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Revealing the untold stories of sinkhole land subsidence over the remains of an underground river in tuff soil by Ground Penetrating Radar

2025· article· en· 1 citations· W4415099718 sur OpenAlex· 10.1016/j.geomat.2025.100078

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Revue canadienneIl a paru dans une revue canadienne.

Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Le tri à trois modèles

les 1 000 travaux triés →

Les trois modèles l'ont jugé hors champ.

strate : venue_new · poids de sondage : 2684.25 (l'échantillon est stratifié ; tout taux calculé sans le poids est faux)
Claude Opus 4.8OUT
genre : empirical
porte sur le Canada: non
confiance: high

Geophysical survey using ground penetrating radar to detect sinkhole subsidence.

GPT-5.6 (high)OUT
genre : empirical
porte sur le Canada: non
confiance: high

This applies ground-penetrating radar to sinkhole detection, not research practice.

Grok 4.5OUT
genre : empirical
porte sur le Canada: non
confiance: high

Geotechnical GPR study of sinkhole land subsidence; domain engineering.

Résumé

Sinkhole-induced land subsidence poses a critical hazard in urban areas underlain by pyroclastic tuff formations. This study applies a calibrated Ground Penetrating Radar (GPR) method to detect subsurface anomalies in Malang city, Indonesia, where residual underground river flow contributes to stratigraphic instability. Using a 90 MHz GPR OKO AB-90 system, calibrated with a portable Vector Network Analyzer (VNA), dielectric values ranging from 4.3 to 13.6 were obtained across dry tuff, saturated clay, and concrete layers. These values yielded reflection coefficients (R) between −0.023 and 0.035, indicating clear contrasts between restored culverts, suspected new sinkholes, and groundwater zones. GPR imaging revealed subsidence features at depths of 4 – 7 m , with high-density signal zones exceeding 0.85 normalized amplitude units. The signal accuracy was validated via Signal-to-Noise Ratio (SNR) and Normalized Root Mean Square Error (NRMSE), with SNR values above 22 dB and NRMSE values below 0.07, confirming reliable anomaly detection. A regression analysis ( R 2 = 0.64 , p < 0.0001 ) between flood severity and subsidence events further supported the hydrogeological linkage and erosion-driven subsurface instability in pyroclastic terrains. These findings demonstrate that calibrated GPR effectively distinguishes subsurface anomalies in moisture-variable tuff environments. This approach enhances early detection of sinkhole-prone zones and supports urban geohazard mitigation strategies. • GPR delineates subsurface anomalies in sinkhole-prone urban volcanic tuff zones. • VNA calibration improves permittivity accuracy and signal reliability for GPR scans. • SNR > 22 dB and NRMSE < 0.07 confirm high-quality subsurface anomaly detection. • Rainfall and flood recurrence contextualize subsidence vulnerability in urban terrain. • Calibrated GPR offers a replicable method for urban geohazard mapping in tuff areas.

Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.

La notice

Revue
GEOMATICA
Thématique
Geophysical Methods and Applications
Domaine
Engineering
Établissements canadiens
Organismes subventionnaires
Universitas AirlanggaUniversiti Teknologi MARA
Mots-clés
Ground-penetrating radarSinkholeGeohazardSubsidenceHydrogeologyAquiferGroundwaterPiezometerRadar
Résumé présent dans OpenAlex
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