Untersuchungen zur hydrologischen Topologie von Landschaftsobjekten für die distributive Flussgebietsmodellierung

Entwicklung einer Methodik zur hydrologischen distributiven Flusseinzugsgebietsmodellierung, die die Vorteile des Ansatzes der Hydrological Resonse Units (HRUs) mit topologischer Information für die Modellierung der lateralen und Gerinneabflussmodifikation versieht. Entwicklung des Distributionskonzepts der topologischen HRUS. Entwicklung einer GIS-Anwendung zur Ausweisung der Modelleinheiten und ihrer Topologie. Erstellung eines distributiven Flussgebietsmodells, das dieses Konzept mit dem PRMS-Modell zur Abflussbildung und konzeptionellen Ansätzen zur lateralen Flächen und Gerinnedynamik implementiert. Evaluierung der Methodik durch Anwendung in zwei ausgewählten Einzugsgebieten (Bröl/Nordrhein-Westfalen, Ilm/Thüringen)

The development of an innovative computer-based Integrated Water Resources Management System for water resources analyses

International audienceThe European IWRMS (Integrated Water Resources Management System) project is dedicated to developing a toolset for a sustainable use and distribution of water resources in souther African countries. This system integrates various scientific components: remote sensing, information systems, database management, and hydrological modelling. This paper is mainly related to the remote sensing contribution of the project. Two points are discussed: land cover classification and the spatio-temporal processing of remote sensing data to extract hydrological parameters

Big data access and processing within the cloud: CODE-DE a non-commercial, operational Earth Observation platform

The amount of Earth Observation (EO) data is increasing at an unprecedented rate. The European Copernicus program, in particular with Sentinel-1 and Sentinel-2 imagery in 10 m spatial resolution, is a major data contributor. These large volumes of data require not only sophisticated data storage and access options, but also new big spatial data analysis approaches. The German Copernicus Data and Exploitation Platform (CODE-DE) is an infrastructure for EO data access, on-demand processing and value-added product generation. CODE-DE is operational since March 2017, hosts more than 1.300 registered users with more than 100.000 downloaded data products. The rolling archive host more than 650 TB of data with und 1.2 million data products. The catalogue client provides an enhanced solution to discover, view, and download available products. While a focus is set on data from the Copernicus program are other satellite imagery integrated into the portal. The on-demand processing environment for high-performance cloud processing is operational since November 2017. The algorithms currently available are mainly based on the Sentinel tool box (SNAP) functionality, such as generic band math or dedicated time series algorithms. Processed data can optionally be mosaicked covering larger areas or a time periods. The capacity of the processing environment has been continuously exploited since March 2018 by selected applications, e.g. in the agricultural, maritime or snow and ice context, based on dedicated virtual machines or docker technology. This flexible and free processing approach supports different use cases – allowing developers, processing experts and data experts to work on the platform in support of their own processing scenarios. The CODE-DE data and IT architecture will be explained and implemented user applications presented

Land use classification at meso-scale using remotely sensed data

International audienceIn this paper we present a framework to generate a land cover classification from coarse spatial resolution remotely sensed data acquired by NOAA-AVHRR sensor. We define a model for the pixels’ content and a process allowing to compute the individual proportions of the different land cover types for each pixel. The method is based on a linear mixture model of reflectances and exploits the good temporal frequency of NOAA acquisitions. The result provides a description in terms of land covers percentage within each NOAA pixel. A quality evaluation is performed on a test area for which high spatial resolution and temporal NOAA data are simultaneously available

Application of Remote Sensing to the Development of an Integrated Water Resources Management System (IWRMS)

International audienceWater resources management in Southern Africa is a complex challenge which requires an appropriate integrated approach if strategic and prognostic planning should be based on sound scientific findings in order to optimize and conserve the precious land and water resources. The prototype Integrated Water Resources Management System (IWRMS) will be a toolset of validated computer based procedures, where remote sensing is the major methodology to provide areal data sources to hydrological models assisting water resources managers through their decision strategies

Integrated Water Resources Management System: a decision support system based on remote sensing data evaluation

International audienceNo abstrac

The development of an innovative computer based "Integrated water resources management system" for semi-arid catchments : concept and firts results

International audienc

Insights into CODE-DE - Germany's Copernicus Data and Exploitation Platform

This article presents and analyses the modular architecture and capabilities of CODE-DE (Copernicus Data and Exploitation Platform - Deutschland, www.code-de.org), the integrated German operational environment for accessing and processing Copernicus data and products, as well as the methodology to establish and operate the system. Since March 2017, CODE-DE has been online with access to Sentinel-1 and Sentinel-2 data, to Sentinel-3 data shortly after this time, and since March 2019 with access to Sentinel-5P data. These products are available and accessed by 1,682 registered users as of March 2019. During this period 654,895 products were downloaded and a global catalogue was continuously updated, featuring a data volume of 814 TByte based on a rolling archive concept supported by a reload mechanism from a long-term archive. Since November 2017, the element for big data processing has been operational, where registered users can process and analyse data themselves specifically assisted by methods for value-added product generation. Utilizing 195,467 core and 696,406 memory hours, 982,948 products of different applications were fully automatically generated in the cloud environment and made available as of March 2019. Special features include an improved visualization of available Sentinel-2 products, which are presented within the catalogue client at full 10 m resolution