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Article

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

1
Departamento de Ciencias de la Tierra, Universidad de Zaragoza, C/Pedro Cerbuna 12, 50009 Zaragoza, Spain
2
Departamento de Geodinámica, Universidad de Granada, Avda. del Hospicio, s/n, 18010 Granada, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Zhong Lu, Konstantinos G. Nikolakopoulos, Mario Parise, Mario Floris and Giulia Tessari
Remote Sens. 2021, 13(16), 3261; https://doi.org/10.3390/rs13163261
Received: 30 June 2021 / Revised: 6 August 2021 / Accepted: 16 August 2021 / Published: 18 August 2021
(This article belongs to the Special Issue Remote Sensing of Engineering Problems in Karst)
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. View Full-Text
Keywords: differential LiDAR; DoD; GEP; SBAS; FASTVEL; salt; karst; subsidence rate; remote sensing; Ebro differential LiDAR; DoD; GEP; SBAS; FASTVEL; salt; karst; subsidence rate; remote sensing; Ebro
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MDPI and ACS Style

Guerrero, J.; Sevil, J.; Desir, G.; Gutiérrez, F.; Arnay, Á.G.; Galve, J.P.; Reyes-Carmona, C. The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools. Remote Sens. 2021, 13, 3261. https://doi.org/10.3390/rs13163261

AMA Style

Guerrero J, Sevil J, Desir G, Gutiérrez F, Arnay ÁG, Galve JP, Reyes-Carmona C. The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools. Remote Sensing. 2021; 13(16):3261. https://doi.org/10.3390/rs13163261

Chicago/Turabian Style

Guerrero, Jesús, Jorge Sevil, Gloria Desir, Francisco Gutiérrez, Ángel G. Arnay, Jorge P. Galve, and Cristina Reyes-Carmona. 2021. "The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools" Remote Sensing 13, no. 16: 3261. https://doi.org/10.3390/rs13163261

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