@article{d4cebeae202a401d8b4ce80e0d9602b3,
title = "Predicting sinkhole susceptibility in Frederick Valley, Maryland, using geographically weighted regression",
author = "Doctor, {Katarina Z.} and Doctor, {Daniel H.} and Barry Kronenfeld and Wong, {David W. S.} and Brezinski, {David K.}",
note = "A dataset of 556 collapsed sinkholes covering six 1:24,000 scale geologic quadrangles was analyzed in order to map the relative likelihood of sinkhole formation in Frederick Valley, Maryland, USA. Factors that help predict the density of sinkholes included clustering of sinkholes, geologic structure, rock type, and proximity to: quarries, water bodies, streams, roads, faults, axes of synclines or anticlines, and depth to groundwater.",
year = "2008",
month = sep,
day = "18",
doi = "10.1061/41003(327)24",
language = "American English",
journal = "11th Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst",
}