基于D-InSAR技术的时间序列雪深反演方法探索研究  

Exploratory Study of Time Series Snow Depth Inversion Method based on D-InSAR Technique

作　　者：史佳鑫 车涛[1] 戴礼云[1] 王静[1,2] SHI Jiaxin;CHE Tao;DAI Liyun;WANG Jing(Northwest Institute of Eco-environment and Resources,Key Laboratory of Remote Sensing of Gansu Province,Heihe Remote Sensing Experimental Research Station,Chinese Academy of Sciences,Lanzhou 730000,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院西北生态资源环境研究院,中国科学院黑河遥感试验研究站,甘肃省遥感重点实验室,甘肃兰州730000 [2]中国科学院大学,北京100049

出　　处：《遥感技术与应用》2024年第6期1383-1391,共9页Remote Sensing Technology and Application

基　　金：国家自然科学基金项目(42125604、42171143)。

摘　　要：积雪是全球能量平衡、气候变化的重要物理变量,遥感技术是积雪监测的主要手段。作为主动微波遥感的主要技术之一,合成孔径雷达(SAR)可以不受天气条件影响成像反演积雪深度。早期的SAR空间分辨率高但时间分辨率低,无法进行雪深的时间序列反演,随着新一代SAR卫星的研制与发射,时间分辨率有了较大提高,为雪深的时间序列分析提供了支持。研究选用高分辨率Sentinel-1数据,基于D-InSAR技术,通过相位离散指数阈值提取,结合光学影像以及高相干系数区校正解缠相位,探索了时间序列雪深反演方法,成功反演了新疆北部乌苏地区积雪积累期11 d的雪深分布,根据积雪站点逐日实测雪深资料探讨了雪深反演误差来源。结果表明:①通过相位离散指数阈值提取并结合光学影像以及高相干系数区校正解缠相位,可以得到较好的雪深反演结果;(2)雪深整体反演结果精度相关系数R为0.93,均方根误差RMSE为3.98 cm,平均相对误差MAPE为25.49%;③由于像对相干性和积雪内部性质的差异,积雪较浅时反演精度较高,多数反演雪深值低于雪深实测值,当站点观测雪深大于17 cm时开始出现大的误差,最大误差约为7.3 cm。差异分析发现,雪深反演精度受干涉像对相干性及实际雪深的差异影响显著。光学影像与SAR影像时间分辨率的不一致也可能是雪深反演误差的因素之一。本文所用到方法能够利用SAR数据进行较好的时间序列雪深估计,为基于D-InSAR雪深时间序列反演提供参考。Snow depth is an important physical variable in global energy balance and climate change,and accurate snow depth parameters are crucial for global and regional climate and hydrological studies.Active microwave remote sensing has high spatial resolution and is suitable for basin-scale snow depth inversion.As one of the key technologies of active microwave remote sensing,Synthetic Aperture Radar(SAR)can image regardless of weather conditions.However,early SAR systems,while offering high spatial resolution,had low temporal resolution,which made it impossible to perform time-series inversion of snow depth.With the development and launch of new generation SAR satellites,there has been a significant improvement in temporal resolution,providing support for time-series analysis of snow depth.In this study,we selected high-resolution Sentinel-1 data,extracted the phase discretization index threshold,combined with the optical image and high coherence coefficient area,and explored a time series snow depth inversion method based on D-InSAR technology,which successfully inverted the distribution of snow depth in the Wusu area of the northern slope of Tianshan Mountain in the snow accumulation period of 11 days.Sources of snow depth estimation errors are explored based on daily measured snow depth data from three meteorological stations.The study demonstrates that relatively accurate snow depth inversion results can be achieved by employing a phase discretization index threshold extraction method,in conjunction with optical imagery and high-coherence areas for correcting the unwrapped phase.is 0.93,the Root Mean Square Error(RMSE)is 3.98 cm,and the Mean Absolute Percentage Error(MAPE)is 25.49%.Due to differences in interferogram pair coherence and internal properties of the snow,the accuracy of the inversion results was higher when the snow was shallow,with most inverted snow depths being lower than the measured values.Large errors began to appear when the station-observed snow depth exceeded 17 cm,with the maximum error being

关 键 词：雪深 遥感 主动微波 SAR 时间序列分析 

分 类 号：P412[天文地球—大气科学及气象学] P426.635