TY - BOOK
T1 - Monitoring land use in cities using satellite imagery and deep learning
AU - Veneri, Paolo
AU - Banquet, Alexandre
AU - Delbouve, Paul
AU - Daams, Michiel
PY - 2022/6/13
Y1 - 2022/6/13
N2 - Over time, cities expand their physical footprint on land and new cities emerge. The shape of the built environment can affect several domains which are policy relevant, such as carbon emissions, housing affordability, infrastructure costs, and access to services. This study lays a methodological basis for the monitoring and consistent comparison of land use across OECD cities. An advanced form of deep learning, namely the U-Net model, is used to classify land cover and land use in EC-ESA satellite imagery for 2021. This complements conventional statistical data by monitoring large surfaces of land efficiently and in near real-time. In specific, following the availability of detailed data for model training, built-up areas in residential or business-related use are mapped and analysed for 687 European metropolitan areas, as a case application. Recent urban expansion’s speed and shape are explored, as well as the potential for assessing land use in cities beyond Europe.
AB - Over time, cities expand their physical footprint on land and new cities emerge. The shape of the built environment can affect several domains which are policy relevant, such as carbon emissions, housing affordability, infrastructure costs, and access to services. This study lays a methodological basis for the monitoring and consistent comparison of land use across OECD cities. An advanced form of deep learning, namely the U-Net model, is used to classify land cover and land use in EC-ESA satellite imagery for 2021. This complements conventional statistical data by monitoring large surfaces of land efficiently and in near real-time. In specific, following the availability of detailed data for model training, built-up areas in residential or business-related use are mapped and analysed for 687 European metropolitan areas, as a case application. Recent urban expansion’s speed and shape are explored, as well as the potential for assessing land use in cities beyond Europe.
U2 - 10.1787/dc8e85d5-en
DO - 10.1787/dc8e85d5-en
M3 - Report
T3 - OECD Regional Development Papers
BT - Monitoring land use in cities using satellite imagery and deep learning
PB - OECD
ER -