论文标题
跟踪具有遥感时空超级分辨率的发展区域中的城市化
Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution
论文作者
论文摘要
随着机器学习和遥感方面的最新进展，在无法获得施工信息的地区的自动跟踪城市发展。不幸的是，这些解决方案在高分辨率图像上的表现最佳，这很难获得和不经常可用，因此很难长期跨越跨越大型地理位置。在这项工作中，我们提出了一条管道，该管道利用单个高分辨率图像和一个公共可用的低分辨率图像的时间序列，以生成准确的高分辨率时间序列，以进行城市结构中的对象跟踪。与基线相比，使用单个图像超级分辨率相比，我们的方法取得了重大改进，并可以帮助扩展整个发展中国家的建筑构建跟踪的可访问性和可扩展性。
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.
