Modeling Occurrence of Urban Mosquitos Based on Land Use Types and Meteorological Factors in Korea

Yong-Su Kwon, Mi-Jung Bae, Namil Chung, Yeo-Rang Lee, Suntae Hwang, Sang-Ae Kim, Young Jean Choi and Young-Seuk Park
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Yong-Su Kwon: Department of Life and Nanopharmaceutical Sciences, Kyung Hee University, Seoul 02447, Korea
Mi-Jung Bae: Department of Life and Nanopharmaceutical Sciences, Kyung Hee University, Seoul 02447, Korea
Namil Chung: Department of Biology, Kyung Hee University, Seoul 02447, Korea
Yeo-Rang Lee: Department of Biology, Kyung Hee University, Seoul 02447, Korea
Suntae Hwang: College of Electrical Engineering & Computer Science, Kookmin University, Seoul 02707, Korea
Sang-Ae Kim: Yeongdeungpo-gu Health Center, Yeongdeungpo-gu, Seoul 07260, Korea
Young Jean Choi: WISE Institute, Hankuk University of Foreign Studies, Seoul 02450, Korea
Young-Seuk Park: Department of Life and Nanopharmaceutical Sciences, Kyung Hee University, Seoul 02447, Korea

IJERPH, 2015, vol. 12, issue 10, 1-17

Abstract: Mosquitoes are a public health concern because they are vectors of pathogen, which cause human-related diseases. It is well known that the occurrence of mosquitoes is highly influenced by meteorological conditions (e.g., temperature and precipitation) and land use, but there are insufficient studies quantifying their impacts. Therefore, three analytical methods were applied to determine the relationships between urban mosquito occurrence, land use type, and meteorological factors: cluster analysis based on land use types; principal component analysis (PCA) based on mosquito occurrence; and three prediction models, support vector machine (SVM), classification and regression tree (CART), and random forest (RF). We used mosquito data collected at 12 sites from 2011 to 2012. Mosquito abundance was highest from August to September in both years. The monitoring sites were differentiated into three clusters based on differences in land use type such as culture and sport areas, inland water, artificial grasslands, and traffic areas. These clusters were well reflected in PCA ordinations, indicating that mosquito occurrence was highly influenced by land use types. Lastly, the RF represented the highest predictive power for mosquito occurrence and temperature-related factors were the most influential. Our study will contribute to effective control and management of mosquito occurrences.

Keywords: urban mosquito; land use type; meteorological factor; random forest (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2015
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