New Enabling Technologies to Observe and Characterise Urban Environments with Big Data from Space – the Urban Thematic Exploitation Platform

Modern Earth Observation (EO) satellite missions provide valuable opportunities to support sustainable urban planning and management by delivering dedicated information on the spatiotemporal development of the built environment and its key morphological and physical characteristics such as imperviousness, greenness, built-up density, building volume, albedo – from global down to local scale. However, the transformation of the raw EO imagery into ready-to-use thematic data and indicators for scientist or planners on the one hand and actionable information for decision makers on the other hand requires detailed technical expert knowledge. Moreover, the imagery collected by satellite missions such as the US Landsat program or the European fleet of Sentinel satellites, but also by airborne systems or drones, rapidly adds up to a multiple of the data volume that can effectively be handled with standard work stations and software solutions. Hence, this contribution introduces the Urban Thematic Exploitation Platform (https://urban-tep.eo.esa.int) that utilizes modern information and communication technology to bridge the gap between the mass data collections of the technology-driven EO sector and the demand of science, planning, and policy for up-to-date information on the status, properties and dynamics of the urban system. Key components of the Urban Thematic Exploitation Platform (U-TEP) are an open, web-based portal that is connected to distributed high-level computing clusters and clouds and that also provides key functionalities for i) high-performance data access, analysis and visualization, ii) customized development and sharing of algorithms, products and services, and iii) networking, communication and exchange of data and information. The overarching objective here is to enable any interested (non-expert) user to easily generate actionable indicators and information for effective sustainable urban development based on a joint analysis of various data sources such as official survey data, EO mission data, socio-economic statistics, and data collected via social media or citizen science. So far more than 3.5 PB of data have been processed and analyzed by means of the U-TEP to finally provide a broad spectrum of urban information products and related services for visualization and analytics that have yet successfully been used by more than 240 institutions (science, planning, NGOs, policy) from 41 countries (i.a. World Bank Group, United Nations, Organisation for Economic Cooperation and Development, World Food Programme, Bill and Melinda Gates Foundation, Group on Earth Observation, Global Platform for Sustainable Cities)

From Pixels to Planning: Large-scale Mapping of Urban Morphology and Population Distribution with the World Settlement Footprint 3D

Urban morphology and human population distribution are two interrelated aspects of our urbanization that play a critical role in shaping the sustainability, resilience and liveability of cities. In recent years, the advent of global datasets with 3D information derived from Earth Observation (EO) technologies has revolutionised our ability to study and analyse these two aspects of urbanisation, providing information that is essential for designing cities that can accommodate the needs of their residents while minimizing their environmental impact. One such dataset is the novel World Settlement Footprint 3D (WSF3D) produced by the German Aerospace Center (DLR). The WSF3D was the first global dataset providing detailed information of the fraction, area, average height and total volume of buildings, at unprecedented spatial resolution, coverage and consistency. Since its development, researchers from different organizations (e.g. WorldBank, United Nations, WorldPop) have employed the dataset as input data for large-scale studies in urban morphology and population distribution, with a level of detail that was previously impossible. In this paper we present a selection of WSF3D-driven applications with the objective of demonstrating how the new data can be used to support urban planning and management. First, the WSF3D has been employed to demonstrate how the four layers of the dataset can be used to determine a building's functional use, and how this information can be leveraged to improve large-scale models of population distribution at large-scale. Thereafter, the WSF3D has been used to determine the relationships among building height/volume, population density and income, which can provide insights into the efficient use of space (e.g. crowding vs layering) on the one hand, and shed light into infrastructure disparities and variations, on the other. With that being said, due to the global nature of the WSF3D dataset, the previous analyses were conducted from local to regional scales, which can also help identify opportunities for interventions that can be replicated across different locations. Overall, with the results of this research, the authors aim to provide planners and policy-makers with valuable insights into usability of the globally available WSF3D dataset. By demonstrating its potential as reliable and robust input data, this study seeks not only to empower evidence-based decision-making, but also to advocate for the widespread adoption of geospatial layers in the implementation of strategies towards sustainable development strategies of the built environment

