu Copernicus, den Sentinels, Erdbeobachtungsmissionen und -sensoren und verwandte Themen gibt es auf Copernicus.DE.

Zukünftig werden auch Projekte, die im Rahmen von CODE-DE umgesetzt werden sowie Prozessoren, die CODE-DE als Elemente neuer Services zur Verfügung stellt, auf dem Marktplatz sichtbar sein. Momentan sind die entsprechende Rubriken noch nicht gefüllt, es erscheint die Meldung: Diese Suche lieferte keine Ergebnisse.


Der Service Marketplace beinhaltet einen JavaScript-basierten CSW-Client, der es ermöglicht CSW-Anfragen an den CODE-DE Discovery Service zu stellen. Der Discovery Service gibt INSPIRE-konforme Metadaten-Einträge zu Produkten der kollaborativen Plattform sowie von Drittanbieter-Missionen zurück.

The Soil Composite Mapping Processor (SCMaP) is a new approach designed to make use of per-pixel compositing to overcome the issue of limited soil exposure due to vegetation. Three primary product levels are generated that will allow for a long term assessment and distribution of soils that include the distribution of exposed soils, a statistical information related to soil use and intensity and the generation of exposed soil reflectance image composites. The resulting composite maps provide useful value-added information on soils with the exposed soil reflectance composites showing high spatial coverage that correlate well with existing soil maps and the underlying geological structural regions.

The Global Urban Footprint® (GUF®) dataset is based on the radar (SAR) satellite imagery of the German satellites TerraSAR-X and TanDEM-X. By creating the GUF database, scientists at the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR) have succeeded in using a newly developed method to generate a global raster map of the world’s built-up pattern in a so far unprecedented spatial resolution of about 12m per raster cell.

Using a fully automated processing system, a global coverage of more than 180,000 very high resolution SAR images (3m ground resolution) has been analyzed acquired between 2010 and 2013. Thereby, the backscatter amplitudes of the SAR data have been used in combination with derived textural information to delineate human settlements in a highly automated, complex decision-making process. The evaluation procedure based mainly on radar signals detects the characteristic vertical structures of human habitations – primarily built-up areas. In addition, auxiliary data such as digital elevation models have been included to improve the classification process. In total, over 20 million datasets were processed with a combined volume of about 320 terabytes. The final global maps show three coverage categories (e. g. in a B&W representation): Built-up areas (vertical structures only) in black, non-built-up surfaces in white, areas of no coverage by TSX/TDX satellites (NoData) as most parts of the oceans in grey.

The final product has been optimized for fast online access through web services by merging the 5° x 5° GUF tiles into a single global mosaic. Furthermore reduced resolution overviews have been generated with an interpolation algorithm, that computes the average value of all contribution pixels. The global mosaic uses PackBits compression to reduce file size.

(GUF® and Global Urban Footprint® are protected as trademarks.)

Datum der letzten Änderung
27-02-2019 01:35:31

The Global Urban Footprint® (GUF®) dataset is based on the radar (SAR) satellite imagery of the German satellites TerraSAR-X and TanDEM-X. Using a fully automated processing system, the so-called Urban Footprint Processor, a global coverage of more than 180,000 very high resolution SAR images (3m ground resolution) has been analyzed, mainly acquired between 2010 and 2013. Thereby, the backscatter amplitudes of the SAR data have been used in combination with derived textural information to delineate human settlements in a highly automated, complex decision-making process. In addition, auxiliary data such as digital elevation models have been included to improve the classification process. The data collection of satellite imagery was performed mainly between 2011 and 2012 (93 %), with single scenes with more recent acquisition dates (of 2013 / 2014) used to fill data gaps.
For more details see:
Esch, T., Marconcini, M., Felbier, A., Roth, A., Heldens, W., Huber, M., Schwinger, M., Taubenböck, H., Müller, A., Dech, S. (2013) Urban Footprint Processor – Fully Automated Processing Chain Generating Settlement Masks from Global Data of the TanDEM-X Mission. IEEE Geoscience and Remote Sensing Letters, Vol. 10, No. 6, November 2013. Pp. 1617-1621. ISSN 1545-598X, DOI 10.1109/LGRS.2013.2272953 (see: )

MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment (from
On January 16, 2001 the antenna was installed on the roof of the DLR German Remote Sensing Data Center building in Oberpfaffenhofen and put into operation for MODIS reception (see for more details).
This mosaic has been generated from TERRA and AQUA products between 30 Sept. to 03 Oct. 2011

Datum der letzten Änderung
03-05-2019 09:18:27

Please refer to for more details. The MODIS data used in this product were obtained through the online Data Pool at the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota (

The RapidEye RESA Germany Mosaic provides a nearly cloud-free view of the country’s geography, natural resources, and infrastructure. It is composed of 374,240 sqkm of multi-spectral RapidEye imagery, acquired between April and October 2015. The product is being provided in the framework of the RapidEye Science Archive (RESA) agreement.

Co-funded by the German Federal Government, the fleet of RapidEye satellites were launched from the Baikonur cosmodrome in Kazakhstan in 2008. The satellites are now owned by Planet Labs, Inc. The RapidEye Earth observation system comprises five satellites equipped with high-resolution optical sensors. With a spatial resolution of 6.5 m the 5-band instruments operate in the visible and near-infrared portions of the electromagnetic spectrum. With its high repetition rate the RapidEye constellation can image each point on the Earth’s at least once per day.

Datum der letzten Änderung
09-04-2018 08:37:19

RapidEye Mosaic products consist of multiple RapidEye image takes that have been orthorectified
and radiometrically color balanced to a uniform appearance that are then assembled to create a single,
seamless large area image. For details see:


Zu diesen Diensten gehören Suche und Zugriff (siehe auch Datensätze), Bildersuche, Download und Verarbeitung (ab Mitte 2017). Bewerbungsprojekte

The Copernicus Services Portfolios database is a user-friendly tool, designed to facilitate the understanding and ease the access to Copernicus products and services for intermediate/final users and research communities.

The Copernicus Services Portfolios database offers three different Search Functionalities: –Search by Keywords, based on users’ needs, –Search by Alphabetical Index, based on Copernicus Services Portfolios, –Search by Theme, based on Copernicus domains of application. Also, support functionalities help enhancing the user’s experience, such as: –Subscription, for top-down communication, –Feedback and Queries, –Print-Out and Download in PDF format, –Analytics and Statistics, –Automated daily updates.

Datum der letzten Änderung
08-05-2018 09:27:01

EY, on behalf of European Union

Copernicus is a European system for monitoring the Earth. Data is collected by different sources, including Earth observation satellites and in-situ sensors. The data is processed and provides reliable and up-to-date information about six thematic areas: land, marine, atmosphere, climate change, emergency management and security. The land theme is divided into four main components:

The Global Land Service provides a series of bio-geophysical products on the status and evolution of the land surface at global scale at mid and low spatial resolution. The products are used to monitor the vegetation, the water cycle and the energy budget.

The pan-European component provides information about the land cover and land use (LC/LU), land cover and land use changes and land cover characteristics. The latter includes information about imperviousness, forests, natural grasslands, wetlands, and permanent water bodies.

The local component focuses on different hotspots, i.e. areas that are prone to specific environmental challenges and problems. This includes detailed LC/LU information for the larger EU cities (Urban Atlas), riparian zones along European river networks and NATURA 2000 sites. It will also include maps of coastal areas.

All of the Copernicus services need access to in-situ data in order to ensure an efficient and effective use of Copernicus space-borne data. Next to data provided by participating countries, Earth observation from space also yields pan-European reference datasets, such as a Digital Elevation Model.

The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas.

