Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges-Reference-Cited by-同舟云学术

Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges

Published:2023-07-12 Issue:1 Volume:49 Page:
ISSN:0703-8992
Container-title:Canadian Journal of Remote Sensing
language:en
Short-container-title:Canadian Journal of Remote Sensing

Author:

Samsonov Sergey V.¹^ORCID,Feng Wanpeng²^ORCID

Affiliation:

1. Canada Centre for Mapping and Earth Observation, Natural Resources Canada, 580 Booth Street, Ottawa, ON K1A 0E4, Canada

2. Guangdong Provincial Key Laboratory of Geodynamics and Geohazards, School of Earth Sciences and Engineering, Sun Yat-Sen University and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/07038992.2023.2247095

Reference51 articles.

1. ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD)

2. Detection of Frozen Soil Using Sentinel-1 SAR Data

3. Statistical comparison of InSAR tropospheric correction techniques

4. A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data

5. Sentinel-1 and RADARSAT Constellation Mission InSAR Assessment of Slope Movements in the Southern Interior of British Columbia, Canada

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2. Estimating volume of large slow-moving deep-seated landslides in northern Canada from DInSAR-derived 2D and constrained 3D deformation rates;Remote Sensing of Environment;2024-05

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