[HTML][HTML] Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning
African cities are growing rapidly and more than half of their populations live in deprived
areas. Local stakeholders urgently need accurate, granular, and routine maps to plan …
areas. Local stakeholders urgently need accurate, granular, and routine maps to plan …
Conceptualizing the nexus between spatiotemporal shrinkage patterns of natural cities and driving mechanisms: Insights into urban shrinkage in Northeast China
Urban shrinkage has become an inevitable problem for the sustainable urban development.
For a long time, the administrative perspective has been the dominant perspective in urban …
For a long time, the administrative perspective has been the dominant perspective in urban …
Mapping Deprived Urban Areas Using Open Geospatial Data and Machine Learning in Africa
Reliable data on slums or deprived living conditions remain scarce in many low-and middle-
income countries (LMICs). Global high-resolution maps of deprived areas are fundamental …
income countries (LMICs). Global high-resolution maps of deprived areas are fundamental …
Uncertainty analysis of potential population exposure within the coastal lowlands of mainland China
F Li, C Yao, J Fu, X Yang - Environmental Research Letters, 2023 - iopscience.iop.org
With accelerating global sea level rise driven by climate change, accurate estimates of
potential population exposure (PPE) within the low-elevation coastal zones (LECZ) are …
potential population exposure (PPE) within the low-elevation coastal zones (LECZ) are …
Deep Learning for Slum Mapping in Remote Sensing Images: A Meta-analysis and Review
The major Sustainable Development Goals (SDG) 2030, set by the United Nations
Development Program (UNDP), include sustainable cities and communities, no poverty, and …
Development Program (UNDP), include sustainable cities and communities, no poverty, and …
[HTML][HTML] Interpretable deep learning for consistent large-scale urban population estimation using Earth observation data
Accurate and up-to-date mapping of the human population is fundamental for a wide range
of disciplines, from effective governance and establishing policies to disaster management …
of disciplines, from effective governance and establishing policies to disaster management …
[HTML][HTML] QIENet: Quantitative irradiance estimation network using recurrent neural network based on satellite remote sensing data
Global horizontal irradiance (GHI) plays a vital role in estimating solar energy resources,
which are used to generate sustainable green energy. In order to estimate GHI with high …
which are used to generate sustainable green energy. In order to estimate GHI with high …
Are public green spaces distributed fairly? A nationwide analysis based on remote sensing, OpenStreetMap and census data
Green space (GS) is a crucial resource in urban areas, but not spatially uniformly distributed.
We compare the availability of GS on a national scale using green land cover (GLC) and …
We compare the availability of GS on a national scale using green land cover (GLC) and …
Scale effects-aware bottom-up population estimation using weakly supervised learning
J Xia, R Li, X Liu, G Liu, M Peng - International Journal of Digital …, 2024 - Taylor & Francis
Fine-scale population estimation (FPE) is crucial for urban management. After training, the
bottom-up FPE models can be applied independently of census data. However, given the …
bottom-up FPE models can be applied independently of census data. However, given the …
IDeaMapSudan: Geo-Spatial Modelling of Urban Poverty
M Kuffer, IMM Ali, A Gummah… - 2023 Joint Urban …, 2023 - ieeexplore.ieee.org
Khartoum, Sudan, is one of the fast-growing African metropolises, with a massive increase in
its population from around 245,000 in 1956, to over 8 million in 2022 (Khartoum State). This …
its population from around 245,000 in 1956, to over 8 million in 2022 (Khartoum State). This …