Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution

• URL: http://arxiv.org/abs/2204.01736v1
• Date: Mon, 4 Apr 2022 17:21:20 GMT
• Title: Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution
• Authors: Yutong He, William Zhang, Chenlin Meng, Marshall Burke, David B. Lobell, Stefano Ermon
• Abstract summary: We propose a pipeline that leverages a single high-resolution image and a time series of publicly available low-resolution images. Our method achieves significant improvement in comparison to baselines using single image super-resolution.
• Score: 82.50301442891602
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Automated tracking of urban development in areas where construction information is not available became possible with recent advancements in machine learning and remote sensing. Unfortunately, these solutions perform best on high-resolution imagery, which is expensive to acquire and infrequently available, making it difficult to scale over long time spans and across large geographies. In this work, we propose a pipeline that leverages a single high-resolution image and a time series of publicly available low-resolution images to generate accurate high-resolution time series for object tracking in urban construction. Our method achieves significant improvement in comparison to baselines using single image super-resolution, and can assist in extending the accessibility and scalability of building construction tracking across the developing world.

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