| Citation: |
YE Shirong, LUO Xinqi, NAN Yang, XIA Pengfei. An Improved Sea Ice Detection Method Based on Spaceborne GNSS-R Using CNN[J]. Geomatics and Information Science of Wuhan University, 2024, 49(1): 90-99. DOI: 10.13203/j.whugis20220585
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Convolutional neural network (CNN) has been used in spaceborne global navigation satellite system-reflectometry（GNSS-R） sea ice detection, which has the advantages of simple data preprocessing and maximum retention of reflector information. However, the data sets used in previous studies of the GNSS-R CNN sea ice detection method have a small span in time and limited representativeness, and the influence of the delay-Doppler map (DDM) ratio of seawater and sea ice in the training set on the generalization ability of the method is not considered.
To solve these problems, a method of screening out malformed DDM is proposed.The appropriate CNN structure and parameters are designed, and the dataset selection strategy is optimized through comparative tests of small samples. A large sample dataset from 2018 is used to evaluate the validity and reliability of the improved method in the case of large data volume and large time.
The results show that the proposed method can screen the wrong data effectively. The CNN model has high accuracy and the best generalization ability when the DDM ratio of seawater and sea ice in the training set is 1∶1, and the improved method is still effective and reliable in large data volume and large time span. The improved method improves the generalization ability and reliability of the CNN sea ice detection method by strengthening data quality control and optimizing the dataset selection strategy, to make it more applicable to practical application scenarios and provide a reference for studies on sea ice melting.
| [1] |
刘婷婷, 杨子健, 王泽民, 等. 利用风云3D微波成像仪数据估算北极海冰密集度的精度评价[J]. 武汉大学学报（信息科学版）, 2021, 46（12）： 1843-1851.
Liu Tingting, Yang Zijian, Wang Zemin, et al. Evaluation of Arctic Sea Ice Concentration Estimated by Fengyun-3D Microwave Radiation Imager[J]. Geomatics and Information Science of Wuhan University, 2021, 46（12）： 1843-1851.
|
| [2] |
柯长青, 彭海涛, 孙波, 等. 2002—2011年北极海冰时空变化分析[J]. 遥感学报, 2013, 17（2）： 459-466.
Ke Changqing, Peng Haitao, Sun Bo, et al. Spatiotemporal Variability of Arctic Sea Ice from 2002 to 2011[J]. Journal of Remote Sensing, 2013, 17（2）： 459-466.
|
| [3] |
张明, 吕晓琪, 张晓峰, 等. 结合纹理特征的SVM海冰分类方法研究[J]. 海洋学报, 2018, 40（11）： 149-156.
Zhang Ming, Xiaoqi Lü, Zhang Xiaofeng, et al. Research on SVM Sea Ice Classification Based on Texture Features[J]. Acta Oceanologica Sinica, 2018, 40（11）： 149-156.
|
| [4] |
孟婉婷. 基于GNSS反射信号的海冰检测的研究[D]. 上海： 上海海洋大学,2016.
MengWanting. Research on Sea Ice Detection Based on GNSS Reflected Signal[D]. Shanghai： Shanghai Ocean University, 2016.
|
| [5] |
杨东凯, 李晓辉, 王峰. GNSS反射信号海洋遥感应用现状分析[J]. 无线电工程, 2019, 49（10）：843-848.
Yang Dongkai, Li Xiaohui, Wang Feng. Analysis of Application Status of GNSS Reflected Signal in Ocean Remote Sensing[J]. Radio Engineering, 2019, 49（10）：843-848.
|
| [6] |
HallC D, CordeyR A. Multistatic Scatterometry[C]//International Geoscience and Remote Sensing Symposium, Remote Sensing： Moving Toward the 21st Century, Edinburgh, UK, 2002.
|
| [7] |
Martín-Neira M. A Pasive Reflectometry and Interferometry System （PARIS） Application to Ocean Altimetry[J]. ESA Journal, 1993, 17（4）： 331-355.
|
| [8] |
Zavorotny V U, Voronovich A G. Scattering of GPS Signals from the Ocean with Wind Remote Sensing Application[J]. IEEE Transactions on Geoscience and Remote Sensing,2000, 38（2）： 951-964.
|
| [9] |
杜皓, 郭文飞, 郭迟, 等. 针对GNSS-R海面风速反演的自适应CDF匹配方法[J]. 武汉大学学报（信息科学版）, 2021, 46（12）： 1924-1931.
Du Hao, Guo Wenfei, Guo Chi, et al. Adaptively CDF Matching Method in GNSS-R Wind Speed Retrieval[J]. Geomatics and Information Science of Wuhan University, 2021, 46（12）： 1924-1931.
|
| [10] |
万玮, 李黄, 洪阳, 等. GNSS-R遥感观测模式及陆面应用[J]. 遥感学报, 2015, 19（6）：882-893.
Wan Wei, Li Huang, Hong Yang, et al. Definition and Application of GNSS-R Observation Patterns[J]. Journal of Remote Sensing, 2015, 19（6）：882-893.
|
| [11] |
张国栋, 郭健, 杨东凯, 等. 星载GNSS-R海冰边界探测方法[J]. 武汉大学学报（信息科学版）, 2019, 44（5）： 668-674.
Zhang Guodong, Guo Jian, Yang Dongkai, et al. Sea Ice Edge Detection Using Spaceborne GNSS-R Signal[J]. Geomatics and Information Science of Wuhan University, 2019, 44（5）： 668-674.
|
| [12] |
严颂华, 唐凤雨, 陈永谦, 等. GNSS-R形变监测技术综述[J]. 无线电工程, 2021, 51（10）：1086-1092.
Yan Songhua, Tang Fengyu, Chen Yongqian, et al. Review of Deformation Monitoring Based on GNSS-R Technology[J]. Radio Engineering, 2021, 51（10）：1086-1092.
|
| [13] |
Di Simone A, Park H, Riccio D, et al. Sea Target Detection Using Spaceborne GNSS-R Delay-Doppler Maps： Theory and Experimental Proof of Concept Using TDS-1 Data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10（9）： 4237-4255.
|
| [14] |
朱勇超, 邹进贵, 余科根. 一种使用卫星反射信号探测海冰分布新方法[J]. 武汉大学学报（信息科学版）, 2018, 43（10）： 1472-1477.
Zhu Yongchao, Zou Jingui, Yu Kegen. A New Sea Ice Distribution Detection Method Using GNSS Reflected Signals[J]. Geomatics and Information Science of Wuhan University, 2018, 43（10）： 1472-1477.
|
| [15] |
Unwin M, Jales P, Tye J, et al. Spaceborne GNSS-Reflectometry on TechDemoSat-1： Early Mission Operations and Exploitation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9（10）： 4525-4539.
|
| [16] |
Zhu Y C, Yu K G, Zou J G, et al. Sea Ice Detection Based on Differential Delay-Doppler Maps from UK TechDemoSat-1[J]. Sensors, 2017, 17（7）： 1614.
|
| [17] |
Ruf C, Chang P, Clarizia M P, et al. CYGNSS Handbook[M]. Ann Arbor：Michigan Pub., 2016.
|
| [18] |
SunY Q, WangX Y, DuQ F, et al. The Status and Progress of Fengyun-3e GNOS II Mission for GNSS Remote Sensing[C]// IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019.
|
| [19] |
Zhang P, Hu X Q, Lu Q F, et al. FY-3E： The First Operational Meteorological Satellite Mission in an Early Morning Orbit[J]. Advances in Atmospheric Sciences, 2022, 39（1）： 1-8.
|
| [20] |
Jing C, Niu X L, Duan C D, et al. Sea Surface Wind Speed Retrieval from the First Chinese GNSS-R Mission： Technique and Preliminary Results[J]. Remote Sensing, 2019, 11（24）： 3013.
|
| [21] |
Foti G, Gommenginger C, Jales P, et al. Spaceborne GNSS Reflectometry for Ocean Winds： First Results from the UK TechDemoSat-1 Mission[J]. Geophysical Research Letters, 2015, 42（13）： 5435-5441.
|
| [22] |
Chew C, Shah R, Zuffada C, et al. Demonstrating Soil Moisture Remote Sensing with Observations from the UK TechDemoSat-1 Satellite Mission[J]. Geophysical Research Letters,2016,43（7）：3317-3324.
|
| [23] |
Li W Q, Cardellach E, Fabra F, et al. First Spaceborne Phase Altimetry over Sea Ice Using TechDemoSat-1 GNSS-R Signals[J]. Geophysical Research Letters, 2017, 44（16）： 8369-8376.
