Andreas Hirner

Exploiting Big Earth Data from Space – First Experiences with the TimeScan Processing Chain

Abstract 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.

Where We Live—A Summary of the Achievements and Planned Evolution of the Global Urban Footprint

The TerraSAR-X (TSX) mission provides a distinguished collection of high resolution satellite images that shows great promise for a global monitoring of human settlements. Hence, the German Aerospace Center (DLR) has developed the Urban Footprint Processor (UFP) that represents an operational framework for the mapping of built-up areas based on a mass processing and analysis of TSX imagery. The UFP includes functionalities for data management, feature extraction, unsupervised classification, mosaicking, and post-editing. Based on >180.000 TSX StripMap scenes, the UFP was used in 2016 to derive a global map of human presence on Earth in a so far unique spatial resolution of 12 m per grid cell: the Global Urban Footprint (GUF). This work provides a comprehensive summary of the major achievements related to the Global Urban Footprint initiative, with dedicated sections focusing on aspects such as UFP methodology, basic product characteristics (specification, accuracy, global figures on urbanization derived from GUF), the user community, and the already initiated future roadmap of follow-on activities and products. The active community of >250 institutions already working with the GUF data documents the relevance and suitability of the GUF initiative and the underlying high-resolution SAR imagery with respect to the provision of key information on the human presence on earth and the global human settlements properties and patterns, respectively.

Experiences of coal fire detection and quantification for resources management

Uncontrolled coal seam fires are an environmental and economic problem of international magnitude. Today, China is the leading country of coal production, consumption and export. The annual Chinese coal production, which is about approx. 2.4 Mt per year, faces a problem of numerous uncontrolled burning coal fires mostly located in the northern Chinese coal belt. The determination of fire radiative energy (FRE) has been introduced recently as a new remote sensing technique to quantify forest and grassland fires. The main research in this project focuses on the development of robust routines to detect coal fire related thermal anomalies within the different areas under investigation. These developments are the prerequisite for a coal fire monitoring.

Earth observation-supported service platform for the development and provision of thematic information on the built environment — the TEP-Urban project

The Sentinel fleet will provide a so-far unique coverage with Earth observation (EO) 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 Information and Communication Technologies (ICTs) that enable any interested user to easily exploit EO 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.

Exploiting Earth observation data pools for urban analysis - The TEP URBAN project

Large amounts of Earth observation (EO) data have been collected to date, to increase even more rapidly with the upcoming Sentinel data. All this data contains unprecedented information, yet it is hard to retrieve, especially for nonremote sensing specialists. As we live in an urban era, with more than 50% of the world population living in cities, urban studies can especially benefit from the EO data. Information is needed for sustainable development of cities, for the understanding of urban growth patterns or for studying the threats of natural hazards or climate change. Bridging this gap between the technology-driven EO sector and the information needs of environmental science, planning, and policy is the driver behind the TEP-Urban project. Modern information technology functionalities and services are tested and implemented in the Urban Thematic Exploitation Platform (U-TEP). The platform enables interested users to easily exploit and generate thematic information on the status and development of the environment based on EO data and technologies. The beta version of the web platform contains value added basic earth observation data, global thematic data sets, and tools to derive user specific indicators and metrics. The code is open source and the architecture of the platform allows adding of new data sets and tools. These functionalities and concepts support the four basic use scenarios of the U-TEP platform: explore existing thematic content; task individual on-demand analyses; develop, deploy and offer your own content or application; and, learn more about innovative data sets and methods.

Earth observation-based service platforms - a new instrument to provide geo-information for urban and regional planning

This paper introduces concepts for the utilization of modern information technology functionalities, bundled in form of dedicated service platforms, to bridge the gap between the technology-driven EO sector and the information needs of environmental science, planning, and policy. Thereby the intended service platforms generally aim at opening up new opportunities by systematically exploring: unique EO capabilities in Europe; Big Data perspective; high-level IT-infrastructures; massive processing power; vast expert knowledge; new media and ways of communication; and increasing connectivity and networks. Key components of such systems are currently developed and tested in the projects OPUS-GMES (Operational Platform for the Provision and Processing of Sentinel Data in Support of Copernicus Geo-Information Services) and TEP Urban (Urban Thematic Exploitation Platform), both coordinated by DLR. The two projects include the implementation of an open, web-based platform employing distributed high-level computing infrastructures (Platform as a Service - PaaS) as well as providing key functionalities for i) high-performance access to thematic data (Information as a Service - InaaS), ii) modular and generic state-of-the art pre-processing, analysis, and visualization (Software as a Service - SaaS), iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication.