InSAR Detection of Localized Subsidence Induced by Sinkhole Activity in Suburban West-Central Florida

Oliver-Cabrera, T.; Wdowinski, S.; Kruse, Sarah; Robinson, Tonian

doi:10.5194/piahs-382-155-2020

Cited by 9 publications

(3 citation statements)

References 18 publications

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“…(b) The low spatial resolution of the SAR models that precludes the detection of the small sinkholes. A 20 m spatial resolution SAR image is unlikely to confidently detect sinkholes less than 100 m in diameter [85,86], and recent studies demonstrate that only SAR images with a very high resolution (pixel resolution ranging between 25 cm and 3 m of TerraSAR-X and COSMO-SkyMed satellite images) are able to identify sinkholes several meters across [25,87,88]. Unfortunately, the 40 m pixel resolution velocity maps of the FASTVEL approach that shows the better performance were useful only for the detection of unstable surface areas over 2300 m 2 .…”

Section: Advantages and Limitations Of Airborne Lidar And Web-based Insar Processing Toolsmentioning

confidence: 99%

The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools

et al. 2021

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InSAR (Interferometric Synthetic Aperture Radar) cloud computing and the subtraction of LiDAR (Light Detection and Ranging) DEMs (Digital Elevation Models) are innovative approaches to detect subsidence in karst areas. InSAR cloud computing allows for analyzing C-band Envisat and Sentinel S1 SAR images through web platforms to produce displacement maps of the Earth’s surface in an easy manner. The subtraction of serial LiDAR DEMs results in the same product but with a different level of accuracy and precision than InSAR maps. Here, we analyze the capability of these products to detect active sinkholes in the mantled evaporite karst of the Ebro Valley (NE Spain). We found that the capability of the displacement maps produced with open access, high-resolution airborne LiDAR DEMs was up to four times higher than InSAR displacement maps generated by the Geohazard Exploitation Platform (GEP). Differential LiDAR maps provide accurate information about the location, active sectors, maximum subsidence rate and growing trend of the most rapid and damaging sinkholes. Unfortunately, artifacts and the subsidence detection limit established at −4 cm/yr entailed important limitations in the precise mapping of the sinkhole edges and the detection of slow-moving sinkholes and small collapses. Although InSAR maps provided by GEP show a worse performance when identifying active sinkholes, in some cases they can serve as a complementary technique to overcome LiDAR limitations in urban areas.

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Section: Advantages and Limitations Of Airborne Lidar And Web-based Insar Processing Toolsmentioning

confidence: 99%

The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools

et al. 2021

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“…Different surface and subsurface investigation methods to identify and characterize sinkholes have been applied throughout the world. Among the others, we can report aerial and satellite image analysis (Dou et al., 2015; Festa et al., 2012; Gutiérrez et al., 2011; Panno & Luman, 2013), topographic map analysis (Basso et al., 2013; Brinkmann et al., 2008; Gutiérrez et al., 2011), field surveys (Bruno et al., 2008; Gutiérrez et al., 2007), LiDAR (Kim et al., 2019; Zhu et al., 2014, 2020), InSAR (Baer et al., 2018; Busetti et al., 2020; Galve et al., 2015; Guerrero et al., 2021; Intrieri et al., 2015; Jones & Blom, 2014; Malinowska et al., 2019; Oliver‐Cabrera et al., 2020; Orhan et al., 2021; Shi et al., 2019; Solari et al., 2020; Theron et al., 2017), ground‐based monitoring (Desir et al., 2018; Kersten et al., 2017; Kobe et al., 2019; Sevil et al., 2017; Zhende et al., 2013), geophysical surveys (De Ritis et al., 2020; García‐Moreno & Mateos, 2011; Krawczyk et al., 2012; Kühn et al., 2011; Margiotta et al., 2012; Malehmir et al., 2016; Pazzi et al., 2018; Ronen et al., 2019; Samyn et al., 2014; Stierman, 2004; Waltham et al., 2005; Wust‐Bloch & Joswig, 2006), hydrogeochemical studies (Delkhahi et al., 2020; Taheri et al., 2021) and trenching (Carbonel et al., 2015; Gutiérrez et al., 2018; Sevil et al., 2017) have been used in a series of multidisciplinary and multi‐technique investigations.…”

