A framework for large-scale mapping of human settlement extent from Sentinel-2 images via fully convolutional neural networks.

Human settlement extent (HSE) information is a valuable indicator of world-wide urbanization as well as the resulting human pressure on the natural environment. Therefore, mapping HSE is critical for various environmental issues at local, regional, and even global scales. This paper presents a deep-learning-based framework to automatically map HSE from multi-spectral Sentinel-2 data using regionally available geo-products as training labels. A straightforward, simple, yet effective fully convolutional network-based architecture, Sen2HSE, is implemented as an example for semantic segmentation within the framework. The framework is validated against both manually labelled checking points distributed evenly over the test areas, and the OpenStreetMap building layer. The HSE mapping results were extensively compared to several baseline products in order to thoroughly evaluate the effectiveness of the proposed HSE mapping framework. The HSE mapping power is consistently demonstrated over 10 representative areas across the world. We also present one regional-scale and one country-wide HSE mapping example from our framework to show the potential for upscaling. The results of this study contribute to the generalization of the applicability of CNN-based approaches for large-scale urban mapping to cases where no up-to-date and accurate ground truth is available, as well as the subsequent monitor of global urbanization.

Nighttime lights and population changes in Europe 1992-2012.

Nighttime satellite photographs of Earth reveal the location of lighting and provide a unique view of the extent of human settlement. Nighttime lights have been shown to correlate with economic development and population but little research has been done on the link between nighttime lights and population change over time. We explore whether population decline is coupled with decline in lighted area and how the age structure of the population and GDP are reflected in nighttime lights. We examine Europe between the period of 1992 and 2012 using a Geographic Information System and regression analysis. The results suggest that population decline is not coupled with decline in lighted area. Instead, human settlement extent is more closely related to the age structure of the population and to GDP. We conclude that declining populations will not necessarily lead to reductions in the extent of land development.