Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
Satellite-based mapping of urban poverty with transfer-learned slum morphologies
In the course of global urbanization, poverty in cities has been observed to increase,
especially in the Global South. Poverty is one of the major challenges for our society in the …
especially in the Global South. Poverty is one of the major challenges for our society in the …
[HTML][HTML] Uncertainty-aware interpretable deep learning for slum mapping and monitoring
Over a billion people live in slums, with poor sanitation, education, property rights and
working conditions having a direct impact on current residents and future generations. Slum …
working conditions having a direct impact on current residents and future generations. Slum …
[HTML][HTML] Slums, space, and state of health—a link between settlement morphology and health data
Approximately 1 billion slum dwellers worldwide are exposed to increased health risks due
to their spatial environment. Recent studies have therefore called for the spatial environment …
to their spatial environment. Recent studies have therefore called for the spatial environment …
Uncertainties of human perception in visual image interpretation in complex urban environments
Today satellite images are mostly exploited automatically due to advances in image
classification methods. Manual visual image interpretation (MVII), however, still plays a …
classification methods. Manual visual image interpretation (MVII), however, still plays a …
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 …
[PDF][PDF] Slum image detection and localization using transfer learning: a case study in Northern Morocco
T El Moudden, R Dahmani, M Amnai… - International Journal of …, 2023 - academia.edu
Developing countries are faced with social and economic challenges, including the
emergence and proliferation of slums. Slum detection and localization methods typically rely …
emergence and proliferation of slums. Slum detection and localization methods typically rely …
Predicting housing deprivation from space in the slums of Dhaka
Cities in developing countries have been struggling to deal with the pressures of
urbanization on infrastructure, basic services, land, and housing that often manifest as poor …
urbanization on infrastructure, basic services, land, and housing that often manifest as poor …
Gaofen-2 satellite image-based characterization of urban villages using multiple convolutional neural networks
C Wei, H Wei, A Crivellari, T Liu, Y Wan… - … Journal of Remote …, 2023 - Taylor & Francis
Remote sensing has proven to be an invaluable and effective tool for mapping urban areas.
However, further efforts are required to fully utilize remote sensing data in mapping the …
However, further efforts are required to fully utilize remote sensing data in mapping the …
[HTML][HTML] Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements
J Ajayakumar, AJ Curtis, V Rouzier, JW Pape… - International Journal of …, 2021 - Springer
Background The health burden in developing world informal settlements often coincides
with a lack of spatial data that could be used to guide intervention strategies. Spatial video …
with a lack of spatial data that could be used to guide intervention strategies. Spatial video …