Automated grounding line delineation using deep learning and phase gradient-based approaches on COSMO-SkyMed DInSAR data

This repository contains the file 'Natalya_Maslennikova_data_2024.zip,' which includes 171 DInSAR interferograms (both phase and coherence of a DInSAR signal) and three versions of the grounding lines: manually mapped ('gl_manual_mapping.shp'), mapped by the neural network ('gl_neural_network.shp'), and mapped using the phase gradient-based approach ('gl_phase_gradient.shp'). The X-band DInSAR data were acquired by the ASI’s COSMO-SkyMed mission between 2020 and 2022 over five East Antarctica glaciers: Stancomb-Wills (STA: 32 interferograms), Veststraumen (VES: 35 interferograms), Jutulstraumen (JUT: 42 interferograms), Moscow University (MOS: 27 interferograms), and Rennick (REN: 35 interferograms). The 'gl_neural_network.shp' and 'gl_phase_gradient.shp' shapefiles contain the following fields: the name of the glacier (the 'Glacier' column), four dates in YYYYMMDD format when the corresponding DInSAR interferogram was acquired (the 'Primary1', 'Secondary1', 'Primary2', 'Secondary2' columns), and the double difference name in 'Primary1_Secondary1-Primary2_Secondary2' format (the 'DD' column). The 'gl_manual_mapping.shp' shapefile contains 'Glacier', 'Primary1', 'Secondary1', 'Primary2', 'Secondary2', and 'DD' columns as well, along with the 'Revisit' column (difference in days between the 'Primary1' and 'Primary2' images were acquired), the 'Time' column (acquisition time in 'HHMMSS' format), the 'Coherence' column (average coherence of the corresponding DInSAR interferogram), and the 'Train_1', 'Train_2', 'Train_3' columns, which contain indicators 'Y' for 'yes' and 'N' for 'no', showing whether or not the DInSAR interferogram was used in the corresponding training session.本仓库包含文件'Natalya_Maslennikova_data_2024.zip'，该压缩包内含171幅差分合成孔径雷达干涉（Differential Interferometric Synthetic Aperture Radar，DInSAR）干涉图（包含DInSAR信号的相位与相干性数据），以及三类冰架接地线数据：人工手动绘制版（'gl_manual_mapping.shp'）、神经网络绘制版（'gl_neural_network.shp'）、基于相位梯度法绘制版（'gl_phase_gradient.shp'）。本次采集的X波段DInSAR数据由意大利空间局（Agenzia Spaziale Italiana，ASI）的COSMO-SkyMed卫星任务于2020至2022年间获取，覆盖南极东部五处冰川：斯坦科姆-威尔斯冰川（Stancomb-Wills，STA：32幅干涉图）、韦斯特斯特劳门冰川（Veststraumen，VES：35幅干涉图）、于图尔斯特劳门冰川（Jutulstraumen，JUT：42幅干涉图）、莫斯科大学冰川（Moscow University，MOS：27幅干涉图）以及伦尼克冰川（Rennick，REN：35幅干涉图）。 'gl_neural_network.shp'与'gl_phase_gradient.shp'矢量文件包含以下字段：冰川名称字段（'Glacier'列）、对应DInSAR干涉图的四幅采集日期（格式为YYYYMMDD，对应'Primary1'、'Secondary1'、'Primary2'、'Secondary2'列），以及格式为'Primary1_Secondary1-Primary2_Secondary2'的双差分名称字段（'DD'列）。'gl_manual_mapping.shp'矢量文件同样包含'Glacier'、'Primary1'、'Secondary1'、'Primary2'、'Secondary2'与'DD'列，此外还增设如下字段：'Revisit'列（记录'Primary1'与'Primary2'图像的采集日期间隔天数）、'Time'列（采集时间，格式为HHMMSS）、'Coherence'列（对应DInSAR干涉图的平均相干性），以及'Train_1'、'Train_2'、'Train_3'列：该类字段以'Y'代表“是”、'N'代表“否”，用于标注该DInSAR干涉图是否被用于对应训练环节。