Slope deformation velocities and controlling factors (Original data)
Description
Research hypothesis We hypothesize that slope instability in mining-affected landscapes is jointly controlled by geological, topographic, climatic, and anthropogenic factors, and that deformation patterns derived from InSAR can be systematically linked to these variables. In particular, intermittently unstable slopes are expected to show periodic responses to dynamic environmental forcing (e.g., rainfall, temperature, snow cover, vegetation). Data description This dataset contains slope-unit based deformation velocities and associated variables in the Datong Coalfield, China, derived from multi-temporal SBAS-InSAR analysis between May 2019 and April 2025. The data are organized into three groups: Mean deformation and variables (TS1, TS2, TWs) Slopes_DeformationVelocity_Variables_TS1.xlsx: Mean LOS deformation velocities (mm/year) and controlling variables for each slope unit during TS1 (2019–2022). Slopes_DeformationVelocity_Variables_TS2.xlsx: Same as above for TS2 (2022–2025). Slopes_DeformationVelocity_Variables_TWs.xlsx: Slope-unit deformation and variables across 12 short-term time windows (TWs). Time series of deformation vs. dynamic variables Deformation_vs_Variables_StableSlopes.xlsx: 2019–2025 deformation and environmental variables for slope units classified as stable. Deformation_vs_Variables_IntermittentlyUnstableSlopes.xlsx: Same for intermittently unstable slopes. Deformation_vs_Variables_UnstableSlopes.xlsx: Same for unstable slopes. Each file is provided in Excel .xlsx format, with rows representing slope units and columns representing deformation velocities and variables (slope angle, aspect, lithology, distance to faults, distance to mines, mine density, rainfall, land surface temperature, snow cover, NDVI). Notable findings Mean deformation velocities allowed classification of slope units into stable, intermittently unstable, and unstable categories using a 10 mm/year threshold. Long-term modeling showed that geological and topographic factors exert persistent influences, while climatic and anthropogenic variables displayed greater temporal variability. Intermittently unstable slopes exhibited periodic lagged associations with rainfall, temperature, snow cover, and vegetation activity. Interpretation and use The dataset provides slope-unit scale information suitable for: Investigating the controls of slope instability in mining-affected landscapes. Developing new methods for spatiotemporal analysis of slope deformation. Cross-referencing with independent datasets (e.g., precipitation, geology, mining activity). Data gathering Surface deformation was derived from Sentinel-1 SAR images processed with the SBAS-InSAR technique. Static variables were extracted from DEMs, geological maps, and mining activity datasets. Dynamic variables (rainfall, LST, snow cover, NDVI) were obtained from remote sensing and meteorological products. All variables were aggregated to slope units delineated using GRASS GIS.