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Application of SAR and Remote Sensing Technology in Earth Observation

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 252

Special Issue Editors


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Guest Editor
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Interests: TomoSAR; forest vertical structure estimation; forest dynamic change monitoring
Special Issues, Collections and Topics in MDPI journals
School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China
Interests: MTInSAR; surface deformation monitoring; digital elevation model reconstruction
School of Geomatics, Liaoning Technical University, Fuxin, China
Interests: PolInSAR; forest vertical structure estimation; forest dynamic change monitoring; survering adjustment

Special Issue Information

Dear Colleagues,

Global environmental issues are becoming increasingly severe, and remote sensing technology offers unique advantages, such as wide coverage, short revisit cycles, and low costs. These features make it a promising tool for large-scale earth observation, especially Synthetic Aperture Radar (SAR) technology. The fusion of multi-source remote sensing data can provide valuable information on land cover changes, surface subsidence, forest disturbances, and more. This integrated approach contributes to us generating a better understanding of environmental issues and enhances our ability to address and mitigate their impacts effectively.

This Special Issue focuses on all types of remote sensors designed for earth observation. Contributions addressing, but not limited to, the following topics are welcome to be submitted to this Special Issue:

  • Land Classification and Mapping;
  • Forest Classification and Mapping;
  • Forest Biomass Estimation;
  • Forest Height Estimation;
  • Multi-Source Remote Sensing Data Fusion;
  • Land Cover Change Detection;
  • Crop Classification and Mapping;
  • Crop Height Monitoring;
  • Farmland Soil Moisture Content Inversion.

Dr. Xing Peng
Dr. Qinghua Xie
Dr. Yanan Du
Dr. Bing Zhang
Guest Editors

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Keywords

  • remote sensing
  • synthetic aperture radar
  • land cover
  • earth observation
  • data fusion

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Published Papers (1 paper)

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Research

14 pages, 16915 KiB  
Article
Performance Assessment of Change Detection Based on Robust PCA for Wavelength Resolution SAR Images Using Nonidentical Flight Passes
by Lucas P. Ramos, Viet T. Vu, Mats I. Pettersson, Patrik Dammert, Leonardo T. Duarte and Renato Machado
Sensors 2025, 25(8), 2506; https://doi.org/10.3390/s25082506 - 16 Apr 2025
Viewed by 203
Abstract
One of the main challenges in Synthetic Aperture Radar (SAR) change detection involves using SAR images from different flight passes. Depending on the flight pass, objects have different specular reflections since the radar cross-sections of these objects can be totally different between passes. [...] Read more.
One of the main challenges in Synthetic Aperture Radar (SAR) change detection involves using SAR images from different flight passes. Depending on the flight pass, objects have different specular reflections since the radar cross-sections of these objects can be totally different between passes. Then, it is common knowledge that the flight passes must be close to identical for conventional SAR change detection. Wavelength-resolution SAR refers to a SAR system with a spatial resolution approximately equal to the wavelength. This high relative resolution helps to stabilize the ground clutter in the SAR images. Consequently, the restricted requirement about identical flight passes for SAR change detection can be relaxed, and SAR change detection becomes possible with nonidentical passes. This paper shows that robust principal component analysis (RPCA) is efficient for change detection even using wavelength-resolution SAR images acquired with very different flight passes. It presents several SAR change detection experimental results using flight pass differences up to 95°. For slightly different passes, e.g., 5°, our method reached a false alarm rate (FAR) of approximately one false alarm per square kilometer for a probability of detection (PD) above 90%. In a particular setting, it achieves a PD of 97.5% for a FAR of 0.917 false alarms per square kilometer, even using SAR images acquired with nonidentical passes. Full article
(This article belongs to the Special Issue Application of SAR and Remote Sensing Technology in Earth Observation)
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