From Pixels to Planning: Large-scale Mapping of Urban Morphology and Population Distribution with the World Settlement Footprint 3D

Urban morphology and human population distribution are two interrelated aspects of our urbanization that play a critical role in shaping the sustainability, resilience and liveability of cities. In recent years, the advent of global datasets with 3D information derived from Earth Observation (EO) technologies has revolutionised our ability to study and analyse these two aspects of urbanisation, providing information that iS essential for designing cities that can accommodate the needs of their residents while minimizing their environmental impact. One such dataset is the novel World Settlement Footprint 3D (WSF3D) produced by the German Aerospace Center (DLR). The WSF3D was the first global dataset providing detailed information of the fraction, area, average height and total volume of buildings, at unprecedented spatial resolution, coverage and consistency. Since its development, researchers from different organizations (e.g. WorldBank, United Nations, WorldPop) have employed the dataset as input data for large-scale studies in urban morphology and population distribution, with a level of detail that was previously impossible. In this paper we present a selection of WSF3D-driven applications with the objective of demonstrating how the new data can be used to support urban planning and management. First, the WSF3D has been employed to demonstrate how the four layers of the dataset can be used to determine a building's functional use, and how this information can be leveraged to improve large-scale models of population distribution at large-scale. Thereafter, the WSF3D has been used to determine the relationships among building height/volume, population density and income, which can provide insights into the efficient use of space (e.g. crowding vs layering) on the one hand, and shed light into infrastructure disparities and variations, on the other. With that being said, due to the global nature of the WSF3D dataset, the previous analyses were conducted from local to regional scales, which can also help identify opportunities for interventions that can be replicated across different locations. Overall, with the results of this research, the authors aim to provide planners and policy-makers with valuable insights into usability of the globally available WSF3D dataset. By demonstrating its potential as reliable and robust input data, this study seeks not only to empower evidence-based decision-making, but also to advocate for the widespread adoption of geospatial layers in the implementation of strategies towards sustainable development strategies of the built environment

Breaking new ground in mapping human settlements from space -The Global Urban Footprint-

Today 7.2 billion people inhabit the Earth and by 2050 this number will have risen to around nine billion, of which about 70 percent will be living in cities. Hence, it is essential to understand drivers, dynamics, and impacts of the human settlements development. A key component in this context is the availability of an up-to-date and spatially consistent map of the location and distribution of human settlements. It is here that the Global Urban Footprint (GUF) raster map can make a valuable contribution. The new global GUF binary settlement mask shows a so far unprecedented spatial resolution of 0.4 arcsec ($\sim12 m$) that provides - for the first time - a complete picture of the entirety of urban and rural settlements. The GUF has been derived by means of a fully automated processing framework - the Urban Footprint Processor (UFP) - that was used to analyze a global coverage of more than 180,000 TanDEM-X and TerraSAR-X radar images with 3m ground resolution collected in 2011-2012. Various quality assessment studies to determine the absolute GUF accuracy based on ground truth data on the one hand and the relative accuracies compared to established settlements maps on the other hand, clearly indicate the added value of the new global GUF layer, in particular with respect to the representation of rural settlement patterns. Generally, the GUF layer achieves an overall absolute accuracy of about 85\%, with observed minima around 65\% and maxima around 98 \%. The GUF will be provided open and free for any scientific use in the full resolution and for any non-profit (but also non-scientific) use in a generalized version of 2.8 arcsec ($\sim84m$). Therewith, the new GUF layer can be expected to break new ground with respect to the analysis of global urbanization and peri-urbanization patterns, population estimation or vulnerability assessment

Outlining where humans live -- The World Settlement Footprint 2015

Human settlements are the cause and consequence of most environmental and societal changes on Earth; however, their location and extent is still under debate. We provide here a new 10m resolution (0.32 arc sec) global map of human settlements on Earth for the year 2015, namely the World Settlement Footprint 2015 (WSF2015). The raster dataset has been generated by means of an advanced classification system which, for the first time, jointly exploits open-and-free optical and radar satellite imagery. The WSF2015 has been validated against 900,000 samples labelled by crowdsourcing photointerpretation of very high resolution Google Earth imagery and outperforms all other similar existing layers; in particular, it considerably improves the detection of very small settlements in rural regions and better outlines scattered suburban areas. The dataset can be used at any scale of observation in support to all applications requiring detailed and accurate information on human presence (e.g., socioeconomic development, population distribution, risks assessment, etc.)

