County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors-Reference-Cited by-同舟云学术

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County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors

Published:2019-11 Issue: Volume:208-209 Page:106044
ISSN:0265-931X
Container-title:Journal of Environmental Radioactivity
language:en
Short-container-title:Journal of Environmental Radioactivity

Author:

Park No-Wook,Kim Yongjae,Chang Byung-Uck,Kwak Geun-Ho

Funder

Nuclear Safety Research Program

Korea Foundation

Nuclear Safety and Security Commission (NSSC), Republic of Korea

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,General Medicine,Environmental Chemistry

Reference57 articles.

1. Local indicators of spatial association—LISA;Anselin;Geogr. Anal.,1995

2. Geological controls on radon potential in Northern Ireland;Appleton;Proc. Geologists' Assoc.,2015

3. A geostatistical approach to define guidelines for radon prone area identification;Borgoni;Stat. Methods Appl.,2010

4. A geostatistical approach to assess the spatial association between indoor radon concentration, geological features and building characteristics: the case of Lombardy, Northern Italy;Borgoni;Int. J. Environ. Res. Public Health,2011

5. Investigations on indoor radon in Austria, part 2: geological classes as categorical external drift for spatial modelling of the radon potential;Bossew;J. Environ. Radioact.,2008

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1. Radon and lung cancer: Current status and future prospects;Critical Reviews in Oncology/Hematology;2024-06

2. Mapping Indoor Radon Concentrations in Chungcheongbuk-do, South Korea: A Geospatial Analysis using Machine Learning Models;2024-05-02

3. Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms;Environment International;2023-01

4. Application of Machine Learning Algorithms for Geogenic Radon Potential Mapping in Danyang-Gun, South Korea;Frontiers in Environmental Science;2021-09-22

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