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Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.

Urbanization and climate change, representing two of the most relevant global trends related to the human presence on the planet, challenge our environmental, societal and economic development. The availability of and access to accurate, detailed and up-to-date information will impact decision making processes all over the world. The suite of the Copernicus Sentinel satellites in combination with their free and open access data policy contributes to a spatially and temporally detailed monitoring of the Earth’s surface. At the same time a multitude of additional sources of open geo-data is available - e.g., from other earth observation (EO) missions (Landsat, etc.), from national or international statistics or land surveying offices, volunteered geographic information or social media. Detailed and reliable information on global human settlements can directly contribute to the monitoring and decision making regarding the 2030 Agenda for Sustainable Development and provides relevant data for the Sustainable Development Goals (SDG), specifically SDG 11, as well as other global and national policy frameworks. However, the capability to effectively and efficiently access, process, and jointly analyze the heterogeneous and often large-volume data collections poses a key technical challenge. The Urban Thematic Exploitation Platform (U-TEP) is developed to provide end-to-end and ready-to-use solutions for a broad spectrum of users (scientists, researchers, planners and policy-/decision makers) to extract unique information/ indicators required for urban management and sustainability. Key components of the system are an open, web-based portal connected to distributed high-level computing infrastructures and providing key functionalities for: i) high-performance data access and processing, ii) modular and generic state-of-the art pre-processing, analysis, and visualization, iii) customized development and sharing of algorithms, products and services, and iv) networking and communication. U-TEP aims at opening up new opportunities to facilitate effective and efficient urban management and the safeguarding of livable cities by systematically exploring the unique EO capabilities in Europe in combination with the big data perspective arising from the constantly growing sources of geo-data. The capabilities of participation and sharing of knowledge by using new media and ways of communication will help to boost interdisciplinary applications with an urban background. The services and functionalities are supposed to enable any interested user to easily exploit and generate thematic information on the status and development of the environment based on EO data and technologies. In order to assure sustainable developments, U-TEP follows an Open Source strategy committing that the platform is based on Open Source components and modules, with an online presence at the world's leading software development platform GitHub (https://github.com/urban-tep). U-TEP provides access to various new products, such as the TimeScan layer, geotagged Tweets, the Global Urban Footprint (GUF) and its successor the World Settlement Footprint (WSF), as well as datasets of other research groups (Nighlights, WorldPop, etc.). Moreover, U-TEP provides processing services that the users can deploy applications to conduct analyses or generate certain products on-demand. U-TEP’s TimeScan on-demand service, for instance, has already been used to successfully generate three global TimeScan layers for 2015, 2010 and 2000 from a total of more than one million Landsat images (Esch et al. 2018). The production was solely based on an implementation of the TimeScan on-demand service at the HPC cluster of U-TEP’s IT4I processing center. The resulting TimeScan-Landsat layers are available at U-TEP’s Geobrowser (https://urban_tep.eo.esa.int/geobrowser/?id=portfolio#!&context=TimeScan%2FLandsat). U-TEP recently successfully completed its development phase and entered a pre-operational phase. The user feedback and the lessons learnt from the 8-months pre-operations phase, identified some key properties and functionalities that can be considered as major determinates for the usability, benefit and attractiveness of an instrument such as U-TEP. A systematic enhancement and streamlining of the platform capabilities and product/service functionalities will be conducted until Q2 2019 and will enable the operational phase of the platform. However, the innovative character of U-TEP platform in terms of available data and processing and analysis functionalities attracted already a large user community (>340 users and institutions from >40 countries) of diverse users (i.a. from science, public institutions, NGOs, industry) so far.

Urbanization and climate change, representing two of the most relevant global trends related to the human presence on the planet, challenge our environmental, societal and economic development. Detailed and reliable information on global human settlements can directly contribute to the monitoring and decision-making regarding the 2030 Agenda for Sustainable Development. Here, the provision of relevant data for the Sustainable Development Goals (SDG), specifically SDG 11, as well as for other global and national policy frameworks is of particular interest. Scientists, analysts, planners and decision makers need capabilities to effectively and efficiently access, process, and jointly analyze the constantly increasing, but often heterogeneous and large-volume data collections on the built environment. The Urban Thematic Exploitation Platform (U-TEP) is developed to provide end-to-end and ready-to-use solutions for the above mentioned users. Key components of the system are an open, web-based portal connected to distributed high-level computing infrastructures and providing key functionalities for i) high-performance data access and processing, ii) modular and generic state-of-the art pre-processing, analysis, and visualization, iii) customized development and sharing of algorithms, products and services, and iv) networking and communication. In addition, it provides access to earth observation (EO) data (Landsat and Copernicus archives) and a heterogeneous ensemble of ready-to-use products from various providers and sources, like geotagged tweets, TimeScan layer, WorldPop population distribution layer, Global Urban Footprint (GUF) and World Settlement Footprint (WSF) products. The Visualization and Analysis Tool (VISAT) on U-TEP allows experts and non-experts to conduct geospatial analyses and queries. Users can create their individual compositions of data and related analysis and visualization functionalities (scopes). In order to allow for the calculation and provision of SDG 11.3.1 ratio of land consumption rate to population growth rate, a dedicated scope was prepared and demonstrated for the region of SE-Asia. The WSF Evolution product, which delineates the development of urban settlements from 1985 to 2015 (derived from advanced Landsat-based analysis), as well as annual population data for four SE-Asian countries were used to track and compare their development path. All countries show an unbalanced development, demonstrated by a higher increase of land up-taken by urban settlement compared to an increase in population. The population of Cambodia doubled in the period of 1985 to 2015, while the settlement area is five times the area of 1985. In Thailand, the settlement area doubled, but the population grew only by 32 %. All results can be combined with other EO-based products or statistical values and can be visualized using several types of multi-temporal graph/chart modes. The demonstration study exemplifies that U-TEP is a powerful tool that can be utilized by administration practitioners and analysts in monitoring and reporting selected SDG indicators such as the SDG 11.3.1. The presentation of the platform will include a live demonstration of the capabilities to analyze urban information relevant for the SDGs with the above-mentioned examples.