|
| [24] |
Yan Q Y, Huang W M. Spaceborne GNSS-R Sea Ice Detection Using Delay-Doppler Maps： First Results from the U.K. TechDemoSat-1 Mission[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9（10）： 4795-4801.
|
| [25] |
Alonso-Arroyo A, Zavorotny V U, Camps A. Sea Ice Detection Using UK TDS-1 GNSS-R Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55（9）： 4989-5001.
|
| [26] |
朱勇超. 星载GNSS-R海冰检测与海冰密集度反演方法研究[D]. 武汉：武汉大学, 2018.
ZhuYongchao. Study of Spaceborne GNSS-R for Sea Ice Detection and Sea Ice Concentration Retrieval Methods[D]. Wuhan： Wuhan University, 2018.
|
| [27] |
Yan Q Y, Huang W M, Moloney C. Neural Networks Based Sea Ice Detection and Concentration Retrieval from GNSS-R Delay-Doppler Maps[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10（8）： 3789-3798.
|
| [28] |
Yan Q Y, Huang W M. Sea Ice Sensing from GNSS-R Data Using Convolutional Neural Networks[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15（10）： 1510-1514.
|
| [29] |
Yan Q Y, Huang W M. Detecting Sea Ice from TechDemoSat-1 Data Using Support Vector Machines with Feature Selection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12（5）： 1409-1416.
|
| [30] |
邵连军, 胡磊, 李冰, 等. 基于CART决策树的星载GNSS-R海冰检测方法[J]. 海洋测绘, 2021, 41（1）：70-74.
Shao Lianjun, Hu Lei, Li Bing, et al. Sea Ice Detection Using Spaceborne GNSS-R Data by CART Decision Tree[J]. Hydrographic Surveying and Charting, 2021, 41（1）：70-74.
|
| [31] |
杨真真, 匡楠, 范露, 等. 基于卷积神经网络的图像分类算法综述[J]. 信号处理, 2018, 34（12）： 1474-1489.
Yang Zhenzhen, Kuang Nan, Fan Lu, et al. Review of Image Classification Algorithms Based on Convolutional Neural Networks[J]. Journal of Signal Processing, 2018, 34（12）： 1474-1489.
|
| [32] |
吴正文. 卷积神经网络在图像分类中的应用研究[D]. 成都： 电子科技大学, 2015.
WuZhengwen. Research on the Application of Convolutional Neural Network in Image Classification[D]. Chengdu： University of Electronic Science and Technology of China, 2015.
|
| [33] |
Peng X, Zhang X, Li Y, et al. Research on Image Feature Extraction and Retrieval Algorithms Based on Convolutional Neural Network[J]. Journal of Visual Communication and Image Representation, 2020, 69： 102705.
|
| [34] |
Wang K G, Debernard J, Sperrevik A K, et al. A Combined Optimal Interpolation and Nudging Scheme to Assimilate OSISAF Sea-Ice Concentration into ROMS[J]. Annals of Glaciology, 2013, 54（62）： 8-12.
|
| [35] |
Cardellach E, Li W Q, Rius A, et al. First Precise Spaceborne Sea Surface Altimetry with GNSS Reflected Signals[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 13： 102-112.
|
| [36] |
杨东凯, 张其善. GNSS反射信号处理基础与实践[M].北京：电子工业出版社, 2012.
Yang Dongkai, Zhang Qishan. GNSS Reflected Signal Processing： Fundamentals and Applications[M]. Beijing： Publishing House of Electronics Industry, 2012.
|
| [37] |
Clarizia M P, Ruf C S. Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System （CYGNSS） Mission[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54（8）： 4419-4432.
|
| [38] |
高震宇. 基于深度卷积神经网络的图像分类方法研究及应用[D]. 合肥： 中国科学技术大学, 2018 .
GaoZhenyu. Research and Application of Image Classification Method Based on Deep Convolution Neural Network[D]. Hefei： University of Science and Technology of China, 2018 .
|
| [39] |
LeCun Y, Bottou L, Bengio Y, et al. Gradient-Based Learning Applied to Document Recognition[J].Proceedings of the IEEE,1998,86（11）： 2278-2324.
|
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