Research on remote sensing monitoring method of water surface area in upper reaches of Jinsha River using multi-source data synergy

Abstract

[Objective] Multi-source data synergistic remote sensing is a crucial pathway for enhancing the monitoring frequency of river water bodies. However, the accuracy of river water body monitoring varies among satellites with different spatial resolutions,leading to uncertainties in the time-series analysis of river water bodies derived from multi-source satellite synergy. A quantitative evaluation of the accuracy differences in water surface area monitoring for river sections by satellites with different spatial resolutions, and the development of a correction model for multi-source satellite-based water surface area monitoring, hold significant importance for achieving high-precision, long-term, and high-frequency satellite synergistic monitoring of river water bodies. [Methods] Three river sections of the upper reaches of the Jinsha River with different channel patterns—Benzilan(straight, channel count index = 1), Shigu(anabranched, channel count index = 1~2), and Zhengkexiang(braided, channel count index = 2 ~ 6)—were selected as the study areas. Data acquired from the MS600 unmanned aerial vehicle( UAV),Landsat series satellites, Sentinel-1/2 satellites, GF-1/2/6 satellites, and HJ-2A/2B satellites were utilized as the main data sources. Spatiotemporally matched sample pairs of river water surface area were established by pairing high-spatial-resolution data with medium-to-high-spatial-resolution satellite data for the three river sections. The accuracy of water surface area monitoring using multi-source medium-to-high-resolution satellites for different river sections was validated, and correction models were constructed. Additionally, the monitoring accuracy of different satellites along with the model' s correction effectiveness were quantitatively evaluated. The factors influencing the accuracy of multi-source satellite monitoring for river sections, the applicability of correction models, and the advantages of multi-source collaborative monitoring were explored. [Results] The result showed that the RMSE of multi-source satellite-monitored water surface area for the Zhengkexiang, Shigu, and Benzilan river sections ranged from 0. 180 9 km² to 0. 706 8 km², 0. 040 8 km² to 0. 096 3 km², and 0. 015 8 km² to 0. 041 4 km²,respectively. After model correction, the average MAPE of Landsat-8/9 OLI, Sentinel-2 MSI, Sentinel-1 SAR, and the 16-meter domestic satellites across the three river sections reduced from 14. 16%, 7. 26%, 20. 06%, and 9. 37% to 10. 30%, 5. 33%,7. 59%, and 7. 32%, respectively. The standard deviation of the differences between the water surface area monitored by multisource satellite synergy and the reference values decreased from 0. 221 8 km², 0. 037 4 km², and 0. 019 1 km² to 0. 159 1 km²,0. 023 4 km², and 0. 012 8 km². The effective monitoring frequency increased from an average of 12 times per year to 260 times per year. Furthermore, the relationships between river water body monitoring accuracy and factors such as satellite spatial resolution, satellite sensor type, and channel morphology were analyzed. [Conclusion] The result demonstrate significant differences in the accuracy of water body monitoring for different morphologies of river sections using satellites of different spatial resolutions. Satellite spatial resolution, satellite sensor type, and the complexity of river section morphology are identified as important factors influencing the accuracy of river water surface area monitoring. The correction model for multi-source satellite remote sensing of water surface area can improve both the accuracy and consistency of water surface area monitoring for river sections from satellites with different spatial resolutions. Multi-source satellite synergistic monitoring can significantly enhance the monitoring frequency of river section water bodies. The research findings have potential for broader application in aspects such as the long-term reconstruction of river water surface area, water level and discharge monitoring, and hydrological model calibration.

Keywords

multi-source data synergy / remote sensing monitoring of river water bodies / upper reaches of Jinsha River / accuracy verification / correction model / applicability / synergistic advantage / influencing factors