InSAR Modeling and Deformation Prediction for Salt Solution Mining Using a Novel CT-PIM Function

Abstract

Deformation prediction for a salt solution mining area is essential to mining environmental protection. The combination of Synthetic Aperture Radar Interferometry (InSAR) technique with Probability Integral Method (PIM) has proven to be powerful in predicting mining-induced subsidence. However, traditional mathematical empirical models (such as linear model or linear model combined with periodical function) are mostly used in InSAR approaches, ignoring the underground mining mechanisms, which may limit the accuracy of the retrieved deformations. Inaccurate InSAR deformations will transmit an unavoidable error to the estimated PIM parameters and the forward predicted subsidence, which may induce more significant errors. Besides, theoretical contradictory and non-consistency between InSAR deformation model and future prediction model is another limitation. This paper introduces the Coordinate-Time (CT) function into InSAR deformation modeling. A novel time-series InSAR model (namely, CT-PIM) is proposed as a substitute for traditional InSAR mathematical empirical models and directly applied for future dynamic prediction. The unknown CT-PIM parameters can be estimated directly via InSAR phase observations, which can avoid the error propagation from the InSAR-generated deformations. The new approach has been tested by both simulated and real data experiments over a salt mine in China. The root mean square error (RMSE) is determined as ±10.9 mm, with an improvement of 37.2% compared to traditional static PIM prediction method. The new approach provides a more robust tool for the forecasting of mining-induced hazards in salt solution mining areas, as well as a reference for ensuring the environment protection and safety management.

Interannual Variation of Landfast Ice Using Ascending and Descending Sentinel-1 Images from 2019 to 2021: A Case Study of Cambridge Bay

“…The majority of average coherence values were within the range of [0.3, 0.4]. The coherence level of landfast ice in the present work was evidently lower than those of traditional research objects, such as roads, bridges, mining areas, and earthquakes [52,53]. The factors for decorrelation could mostly be attributed to the physical properties of the ice, which was susceptible to temperature, wind, and precipitation.…”

InSAR-CTPIM-Based 3D Deformation Prediction in Coal Mining Areas of the Baisha Reservoir, China

“…This technique is used to invert the LOS deformation of the area by solving the deformation of a large number of dense, high-coherence points in the area. Assuming that N + 1 SAR images of the study area are acquired and M differential interferograms are generated [20,21], the phase of the i-th pixel on the m-th (1 ≤ m < M) differential interferogram can be expressed as follows [22]:…”

Quantitative Prediction for Deformation and Brine Extraction in Salt Solution Mining Based on Water-Solution Kinetic (WSK) InSAR Model

“…where g represents the average content of the primary brine composition. Substituting ( 11) into (10), it can be derived: G , E , and g can be determined by investigating the geological structure of the study area [33]- [35]. According to (1), the total amount of brine Q at time t can be written as:…”

“…The space parameters of the Sentinel-1 A SAR images have been used for the simulation of the satellite parameters. The geological parameters were set as   (60, 60) rand is total simulated size of the phase function by random noise function [32] - [33]. The WSK parameters can be estimated by LSIC, which can be used to generate the predicted time series subsidence field.…”