A suite of novel EO-based products in support of urban green planning

The strategic implementation of green infrastructures can sensibly help facing the effects of climate change in urban areas by reducing high temperatures, decreasing stormwater runoff, saving energy, improving air quality and increasing biodiversity. In this framework, the benefits of green roofs and urban trees are many and well documented in several recent studies, hence their monitoring is of high use for urban planners to properly design effective adaptation and mitigation strategies. Nevertheless, such activities have been so far solely carried out by means of in situ surveys or photointerpretation of very high resolution airborne imagery, thus being very costly both in terms of money and time. To overcome this drawback, we implemented two novel techniques aimed at automatically identifying current and potential green roofs, as well as mapping tree location and canopy, respectively. In particular, this is carried out by jointly exploiting satellite/airborne color infrared remote sensing imagery and LiDAR height data. Experimental results obtained for Antwerp, Milan, the Helsinki Capital Region, and the Royal Borough of Kensington and Chelsea assess the effectiveness and potential of the proposed techniques

EO-based Smart City Decision Support Services for Integrated Urban Governance: the DECUMANUS project

Urbanization is a fundamental force of change and in Europe has underpinned the flourishing of civilization for millennia. However, the 21st-century is also witnessing the impact of other societal challenges, including climate change adaptation, and mitigation, as well as the need to secure the efficient utilisation of finite resources. These societal challenges are impacting not only the social fabric of urban life, and the economy of cities, but also the civil quality of urban environments throughout Europe. It is clear that if properly governed cities can become a major part of the solutions to the growing threat of these urban challenges, and so can become economically vital, culturally vibrant, and healthy environments delivering first-class quality of life for hundreds of millions of city dwellers throughout Europe. Nonetheless, the challenge of urban governance is immense, and must address the complex and interconnected reality of urban systems to secure a proper balance between the socio-economic and environmental dynamics of urban areas. The key to effective governance of cities is the generation of the necessary intelligence to inform decision-making by city administrations and politicians, to guide urban policy making and implementation, and to inform and engage all citizens in the delivery of sustainable urban development. DECUMANUS (DEvelopment and Consolidation of geo-spatial sUstainability services for adaptation and environmental and cliMAte chaNge Urban impactS) underpins this understanding that the delivery of more sustainable cities requires the application of enhanced intelligence in urban management, to produce an effective basis for assessment of urban complexity and decision-making. The enhanced services proposed by DECUMANUS offer the potential to provide urban planners with the tools and intelligence that allow city managers to deploy geo-spatial products in the development and implementation of their climate change strategies, and more generally in meeting the diverse challenges of sustainable urban development

Flood depth estimation by means of high-resolution SAR images and lidar data

When floods hit inhabited areas, great losses are usually registered in terms of both impacts on people (i.e., fatalities and injuries) and economic impacts on urban areas, commercial and productive sites, infrastructures, and agriculture. To properly assess these, several parameters are needed, among which flood depth is one of the most important as it governs the models used to compute damages in economic terms. This paper presents a simple yet effective semiautomatic approach for deriving very precise inundation depth. First, precise flood extent is derived employing a change detection approach based on the normalized difference flood index computed from high-resolution synthetic aperture radar imagery. Second, by means of a high-resolution lidar digital elevation model, water surface elevation is estimated through a statistical analysis of terrain elevation along the boundary lines of the identified flooded areas. Experimental results and quality assessment are given for the flood that occurred in the Veneto region, northeastern Italy, in 2010. In particular, the method proved fast and robust and, compared to hydrodynamic models, it requires sensibly less input information

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.)

Are European Cities Getting Warmer? Investigating the Urban Heat Island Phenomenon in Europe from 1981-2018 through the Use of NOAA-AVHRR Data

The Urban Heat Island (UHI) effect is one of the most prominent signs of human impact on the Earth system. This phenomenon has significantly altered the energy exchange between land surfaces and the atmosphere which has led to several negative impacts on the quality of city life in terms of air and water quality, energy consumption, vegetation growth and human health. European cities are particularly vulnerable to UHI because of their high degree of urbanization, as illustrated by the 2003 heatwave which claimed thousands of lives. However, the existing body of research mostly concentrates on local-scale and/or short-term analyses, which leaves long-term effects at continental scale poorly understood. Within the TIMELINE project of the Earth Observation Center (EOC) of the German Aerospace Center (DLR), a consistent AVHRR Land Surface Temperature (LST) product has been generated, which is employed in this study to determine the intensity of the surface UHI (SUHI) over Europe for the period 1981−2018. Specifically, the objective is to analyze the long-term SUHI trends and corresponding changes over European cities, as well as to gain insights on their relationships with different variables, like climate, land use and land cover (change), vegetation indices and day-night temperature differences. First results point towards a remarkable increase in both SUHI spatial extent and intensity across the entire continent

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

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 top-down land use planning intelligence to bottom-up stakeholder engagement for smart cities – A case study: DECUMANUS service products

Copyright © 2017 Inderscience Enterprises Ltd. Intelligence delivered by earth observation (EO) satellites performs a vital role in supporting ICT enabled urban governance, and the creation of decision making tools delivering integrated urban planning. This paper reviews the DECUMANUS project experience, detailing the development of the EO derived tools, and evaluating the service products that facilitate the deployment of top-down expertise in land use planning. The central purpose of the paper is to assess the potential for use of these DECUMANUS high resolution EO images and data, also to support bottom-up participatory planning, promoting co-design. It is concluded: 1) EO derived images and associated data offer great opportunity to deliver top-down decision making tools, which combined with auxiliary data, including participatory sensing data, effectively support integrated urban planning; 2) EO derived images also offer substantial potential as communication tools, enabling citizens to make more informed and responsible choices and participate in co-designed urban planning

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