Automatic satellite building construction monitoring

TL;DR

This paper presents a novel deep learning pipeline that combines segmentation and detection networks to monitor building construction progress from satellite images, enabling remote and efficient construction oversight.

Contribution

It introduces a unified deep learning approach that integrates multiple networks for satellite image interpretation of construction progress, addressing interpretation challenges.

Findings

Effective combination of segmentation and detection networks

Accurate monitoring of construction progress from satellite images

Potential for remote construction oversight

Abstract

One of the promising applications of satellite images is building construction monitoring. It allows to control the construction progress around the world even in the locations that are hard to reach. One of the main hurdles of this approach is the interpretation of the image data. In this paper, we have employed several novel deep learning techniques to tackle the problem. Various image segmentation and object detection networks were combined into a unified pipeline, which was then used to determine the building construction progress.