Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/235822 
Year of Publication: 
2020
Citation: 
[Journal:] REGION [ISSN:] 2409-5370 [Volume:] 7 [Issue:] 2 [Publisher:] European Regional Science Association (ERSA) [Place:] Louvain-la-Neuve [Year:] 2020 [Pages:] R15-R46
Publisher: 
European Regional Science Association (ERSA), Louvain-la-Neuve
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.
Subjects: 
satellite imagery
image segmentation
urbanisation
cities
urban change,computational notebooks
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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