Caves are one of the last frontiers of human exploration on Earth. They are very relevant scientific targets as they host significant biodiversity and unique geologic formations. The presence of underground passages accessible for human or robotic exploration are revealed by localized collapse of the near-surface ceiling of a cave system (skylight). Remote sensing systems are a valuable tool for skylights detection as these features are often located on very remote and often inaccessible regions of the Earth. However, with the available remote sensing techniques and data analysis methodologies, it is very difficult to determine whether a skylight is providing access to a cave continuation or it represents only a closed depression with no extensions. In this article we propose a methodology, based on very high-resolution (VHR) orbital synthetic aperture radar (SAR) imaging systems, to estimate both caves geometric characteristics and accessibility information in the proximity of a skylight. To test our methodology, we acquired radar data over different Earth’s location by exploiting the Capella Space X-band microsatellite radar constellation. The experimental results show that our methodology effectively determines the caves geometric characteristics and accessibility under a variety of surface conditions. We also detected several unknown and unexplored large cave systems located near Volcan Wolf and Ecuador, Isla Isabela, Galapagos. The presented work has relevant implications for the field of geological studies, ecology, and space exploration research since optical imaging shows the evidence of potential cave systems accessible from skylights on other planetary bodies such as Mars.

A Novel Method for Hidden Natural Caves Characterization and Accessibility Assessment from Spaceborne VHR SAR Images / Carrer, Leonardo; Castelletti, Davide; Pozzobon, Riccardo; Sauro, Francesco; Bruzzone, Lorenzo. - In: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. - ISSN 0196-2892. - 2023, 61:(2023), pp. 450011101-450011111. [10.1109/TGRS.2022.3222991]

A Novel Method for Hidden Natural Caves Characterization and Accessibility Assessment from Spaceborne VHR SAR Images

Carrer, Leonardo
;
Castelletti, Davide;Bruzzone, Lorenzo
2023-01-01

Abstract

Caves are one of the last frontiers of human exploration on Earth. They are very relevant scientific targets as they host significant biodiversity and unique geologic formations. The presence of underground passages accessible for human or robotic exploration are revealed by localized collapse of the near-surface ceiling of a cave system (skylight). Remote sensing systems are a valuable tool for skylights detection as these features are often located on very remote and often inaccessible regions of the Earth. However, with the available remote sensing techniques and data analysis methodologies, it is very difficult to determine whether a skylight is providing access to a cave continuation or it represents only a closed depression with no extensions. In this article we propose a methodology, based on very high-resolution (VHR) orbital synthetic aperture radar (SAR) imaging systems, to estimate both caves geometric characteristics and accessibility information in the proximity of a skylight. To test our methodology, we acquired radar data over different Earth’s location by exploiting the Capella Space X-band microsatellite radar constellation. The experimental results show that our methodology effectively determines the caves geometric characteristics and accessibility under a variety of surface conditions. We also detected several unknown and unexplored large cave systems located near Volcan Wolf and Ecuador, Isla Isabela, Galapagos. The presented work has relevant implications for the field of geological studies, ecology, and space exploration research since optical imaging shows the evidence of potential cave systems accessible from skylights on other planetary bodies such as Mars.
2023
Carrer, Leonardo; Castelletti, Davide; Pozzobon, Riccardo; Sauro, Francesco; Bruzzone, Lorenzo
A Novel Method for Hidden Natural Caves Characterization and Accessibility Assessment from Spaceborne VHR SAR Images / Carrer, Leonardo; Castelletti, Davide; Pozzobon, Riccardo; Sauro, Francesco; Bruzzone, Lorenzo. - In: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. - ISSN 0196-2892. - 2023, 61:(2023), pp. 450011101-450011111. [10.1109/TGRS.2022.3222991]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/362863
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