Abstract

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.

Highlights

  • Settlements and urban areas characterize the cores of human activity

  • 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), SDG 11 [4]

  • The production of the Global Urban Footprint (GUF) layer is based on a fully automatic, generic and autonomous processing environment orchestrating an extensive suite of processing and analysis modules: the Urban Footprint Processor (UFP)

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Summary

Introduction

Settlements and urban areas characterize the cores of human activity. Population growth and the related urbanization as well as climate change represent the most relevant developments for the human presence on the planet that challenge our ecologic, societal and economic systems at a global scale. The methodology was applied at a global scale and resulted in the Global Urban Footprint (GUF) dataset with a spatial resolution of 12 m [32,33] Considering this evolution and the more than 10 years of experience in the SAR-based mapping of built-up areas, this paper aims at providing a summary of the major achievements and intended future developments of the GUF initiative and product, respectively. Strengthened by the promising results of diverse studies on the use of SAR data for detecting and delineating human settlements, the German Aerospace Center (DLR, Cologne, Germany) initiated the Global Urban Footprint campaign [31] This initiative aimed at the generation of a so far unprecedented worldwide map of human settlements that would for the first time include a significant proportion of the small-scale rural settlements in addition to the comparably large structures of cities and urban clusters already covered by other data sets available at that time

Data Base and Processing Framework
Urban Footprint Processor
Data Management
Feature Extraction
Unsupervised Classification
Mosaicking
Automated Post-Editing
GUF Product Specification and Validation
The State of Global Urbanization—First Figures Derived from the GUF Data
Evolution of the Product Portfolio and Future Updating Capability
Findings
Conclusions and Outlook
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