Quantitative remote sensing inversion and spatial-temporal analysis of suspended sediment concentration in the Yellow River estuary based on QAA algorithm

Ruixiang Liu; Jianzhong Feng; Shu Zhang; Linyan Bai; Xiangwei Gao; Jun Zou

doi:10.1117/12.3020966

19 January 2024 Quantitative remote sensing inversion and spatial-temporal analysis of suspended sediment concentration in the Yellow River estuary based on QAA algorithm

Ruixiang Liu, Jianzhong Feng, Shu Zhang, Linyan Bai, Xiangwei Gao, Jun Zou

Author Affiliations +

Proceedings Volume 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023); 129801Q (2024) https://doi.org/10.1117/12.3020966
Event: Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 2023, Lianyungang, China

Abstract

The concentration of suspended solids is a critical parameter for water bodies, impacting optical properties like transparency and color, as well as the overall ecological environment. In this study, the field measurement data of total suspended matter concentration obtained from the sea area near the Yellow River estuary is used to train the inversion model of total suspended matter concentration and carry out the accuracy verification of the model inversion. Firstly, the inherent optical properties are calculated using the QAA algorithm based on Sentinel-2 data; then a linear regression model is established with the field-measured suspended matter concentration data, thereby inverting the suspended matter concentration. The model's validation accuracy, with an R 2 of 0.5557, demonstrates its effectiveness. The suspended matter concentration in the Yellow River estuary has obvious spatiotemporal characteristics: the suspended matter concentration in the Yellow River estuary is relatively high, and the concentration gradually decreases from the estuary outward; seasonally, the distribution of suspended matter concentration changes is high in summer and winter, and low in spring and autumn.

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

Citation Download Citation

Ruixiang Liu, Jianzhong Feng, Shu Zhang, Linyan Bai, Xiangwei Gao, and Jun Zou "Quantitative remote sensing inversion and spatial-temporal analysis of suspended sediment concentration in the Yellow River estuary based on QAA algorithm", Proc. SPIE 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 129801Q (19 January 2024); https://doi.org/10.1117/12.3020966

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