Publication Date

5-2020

Abstract

Sinkholes in west-central Florida are usually formed from the erosion of overlying soil and sediment into open fissures of dissolved limestone bedrock. They are one of the leading natural disasters in the area, and therefore, precursory detection is crucial to alleviate risks of property damage. Using the Interferometric Synthetic Aperture Radar (InSAR) method, we can detect surface subsidence in selected study areas over which InSAR scenes were captured every 22–45 days over ~two years. InSAR is an airborne remote sensing technique that uses multiple Synthetic Aperture Radar (SAR) images to resolve elevation changes over time. Using the Persistent Scatterer Interferometry (PSI) method, processed InSAR datasets can be used to create time-series datasets of localized subsidence. We complete a statistical analysis to determine if individual InSAR time series points show evidence of discontinuous behavior (as might be expected for sinkhole activity), which could be indicated by a slope break within the time-series. These time-series points with statistically identified slope breaks are compared against other terrain data. We examine the relationship between subsidence rates and distance from surface water features identified from both aerial images from 1944 and present surface water features from the USDA database. The proximity of InSAR points to surface water features was determined using the NEAR analysis technique in ArcGIS Pro. This analysis shows a weak correlation between subsidence rates and distance to both past and present surface water features. We also examined how subsidence rates relate to the elevation of the study area. This analysis shows no correlation between subsidence rate and local elevation.

DOI

https://doi.org/10.5038/9781733375313.1005

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Relationships between Sinkhole-related features and activity and InSAR-detected Subsidence Points in West Central Florida

Sinkholes in west-central Florida are usually formed from the erosion of overlying soil and sediment into open fissures of dissolved limestone bedrock. They are one of the leading natural disasters in the area, and therefore, precursory detection is crucial to alleviate risks of property damage. Using the Interferometric Synthetic Aperture Radar (InSAR) method, we can detect surface subsidence in selected study areas over which InSAR scenes were captured every 22–45 days over ~two years. InSAR is an airborne remote sensing technique that uses multiple Synthetic Aperture Radar (SAR) images to resolve elevation changes over time. Using the Persistent Scatterer Interferometry (PSI) method, processed InSAR datasets can be used to create time-series datasets of localized subsidence. We complete a statistical analysis to determine if individual InSAR time series points show evidence of discontinuous behavior (as might be expected for sinkhole activity), which could be indicated by a slope break within the time-series. These time-series points with statistically identified slope breaks are compared against other terrain data. We examine the relationship between subsidence rates and distance from surface water features identified from both aerial images from 1944 and present surface water features from the USDA database. The proximity of InSAR points to surface water features was determined using the NEAR analysis technique in ArcGIS Pro. This analysis shows a weak correlation between subsidence rates and distance to both past and present surface water features. We also examined how subsidence rates relate to the elevation of the study area. This analysis shows no correlation between subsidence rate and local elevation.