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SCIENCE

Sinkhole susceptibility, Lazio Region, central Italy

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Pages 287-294 | Received 28 Jul 2014, Accepted 30 Jan 2015, Published online: 19 Feb 2015

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Silvia Bianchini, Pierluigi Confuorto, Emanuele Intrieri, Paolo Sbarra, Diego Di Martire, Domenico Calcaterra & Riccardo Fanti. (2022) Machine learning for sinkhole risk mapping in Guidonia-Bagni di Tivoli plain (Rome), Italy. Geocarto International 37:27, pages 16687-16715.
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Chiara Calligaris, Stefano Devoto & Luca Zini. (2017) Evaporite sinkholes of the Friuli Venezia Giulia region (NE Italy). Journal of Maps 13:2, pages 406-414.
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Chiara Calligaris, Emanuele Forte, Alice Busetti & Luca Zini. (2023) A joint geophysical approach to tune an integrated sinkhole monitoring method in evaporitic environments. Near Surface Geophysics.
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Jun Hwan Park, Junggoo Kang, Jaemo Kang & Duhwan Mun. (2022) Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area. Scientific Reports 12:1.
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Yong Je Kim, Boo Hyun Nam, Young-Hoon Jung, Xin Liu, Shinwoo Choi, Donghwi Kim & Seongmin Kim. (2022) Probabilistic spatial susceptibility modeling of carbonate karst sinkhole. Engineering Geology 306, pages 106728.
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Vahdettin Demir. (2022) Trend analysis of lakes and sinkholes in the Konya Closed Basin, in Turkey. Natural Hazards 112:3, pages 2873-2912.
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Osman Orhan, Murat Yakar & Semih Ekercin. (2020) An application on sinkhole susceptibility mapping by integrating remote sensing and geographic information systems. Arabian Journal of Geosciences 13:17.
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Boo Hyun Nam, Yong Je Kim & Heejung Youn. (2020) Identification and quantitative analysis of sinkhole contributing factors in Florida's Karst. Engineering Geology 271, pages 105610.
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Praveen Subedi, Kabiraj Subedi, Bina Thapa & Pradeep Subedi. (2019) Sinkhole susceptibility mapping in Marion County, Florida: Evaluation and comparison between analytical hierarchy process and logistic regression based approaches. Scientific Reports 9:1.
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V. Zumpano, L. Pisano & M. Parise. (2019) An integrated framework to identify and analyze karst sinkholes. Geomorphology 332, pages 213-225.
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Kamal Taheri, Himan Shahabi, Kamran Chapi, Ataollah Shirzadi, Francisco Gutiérrez & Khabat Khosravi. (2019) Sinkhole susceptibility mapping: A comparison between Bayes‐based machine learning algorithms. Land Degradation & Development 30:7, pages 730-745.
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Kiyeon Kim, Joonyoung Kim, Tae-Young Kwak & Choong-Ki Chung. (2018) Logistic regression model for sinkhole susceptibility due to damaged sewer pipes. Natural Hazards 93:2, pages 765-785.
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V. Baiocchi, G. Caramanna, D. Costantino, P. J. V. D’Aranno, F. Giannone, L. Liso, C. Piccaro, A. Sonnessa & M. Vecchio. (2018) First geomatic restitution of the sinkhole known as ‘Pozzo del Merro’ (Italy), with the integration and comparison of ‘classic’ and innovative geomatic techniques. Environmental Earth Sciences 77:3.
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