Remote sensing using Synthetic Aperture Radar (SAR) is an indispensable technology for effective disaster management, owing to its large observation area, cloud penetrating ability and its independence from sunlight, which allow for quick observation of large disaster affected areas disregarding weather or time of the day. In particular, 3D measurement from SAR images could contribute a better understanding of the affected area and speed up decision making. Most methods require prior knowledge of the scene such as ground control points to achieve a reasonable level of 3D measurement accuracy, resulting in losing the advantage of quick observation. In this paper, we propose an accurate 3D measurement method from SAR images based on the principle of stereo vision without any prior knowledge of the scene. We demonstrate the effectiveness of our method compared with the conventional method through a set of experiments using an airborne SAR image dataset.
|出版ステータス||出版済み - 2021|
|イベント||2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, ベルギー|
継続期間: 2021 7月 12 → 2021 7月 16
|会議||2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021|
|Period||21/7/12 → 21/7/16|