Section: Introductionmentioning

confidence: 99%

A joint geophysical approach to tune an integrated sinkhole monitoring method in evaporitic environments

Calligaris

Forte

Busetti

et al. 2023

Near Surface Geophysics

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Several methodologies allow for the detection and mapping of existing sinkholes in order to asses and manage the associated hazards and risks. These phenomena, linked to the presence of soluble rocks, are well known globally as they can cause severe damage to man‐made structures. In this paper, we propose an integrated method applied to a test‐site area in NE Italy where, on May 11 2017, a failure shaped like a sinkhole, suddenly occurred along a main regional road, which then had to be closed to traffic in part as a result of a landslide developing on the slope just upstream from the surface depression which had already formed. The slope was reprofiled, a paved barrier was placed at the toe of the slope, and the road itself was finally repaired and restored. In the test site, a detailed morphological and geological survey was performed, as well as several integrated multi‐scale geophysical investigations, both in correspondence to the sinkhole location and in surrounding areas where other depressions were found. Results confirm the absence of large cavities down to the maximum investigated depth and highlighted a complex geological situation with abrupt lateral variations, a straight correlation between different geomorphological and geological elements, and the role of water paths. Geophysical investigations were found to be a useful tool to monitor the future evolution of the identified phenomena and to prevent further collapses and disasters along roads.

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“…Sentinel-1 data has been widely used for monitoring land subsidence in areas prone to sinkhole formation worldwide, including Texas [ 25 ], Iran [ 26 ], and Western Central Florida [ 27 ]. Sinkhole-induced deformation was also detected by X-band (3.1 cm wavelength) COnstellation of small Satellites for the Mediterranean basin Observation (COSMO SkyMed) satellite constellation and the TerraSAR-X satellite [ 28 , 29 , 30 ]. The precursory deformation, which are harbingers of sinkhole formations, were detected along the Dead Sea (DS) shorelines in Israel using InSAR measurements by using COSMO-SkyMed satellites, by [ 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Land Subsidence and Its Relations with Sinkhole Activity in Karapınar Region, Turkey: A Multi-Sensor InSAR Time Series Study

Orhan

Oliver-Cabrera

Wdowinski

et al. 2021

Sensors

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The Karapinar basin, located in the Central Anatolian part of Turkey, is subjected to land subsidence and sinkhole activity due to extensive groundwater withdrawal that began in the early 2000s. In this study, we use Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), and groundwater level data to monitor and better understand the relations between groundwater extraction, land subsidence, and sinkhole formation in the Karapinar basin. The main observations used in the study are InSAR-derived subsidence velocity maps calculated from both Sentinel-1 (2014–2018) and COSMO-SkyMed (2016–2017) SAR data. Our analysis reveals broad areas of subsidence with rates exceeding 70 mm/yr. The InSAR-derived subsidence was compared with GNSS data acquired by a continuously operating GNSS station located in the study area, which show a similar rate of subsidence. The temporal characteristic of both InSAR and GNSS time series indicate a long-term subsidence signal superimposed by seasonal variability, which follows the overall groundwater level changes, with over 80% cross-correlation consistency. Our results also indicate that sinkhole activity is limited to slow subsidence areas, reflecting strong cohesion of near-surface rock layers that resist subsidence but yield to collapse in response to aquifer system deformation induced by groundwater extraction.

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InSAR Detection of Localized Subsidence Induced by Sinkhole Activity in Suburban West-Central Florida

Cited by 9 publications

References 18 publications

The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools

The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools

A joint geophysical approach to tune an integrated sinkhole monitoring method in evaporitic environments

Land Subsidence and Its Relations with Sinkhole Activity in Karapınar Region, Turkey: A Multi-Sensor InSAR Time Series Study

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