The observations and forecasts produced by the service support all marine applications. For instance, the provision of data on currents, winds and sea ice help to improve ship routing services, offshore operations or search and rescue operations, thus contributing to marine safety.
The service also contributes to the protection and the sustainable management of living marine resources in particular for aquaculture, fishery research or regional fishery organisations.
Physical and marine biogeochemical components are useful for water quality monitoring and pollution control. Sea level rise helps to assess coastal erosion. Sea surface temperature is one of the primary physical impacts of climate change and has direct consequences on marine ecosystems.

As a result of this, the service supports a wide range of coastal and marine environment applications. Many of the data delivered by the service (e.g. temperature, salinity, sea level, currents, wind and sea ice) also play a crucial role in the domain of weather, climate and seasonal forecasting.

Some of today’s most important environmental concerns relate to the composition of the atmosphere. The increasing concentration of the greenhouse gases and the cooling effect of aerosol are prominent drivers of a changing climate, but the extent of their impact is often still uncertain.

At the Earth’s surface, aerosols, ozone and other reactive gases such as nitrogen dioxide determine the quality of the air around us, affecting human health and life expectancy, the health of ecosystems and the fabric of the built environment. Ozone distributions in the stratosphere influence the amount of ultraviolet radiation reaching the surface. Dust, sand, smoke and volcanic aerosols affect the safe operation of transport systems and the availability of power from solar generation, the formation of clouds and rainfall, and the remote sensing by satellite of land, ocean and atmosphere.

To address these environmental concerns there is a need for data and processed information. The Copernicus Atmosphere Monitoring Service (CAMS) has been developed to meet these needs, aiming at supporting policymakers, business and citizens with enhanced atmospheric environmental information.


Die Anwendungsprojekte werden von der CODE-DE Gesamtleitung genehmigt, um die Möglichkeiten der Infrastruktur zu demonstrieren. Die Projekte werden von BMVI unter besonderen Bedingungen unterstützt und zeitlich begrenzt.

BigDataCube in CODE-DE

Flexible, skalierbare Nutzerdienste für massive raum-zeitliche Datenwürfel

Mit dem Vorhaben BigDataCube ( wird das innovative Paradigma der "Datenwürfel" – also analysefertige raum-zeitliche Rasterdaten – auf CODE-DE etabliert. Damit können Anwender jede Anfrage, jederzeit und ohne Programmierung auf den Sentinel-1 und Sentinel-2 Datenwürfeln ausführen lassen. Durch den konsequenten Einsatz der OGC-Standards bleibt der Anwender in der Komfortzone seiner eigenen Clients und kann aus einem breiten Spektrum wählen, unter anderem:

Karten-Navigation: OpenLayers, Leaflet, ...
Virtelle Globen: NASA WorldWind, Cesium, ...
Web GIS: QGIS, ArcGIS, ...
für komplexe Analyse: GDAL, R, python, ...

Auf dieser Plattform können neue, spezialisierte Dienste von Drittanbietern schnell, flexibel und skalierbar aufgebaut werden, ohne dass besondere Programmierexpertise erforderlich ist. Damit ist diese Datenwürfel-Plattform exzellent für Kleinunternehmen und Neugründungen geeignet, um innovative Dienste schnell aufzusetzen und dynamisch an neue Kundenerfordernisse anzupassen. In BigDataCube wurde dazu pixelgenaue Abrechnung von Zugriff und Prozessierung möglich sowie Quota, immer unter vollständiger Kontrolle durch den Administrator. Bis auf weiteres sind die CODE-DE Anfragedienste kostenfrei zugänglich.

