研究目的
To observe and analyze the evolution of sinkholes over Wink, Texas, using high-resolution optical and SAR imagery, and to understand the mechanisms behind sinkhole development and deformation.
研究成果
The sinkholes in Wink, Texas, are influenced by both anthropogenic activities (e.g., hydrocarbon production, improper well management) and natural factors (e.g., drought-induced fractures). High-resolution imagery effectively monitors deformation, revealing ongoing subsidence and potential geohazards. Continuous monitoring is recommended to mitigate risks, and the methods can be applied to other sinkhole-prone areas.
研究不足
The study is limited by the spatial and temporal resolution of available data; low-resolution sensors may miss small deformations. Subsurface fractures cannot be directly confirmed with remote sensing alone, requiring inferential analysis. The linear assumption in deformation may not hold over longer periods, and predictive capabilities for future collapses are uncertain.
1:Experimental Design and Method Selection:
The study uses high-resolution aerial photography and SAR interferometry (InSAR) with TerraSAR-X in staring spotlight mode to monitor sinkhole deformations. The small baseline subset (SBAS) method is employed for time-series analysis.
2:Sample Selection and Data Sources:
Data include aerial ortho-rectified photography from the National Agriculture Imagery Program (NAIP) for 2004-2016 and TerraSAR-X scenes from October 2015 to March
3:Hydrocarbon production records from Texas RRC and drillinginfo?, and groundwater data from Texas Water Development Board are used. List of Experimental Equipment and Materials:
20 Equipment includes TerraSAR-X satellite for SAR data, aerial cameras for photography, and software for InSAR processing and modeling.
4:Experimental Procedures and Operational Workflow:
Aerial images are analyzed to delineate sinkhole areas. InSAR pairs are processed to generate interferograms and time-series deformation maps. Deformation is modeled using Okada formulation for subsurface cavities.
5:Data Analysis Methods:
Statistical analysis of deformation rates, modeling of subsurface cavities, and correlation with environmental data (e.g., precipitation, groundwater levels) are performed.
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