异构卫星遥感数据融合的水深反演模型

doi:10.13474/j.cnki.11-2246.2024.0504

摘要/Abstract

摘要： 为探究影像分辨率和水深反演模型对异构卫星数据融合水深反演结果的影响,本文将ICESat-2激光测高数据分别与多时相Landsat 8、Sentinel-2及WorldView-3卫星数据相融合,利用对数比值模型、多波段模型、BP神经网络、支持向量机、随机森林和极限梯度提升进行水深反演。试验结果表明,影像空间分辨率对水深反演结果精度影响不显著,且综合考虑反演结果的精度和分辨率,Sentinel-2卫星数据性能最佳,同时极限梯度提升相较于其他模型的反演性能最优,其在东沙环礁试验区域的水深反演结果RMSE最优可达0.51m。该结果对基于异构遥感卫星数据融合的近岸区域水深测量具有很好的参考价值。

关键词: 水深反演, 多光谱卫星遥感影像, 冰、云和陆地高程卫星, 数据融合, 对比分析

Abstract: To investigate the impact of image resolution and bathymetry models on the fusion of heterogeneous satellite data for depth inversion, this study integrates ICESat-2 laser altimetry data with multi-temporal Landsat 8, Sentinel-2, and WorldView-3 satellite data. Depth inversion is performed using logarithmic ratio model, multi-band model, BP neural network, support vector machine, random forest, and extreme gradient boosting. Experimental results show that the spatial resolution of the images has an insignificant effect on the accuracy of depth inversion. Considering both the accuracy and resolution of the inversion results, Sentinel-2 satellite data performs the best. Moreover, the XGBoost model outperforms other models in terms of inversion performance, achieving an optimal RMSE of 0.51 meters in the Dongsha Atoll experimental area. These results provide valuable reference for coastal depth measurement based on the fusion of heterogeneous remote sensing satellite data.

Key words: water depth retrieval, multispectral satellite remote sensing imagery, ICESat-2, data fusion, contrastive analysis

中图分类号:

P237

郭松涛, 邢帅, 张国平, 孔瑞瑶, 陈丽. 异构卫星遥感数据融合的水深反演模型[J]. 测绘通报, 2024, 0(5): 19-23.

GUO Songtao, XING Shuai, ZHANG Guoping, KONG Ruiyao, CHEN Li. Bathymetric inversion model for fusion of heterogeneous satellite remote sensing data[J]. Bulletin of Surveying and Mapping, 2024, 0(5): 19-23.

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