@inproceedings{fd2ca347f3344268bb60346b88a37666,
title = "A Preliminary Study on Use of LiDAR Data to Characterize Sinkholes in Central Florida",
abstract = "The state of Florida is highly prone to sinkhole incident and formation, mainly because of the soluble carbonate bedrock and its susceptibility to dissolution. Numerous sinkholes, particularly Central Florida, have occurred. Florida subsidence incident reports (FSIR) contain verified sinkholes with global positioning system (GPS) information. In addition to existing detection methods such as subsurface exploration and geophysical methods, a remote sensing method can be a precise and efficient tool to detect and characterize sinkholes. By using light detection and ranging (LiDAR) data, the authors produce a GIS-based data layer of a selected area in Central Florida to identify probable sinkholes. A semi-automated model in ArcMap was then developed to detect sinkholes and also to determine geometric characteristics (e.g., depth, length, circularity, area, and volume). This remote sensing technique has a potential to detect unreported sinkholes in rural and/or inaccessible areas.",
author = "Amirarsalan Rajabi and Kim, \{Yong Je\} and Kim, \{Sung Hee\} and Kim, \{Yong Seong\} and Kim, \{Bum Joo\} and Nam, \{Boo Hyun\}",
note = "Publisher Copyright: {\textcopyright} ASCE.; 3rd International Foundation Congress and Equipment Expo 2018: Advances in Geomaterial Modeling and Site Characterization, IFCEE 2018 ; Conference date: 05-03-2018 Through 10-03-2018",
year = "2018",
doi = "10.1061/9780784481585.003",
language = "English",
series = "Geotechnical Special Publication",
publisher = "American Society of Civil Engineers (ASCE)",
number = "GSP 295",
pages = "23--31",
editor = "Stuedlein, \{Armin W.\} and Suleiman, \{Muhannad T.\} and Anne Lemnitzer",
booktitle = "Geotechnical Special Publication",
address = "United States",
edition = "GSP 295",
}