Dataset for "Unraveling Surface Subsidence Mechanisms in Typical Oil Production Areas of Songyuan City by Integrating Time-Series InSAR and Deep Learning"

This dataset serves as the data source for the paper "Unraveling Surface Subsidence Mechanisms in Typical Oil Production Areas of Songyuan City by Integrating Time-Series InSAR and Deep Learning," forming the foundation for data processing and analysis in this study. It primarily consists of three files: DEM Data.zip, containing DEM data for the study area used in PS-InSAR data processing; Sentinel-1 SAR Data.docx: This file contains Sentinel-1 SAR imagery covering the study area for PS-InSAR data processing. Due to the large data volume, this file only lists image parameters, phase numbers, download links, and other relevant information; 2019-2020LevelingBenchmark.xlsx: This file contains 2019-2020 leveling data for selected points within the study area, used to validate the data validity of PS-InSAR. We are grateful for the data provided by the European Space Agency and United States Geological Survey. We extend our gratitude to the authors of the papers for their contributions to level data measurement. We also thank you for your reading and recognition.