Study of wetland sample discrimination using a long time series of SAR data

Wenhao Huo; Zheng Zhao; Jinqi Zhao

doi:10.1117/12.3024226

21 February 2024 Study of wetland sample discrimination using a long time series of SAR data

Wenhao Huo, Zheng Zhao, Jinqi Zhao

Proceedings Volume 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023); 1298806 (2024) https://doi.org/10.1117/12.3024226
Event: Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 2023, Xi’an, China

Abstract

The wetland is one of the most important ecosystems in the world, and monitoring its evolution is of great significance to protect wetland biodiversity and maintain ecosystem stability. This study aims to address the problem of low accuracy in salt marsh vegetation monitoring due to the difficulty of obtaining measured data in complex wetland areas. The Yellow River Delta serves as the test area in this study. The method for discriminating samples of dual-polarization time-series datasets is constructed by combining the time-weighted dynamic temporal warping algorithm and the DBSCAN clustering algorithm, using the intensity information provided by time-series Sentinel-1A images. On this basis, the support vector machine classifier is used to classify different polarized temporal datasets. Research shows that the sample discrimination method based on this article can extract wetland feature information. Among the classification results, the VV+VH polarization dataset exhibits the highest accuracy, with overall accuracy and Kappa coefficient of 88.734% and 0.857, respectively. These values are 2.43% and 0.025 higher than the classification accuracy of the VH polarization time series dataset relying only on visual discrimination samples. The research results in this paper provide a basis for decision-making on the restoration and protection of wetlands in the Yellow River Delta.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenhao Huo, Zheng Zhao, and Jinqi Zhao "Study of wetland sample discrimination using a long time series of SAR data", Proc. SPIE 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 1298806 (21 February 2024); https://doi.org/10.1117/12.3024226

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KEYWORDS

Polarization

Vegetation

Backscatter

Synthetic aperture radar

Visualization

Distance measurement

Support vector machines

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