TY - JOUR
T1 - Spatial clustering based meteorological fields construction for regional vulnerability assessment
AU - Lee, Taemin
AU - Choi, Woosung
AU - Sohn, Jongryuel
AU - Moon, Kyongwhan
AU - Byeon, Sanghoon
AU - Lee, Wookyun
AU - Jung, Soonyoung
N1 - Funding Information:
This subject is supported by Korea Ministry of Environment(MOE) as "The Chemical Accident Prevention Technology Development Project." (Project No. 2015001950001)' provided by Korea Ministry of Environment.
PY - 2018
Y1 - 2018
N2 - Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.
AB - Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results.
KW - DBSCAN
KW - Meteorological field
KW - Spatial clustering
KW - Vulnerability assessment
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U2 - 10.18517/ijaseit.8.4-2.5759
DO - 10.18517/ijaseit.8.4-2.5759
M3 - Article
AN - SCOPUS:85055328325
VL - 8
SP - 1686
EP - 1691
JO - International Journal on Advanced Science, Engineering and Information Technology
JF - International Journal on Advanced Science, Engineering and Information Technology
SN - 2088-5334
IS - 4-2
ER -