基于区域增长策略的三维合成孔径雷达断层成像改进型桥梁参考网络

IF 3.7 1区地球科学 Q1 GEOGRAPHY, PHYSICAL

International Journal of Digital Earth Pub Date : 2024-09-09 DOI:10.1080/17538947.2024.2398072

Youjun Wang, Zhen Dong, Xiantao Wang, Anxi Yu, Yifei Ji, Xing Peng

引用次数: 0

摘要

利用合成孔径雷达层析成像（TomoSAR）技术对城市区域进行三维成像已引起广泛关注。在多通道机载雷达层析成像（TomoSAR）技术的应用中，城市区域的三维成像受到了极大关注。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An improved bridge reference network for 3-D SAR tomography based on regional growing strategy

The utilization of synthetic aperture radar tomography (TomoSAR) technology for the three-dimensional imaging of urban areas has garnered significant attention. In the case of multi-pass spaceborne...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Digital Earth 地学-遥感

CiteScore

6.50

自引率

3.90%

发文量

审稿时长

3 months

期刊介绍： The International Journal of Digital Earth is a response to this initiative. This peer-reviewed academic journal (SCI-E) focuses on the theories, technologies, applications, and societal implications of Digital Earth and those visionary concepts that will enable a modeled virtual world. The journal encourages papers that: Progress visions for Digital Earth frameworks, policies, and standards; Explore geographically referenced 3D, 4D, or 5D models to represent the real planet, and geo-data-intensive science and discovery; Develop methods that turn all forms of geo-referenced data, from scientific to social, into useful information that can be analyzed, visualized, and shared; Present innovative, operational applications and pilots of Digital Earth technologies at a local, national, regional, and global level; Expand the role of Digital Earth in the fields of Earth science, including climate change, adaptation and health related issues,natural disasters, new energy sources, agricultural and food security, and urban planning; Foster the use of web-based public-domain platforms, social networks, and location-based services for the sharing of digital data, models, and information about the virtual Earth; and Explore the role of social media and citizen-provided data in generating geo-referenced information in the spatial sciences and technologies.