Zusätzlich sind durch eine ortstransparente Föderation weitere Daten anderer Anbieter nahtlos eingebunden; in BigDataCube wurde dies mit den kommerziellen Diensten von cloudeo AG demonstriert, weitere nationale und internationale Datenzentren sind in Verhandlung. Realisiert sind die CODE-DE Datenwürfel mit rasdaman "(raster data manager"), der vollstöndig in Deutschland entwickelten, weltweit führenden Datenwürfel-Technologie (im Datenbank-Jargon: "Array-Datenbank"), welche gleichzeitig OGC-Referenzimplementierung ist. Gleichzeitig werden während des Projekts die Datenwürfel-Standards von OGC, ISO und INSPIRE weiterentwickelt.

BigDataCube wird gefördert vom Bundeswirtschaftsministerium.

Projektpartner sind:
Jacobs University (Projektleitung),
rasdaman GmbH,
cloudeo AG und
DLR Earth Observation Center (im Unterauftrag)

BigDataCube Dienste in CODE-DE:

Sentinel Datacubes: Extraktion, Analyse und Visualisierung

WCS / WCPS / WMS Service-Endpunkt:

Datum der letzten Änderung
17-07-2019 11:28:00

Jacobs University, rasdaman GmbH, cloudeo AG, DLR Earth Observation Center


Mit dem Projekt AGRO-DE wird ein Daten- und Auswertungscluster geschaffen werden, welches landwirtschaftlichen Betrieben, Beratern, Lohnunternehmern und Serviceprovidern ermöglicht, vorverarbeitete Fernerkundungsinformationen zeitnah nutzen zu können und in ihre Betriebsabläufe zu integrieren. Die Informationen sollen dabei in verschiedenen Formen (z.B. als Karten- oder Datendienst), Informationstiefen (z.B. als Bilddaten, Informationsprodukt, oder als dynamisches Modellierungsergebnis) und Abrechnungsmodellen (kostenfrei und gebührenpflichtig) bereitgestellt werden. Erstmalig können alle Landwirte in Deutschland von aktuellen Satelliteninformationen profitieren. Mit AGRO-DE wird ein offener Zugang zu nutzbaren Informationsprodukten geschaffen, der den Einsatz von Precision Farming Technologien stimulieren soll. Diese Technologien sollen auch kleinstrukturierte Betriebe und Betriebe mit ökologischem Landbau ansprechen. Darüber hinaus können Informationsprodukte aus AGRO-DE zukünftig auch Forschungseinrichtungen, Bundes- und Landesbehörden sowie Nichtregierungsorganisationen (NGO) bei ihrer Arbeit unterstützen, da methodisch einheitlich hergestellte Datensätze für Deutschland bereitstehen.

AGRO-DE Produkte in CODE-DE:

Sentinel-2 MSI - Level 2A Surface Reflectance (AGRO-DE) - Germany; siehe:

Sentinel-2 MSI - Level 2B Vegetation Indices (AGRO-DE) - Germany; siehe:

SCMaP - Landsat - Germany, 1984-2014; siehe:

AGRO-DE Download Service (erfordert Registrierung und Beantragung zusätzlicher Berechtigungen):

Datum der letzten Änderung
15-03-2019 01:11:28

Bundesministerium für Ernährung und Landwirtschaft


CODE-DE bietet nützliche Werkzeuge wie die Sentinel-Toolboxen. Werkzeuge, die extern gehostet werden, werden verknüpft; Andere Werkzeuge können direkt vom Marktplatz heruntergeladen werden. Informationen zur Verwendung dieser Werkzeuge im Rahmen von CODE-DE finden Sie im Benutzerhandbuch oder im HelpDesk.

TIMESAT is a software package for analysing time-series of satellite sensor data.

TIMESAT has been developed to investigate the seasonality of satellite time-series data and their relationship with dynamic properties of vegetation, such as phenology and temporal development. The temporal domain holds important information about short- and long-term vegetation changes. TIMESAT was originally intended for handling noisy time-series of AVHRR NDVI data and to extract seasonality information from the data. The program now has the capability to handle different types of remotely sensed time-series , e.g. data from Terra/MODIS at different time resolutions. It has also been tested with eddy covariance data and moisture data, although these applications are not the main target.