World Settlement Footprint 3D - A first three-dimensional survey of the global building stock

Settlements, and in particular cities, are at the center of key future challenges related to global change and sustainable development. Widely used indicators to assess the efficiency and sustainability of settlement development are the compactness and density of the built-up area. However, at global scale, a temporally consistent and spatially detailed survey of the distribution and concentration of the building stock – meaning the total area and volume of buildings within a defined spatial unit or settlement, commonly referred to as building density – does not yet exist. To fill this data and knowledge gap, an approach was developed to map key characteristics of the world’s building stock in a so far unprecedented level of spatial detail for every single settlement on our planet. The resulting World Settlement Footprint 3D dataset quantifies the fraction, total area, average height, and total volume of buildings for a measuring grid with 90 m cell size. The World Settlement Footprint 3D is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery at 10 m spatial resolution, in combination with 12 m digital elevation data and radar imagery collected by the TanDEM-X mission. The underlying, automated processing framework includes three basic workflows: one estimating the mean building height based on an analysis of height differences along potential building edges, a second module determining the building fraction and total building area within each 90 m cell, and a third part combining the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. Optionally, a simple 3D building model (level of detail 1) can be generated for regions where data on the building footprints is available. A comprehensive validation campaign based on 3D building models obtained for 19 regions (~86,000 km2) and street-view samples indicating the number of floors for >130,000 individual buildings in 15 additional cities documents that the novel World Settlement Footprint 3D data provides valuable and, for the first time, globally consistent information on key characteristics of the building stock in both, large urban agglomerations as well as small-scale rural settlements. Thus, the new dataset represents a promising baseline dataset for a wide range of previously impossible environmental, socioeconomic, and climatological studies worldwide

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

Large-scale 3D Modelling of the Built Environment - Joint Analysis of TanDEM-X, Sentinel-2 and Open Street Map Data

Continental to global scale mapping of the human settlement extent based on earth observation satellite data has made considerable progress. Nevertheless, the current approaches only provide a two-dimensional representation of the built environment. Therewith, a full characterization is restricted in terms of the urban morphology and built-up density, which can only be gained by a detailed examination of the vertical settlement extent. This paper introduces a methodology for the extraction of three-dimensional (3D) information on human settlements by analyzing the digital elevation and radar intensity data collected by the German TanDEM-X satellite mission in combination with multispectral Sentinel-2 imagery and data from the Open Street Map initiative and the Global Urban Footprint human settlement mask. The first module of the underlying processor generates a normalized digital surface model from the TanDEM-X digital elevation model for all regions marked as a built-up area by the Global Urban Footprint. The second module generates a building mask based on a joint processing of Open Street Map, TanDEM-X/TerraSAR-X radar images, the calculated normalized digital surface model and Sentinel-2 imagery. Finally, a third module allocates the local relative heights of the normalized digital surface model to the building structures provided by the building mask. The outcome of the procedure is a 3D map of the built environment showing the estimated local height for all identified vertical building structures at 12 m spatial resolution. The results of a first validation campaign based on reference data collected for the seven cities of Amsterdam (NL), Indianapolis (US), Kigali (RW), Munich (DE), New York (US), Vienna (AT), and Washington (US) indicate the potential of the proposed methodology to accurately estimate the distribution of building heights within the built-up area

Digital world meets urban planet – new prospects for evidence-based urban studies arising from joint exploitation of big earth data, information technology and shared knowledge

The digital transformation taking place in all areas of life has led to a massive increase in digital data – in 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 multi-source 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