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United States Department of Agriculture

Agricultural Research Service

Title: Identification of Larval Anopheline Habitats in the Republic of Korea Using Remote Sensing

Authors
item Sithiprasasna, Ratana - USAMC-AFRIMS, THAILAND
item Linthicum, Kenneth
item Lee, Won - SEOUL, KOREA
item Klein, Terry - U.S. ARMY, KOREA
item Ugsang, Donald - THAILAND
item Jones, James - USAMC-AFRIMS, THAILAND

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: March 3, 2005
Publication Date: April 7, 2005
Citation: Sithiprasasna, R., Linthicum, K., Lee, W.J., Klein, T.A., Ugsang, D.M., Jones, J.W. Identification of larval anopheline habitats in the republic of korea using remote sensing. 71st Annual Meeting of the American Mosquito Control Association, Vancouver, British Columbia, Canada, pg. 28.

Technical Abstract: Plasmodium vivax malaria reemerged in the Republic of Korea in 1993, with more than 2000 cases reported in the northwestern part of the country over the last 10 years. To better assess the risk of malaria transmission we conducted a surveillance study to identify and characterize the habitats that produce potential Anopheles vector mosquitoes. Immature and adult mosquito collection data were incorporated into a Geographic Information System along with remotely sensed satellite imagery, and imagery classified to land use. More than 2,000 anopheline larvae were collected and mapped from 186 breeding habitats, which were categorized into 9 types. Anopheles sinensis was the most commonly collected species, representing more than 97% of the specimens, followed by An. pullus 1.0%, An. sineroides 0.8%, and An. lesteri s.l 1.0%. An. sinensis , pullus , and lesteri were found most frequently in rice paddies followed by: ditches, flooded areas, ground pools, wheel tracks, swamps, irrigation canals, and stream margins. Satellite data were used to display spatial data in the form of geographic coverage and descriptive information in the form of relational databases associated with the mapped features. Supervised classification of imagery permitted good separation between paddy, forest, and water breeding site classes.

Last Modified: 12/17/2014