Generation of Large-Scale High Quality 3-D Urban Models

Shi, Yilei; Bamler, Richard; Wang, Yuanyuan; Zhu, Xiao Xiang

doi:10.1109/radarconf2043947.2020.9266314

Cited by 2 publications

(4 citation statements)

References 24 publications

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“…Concluding this section, it is essential to recognize that new methods with various characteristics appear constantly, giving rise to very detailed representations of tomographic urban representations [136][137][138]. Accordingly, Rambour et al proposed [136] a method for urban surface reconstruction in SAR tomography by graph cuts.…”

Section: Urban Tomographic Imaging From Polsar Data [72]mentioning

confidence: 99%

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SAR Features and Techniques for Urban Planning—A Review

Koukiou

2024

Remote Sensing

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Urban planning has, in recent years, been significantly assisted by remote sensing data. The data and techniques that are used are very diverse and are available to government agencies as well as to private companies that are involved in planning urban and peri-urban areas. Synthetic aperture radar data are particularly important since they provide information on the geometric and electrical characteristics of ground objects and, at the same time, are unaffected by sunlight (day–night) and cloud cover. SAR data are usually combined with optical data (fusion) in order to increase the reliability of the terrain information. Most of the existing relative classification methods have been reviewed. New techniques that have been developed use decorrelation and interferometry to record changes on the Earth’s surface. Texture-based features, such as Markov random fields and co-occurrence matrices, are employed, among others, for terrain classification. Furthermore, target geometrical features are used for the same purpose. Among the innovative works presented in this manuscript are those dealing with tomographic SAR imaging for creating digital elevation models in urban areas. Finally, tomographic techniques and digital elevation models can render three-dimensional representations for a much better understanding of the urban region. The above-mentioned sources of information are integrated into geographic information systems, making them more intelligent. In this work, most of the previous techniques and methods are reviewed, and selected papers are highlighted in order for the reader-researcher to have a complete picture of the use of SAR in urban planning.

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Section: Urban Tomographic Imaging From Polsar Data [72]mentioning

confidence: 99%

“…On the other hand, Huang and Ferro-Famil introduced [137] a way to characterize 3-D urban areas using high-resolution polarimetric SAR tomographic techniques and a minimal number of acquisitions. Finally, Shi et al proposed [138] the generation of large-scale high-quality 3-D urban models.…”

Section: Urban Tomographic Imaging From Polsar Data [72]mentioning

confidence: 99%

SAR Features and Techniques for Urban Planning—A Review

Koukiou

2024

Remote Sensing

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“…As discussed earlier, the SM signal model with a fixed master image is limited in long-baseline cases. Previous research [39,40,42,43] has proposed a bistatic-like MM signal model for atmospheric phase error elimination, which can be adopted for image pairing in D-TomoSAR. This model allows for an unfixed master image.…”

Section: Signal Modelmentioning

confidence: 99%

“…To address this issue, we propose a solution through the idea of MM D-TomoSAR using a non-fixed master image. Although the bistatic-like MM model has been introduced previously in [39,40,42,43], it is a limited one, and only bistatic-like SAR images can be paired to generate interferograms to avoid atmospheric phase errors. In contrast, the proposed model effectively utilizes the advantage that UAV-SAR is free from atmospheric phase errors.…”

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confidence: 99%

P-Band UAV-SAR 4D Imaging: A Multi-Master Differential SAR Tomography Approach

et al. 2023

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Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond the dimensions of range and azimuth, enabling four-dimensional (4D) SAR imaging. In the case of P-band UAV-SAR, a long spatial-temporal baseline is necessary to achieve high enough elevation-velocity dimensional resolution. Although P-band UAV-SAR maintains temporal coherence, it still faces two issues due to the extended spatial baseline, i.e., low spatial coherence and high sidelobes. To tackle these problems, we introduce a multi-master (MM) D-TomoSAR approach, contributing three main points. Firstly, the traditional D-TomoSAR signal model is extended to a MM one, which improves the average coherence coefficient and the number of baselines (NOB) as well as suppresses sidelobes. Secondly, a baseline distribution optimization processing is proposed to equalize the spatial–temporal baseline distribution, achieve more uniform spectrum samplings, and reduce sidelobes. Thirdly, a clustering-based outlier elimination method is employed to ensure 4D imaging quality. The proposed method is effectively validated through computer simulation and P-band UAV-SAR experiment.

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Generation of Large-Scale High Quality 3-D Urban Models

Cited by 2 publications

References 24 publications

SAR Features and Techniques for Urban Planning—A Review

SAR Features and Techniques for Urban Planning—A Review

P-Band UAV-SAR 4D Imaging: A Multi-Master Differential SAR Tomography Approach

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