Datum der letzten Änderung
07-03-2017 02:29:51

Per Jönsson, Malmö University; Lars Eklundh, Lund University

Sen2Cor is a processor for Sentinel-2 Level 2A product generation and formatting.

The processor performs the atmospheric-, terrain and cirrus correction of Top-Of-Atmosphere Level 1C input data. Sen2Cor creates Bottom-Of-Atmosphere, optionally terrain- and cirrus corrected reflectance images; additional, Aerosol Optical Thickness-, Water Vapor-, Scene Classification Maps and Quality Indicators for cloud and snow probabilities. Its output product format is equivalent to the Level 1C User Product: JPEG 2000 images, three different resolutions, 60, 20 and 10 m.

Datum der letzten Änderung
07-03-2017 02:31:30

European Space Agency (ESA)

The software Fmask (Function of mask) is used for automated clouds, cloud shadows, and snow masking for Landsat (4, 5, 7, and 8) and Sentinel-2 data.

This package implements the Fmask algorithm as a Python module. It is intended that this can be wrapped in a variety of main programs which can handle the local details of how the image files are named and organised, and is intended to provide maximum flexibility. It should not be tied to expecting the imagery to be layed out in a particular manner. This modular design also simplifies the use of the same core algorithm on either Landsat and Sentinel imagery. The wrapper programs take care of differences in file organisation and metadata formats, while the core algorithm is the same for both

Datum der letzten Änderung
07-03-2017 02:30:44

Neil Flood, Sam Gillingham

The Automated Radiative Transfer Models Operator (ARTMO) Graphic User Interface (GUI) is a software package that provides essential tools for running and inverting a suite of plant RTMs, both at the leaf and at the canopy level.

ARTMO facilitates consistent and intuitive user interaction, thereby streamlining model setup, running, storing and spectra output plotting for any kind of optical sensor operating in the visible, near-infrared and shortwave infrared range (400-2500 nm).

Datum der letzten Änderung
07-03-2017 02:33:16

Universitat de València, IPL Image Processing Laboratory


Bestimmte Verarbeitungswerkzeuge, wie saisonal wolkenfreie Mosaiken oder zeitliche Merkmalserzeugung, stehen für registrierte Benutzer zur Verfügung, um auf ihren bevorzugten Sensor oder Bereich von Interesse angewendet zu werden.

Processor for band math with Sentinel Products in CODE-DE

The SNAP Generic BandMath operator allows to create a product with multiple bands based on mathematical expressions. The geo-coding information and metadata for the target product is taken from the source product.

Sentinel-2 Atmospheric Correction (Sen2Cor) Processor in CODE-DE

Sen2Cor is a processor for Sentinel-2 Level 2A product generation and formatting; it performs the atmospheric-, terrain and cirrus correction of Top-Of- Atmosphere Level 1C input data. Sen2Cor creates Bottom-Of-Atmosphere, optionally terrain- and cirrus corrected reflectance images; additional, Aerosol Optical Thickness-, Water Vapor-, Scene Classification Maps and Quality Indicators for cloud and snow probabilities. Equivalent to the Level 1C User Product: JPEG 2000 images, three different resolutions, 60, 20 and 10 m.

Copernicus Data Access and Exploitation Platform for Germany (CODE-DE) - Processors

The CODE-DE processing subsystem is based on existing software components like Hadoop, Calvalus and Sentinel Toolbox. The processing services offered provide an environment to generate higher level data products from the satellite data hosted on the CODE-DE platform.

Datum der letzten Änderung
30-11-2017 01:47:04

Brockmann Consult GmbH

VM Template for CODE-DE

This is the VM Template for CODE-DE. It consists of tools which allow users to search for data in the CODE-DE data storage, retrieve data from the CODE-DE data storage, and to interact with CODE-DE processing system. The tools are accompanied by documentation and a sample processing request file.


Sample processing file: