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European Regional Science Association (ERSA), REGION, 2(7), p. R15-R46, 2020

DOI: 10.18335/region.v7i2.295

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A reproducible notebook to acquire, process and analyse satellite imagery

Journal article published in 2020 by Meixu Chen ORCID, Dominik Fahrner ORCID, Daniel Arribas-Bel ORCID, Francisco Rowe ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Satellite imagery is often used to study and monitor Earth surface changes. The open availability and extensive temporal coverage of Landsat imagery has enabled changes in temperature, wind, vegetation and ice melting speed for a period of up to 46 years. Yet, the use of satellite imagery to study cities has remained underutilised, partly due to the lack of a methodological approach to capture features and changes in the urban environment. This notebook offers a framework based on Python tools to demonstrate how to batch-download high-resolution satellite imagery; and enable the extraction, analysis and visualisation of features of the built environment to capture long-term urban changes.