The European Sentinel missions and the latest generation of the United States Landsat satellites provide new opportunities for global environmental monitoring. They acquire imagery at spatial resolutions between 10 and 60 m in a temporal and spatial coverage that could before only be realized on the basis of lower resolution Earth observation data (>250 m). However, images gathered by these modern missions rapidly add up to data volume that can no longer be handled with standard work stations and software solutions. Hence, this contribution introduces the TimeScan concept which combines pre-existing tools to an exemplary modular pipeline for the flexible and scalable processing of massive image data collections on a variety of (private or public) computing clusters. The TimeScan framework covers solutions for data access to arbitrary mission archives (with different data provisioning policies) and data ingestion into a processing environment (EO2Data module), mission specific pre-processing of multi-temporal data collections (Data2TimeS module), and the generation of a final TimeScan baseline product (TimeS2Stats module) providing a spectrally and temporally harmonized representation of the observed surfaces. Technically, a TimeScan layer aggregates the information content of hundreds or thousands of single images available for the area and time period of interest (i.e. up to hundreds of TBs or even PBs of data) into a higher level product with significantly reduced volume. In first test, the TimeScan pipeline has been used to process a global coverage of 452,799 multispectral Landsat-8 scenes acquired from 2013 to 2015, a global data-set of 25,550 Envisat ASAR radar images collected 2010-2012, and regional Sentinel-1 and Sentinel-2 collections of ∼1500 images acquired from 2014 to 2016. The resulting TimeScan products have already been successfully used in various studies related to the large-scale monitoring of environmental processes and their temporal dynamics.
ARTICLE HISTORY
The digital transformation taking place in all areas of life has led to a massive increase in digital datain particular, related to the places where and the ways how we live. To facilitate an exploration of the new opportunities arising from this development the Urban Thematic Exploitation Platform (U-TEP) has been set-up. This enabling instrument represents a virtual environment that combines open access to multisource data repositories with dedicated data processing, analysis and visualisation functionalities. Moreover, it includes mechanisms for the development and sharing of technology and knowledge. After an introduction of the underlying methodical concept, this paper introduces four selected use cases that were carried out on the basis of U-TEP: two technology-driven applications implemented by users from the remote sensing and software engineering community (generation of cloud-free mosaics, processing of drone data) and two examples related to concrete use scenarios defined by planners and decision makers (data analytics related to global urbanization, monitoring of regional land-use dynamics). The experiences from U-TEP's pre-operations phase show that the system can effectively support the derivation of new data, facts and empirical evidence that helps scientists and decision-makers to implement improved strategies for sustainable urban development.
The Sentinel fleet will provide a so-far unique coverage with Earth observation data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and services. It is here where the TEP Urban project is supposed to initiate a step change by providing an open and participatory platform based on modern ICT technologies and services that enables any interested user to easily exploit Earth observation data pools, in particular those of the Sentinel missions, and derive thematic information on the status and development of the built environment from these data. Key component of TEP Urban project is the implementation of a web-based platform employing distributed high-level computing infrastructures and providing key functionalities for i) high-performance access to satellite imagery and derived thematic data, ii) modular and generic state-of-the art pre-processing, analysis, and visualization techniques, iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication. This contribution introduces the main facts about the TEP Urban project, including a description of the general objectives, the platform systems design and functionalities, and the preliminary portfolio products and services available at the TEP Urban platform.
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