A multi-task convolutional neural network for mega-city analysis using very high resolution satellite imagery and geospatial data

Understand

Mega-city analysis with very high resolution (VHR) satellite images has been drawing increasing interest in the fields of city planning and social investigation.

• It is known that accurate land-use, urban density, and population distribution information is the key to mega-city monitoring and environmental studies.
• Therefore, how to generate land-use, urban density, and population distribution maps at a fine scale using VHR satellite images has become a hot topic.
• Previous studies have focused solely on individual tasks with elaborate hand-crafted features and have ignored the relationship between different tasks.