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Proceedings Paper

Identification of mosquito larval habitats in high resolution satellite data
Author(s): Richard K. Kiang; Stephanie M. Hulina; Penny M. Masuoka; David M. Claborn
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Paper Abstract

Mosquito-born infectious diseases are a serious public health concern, not only for the less developed countries, but also for developed countries like the U.S. Larviciding is an effective method for vector control and adverse effects to non-target species are minimized when mosquito larval habitats are properly surveyed and treated. Remote sensing has proven to be a useful technique for large-area ground cover mapping, and hence, is an ideal tool for identifying potential larval habitats. Locating small larval habitats, however, requires data with very high spatial resolution. Textural and contextual characteristics become increasingly evident at higher spatial resolution. Per-pixel classification often leads to suboptimal results. In this study, we use pan-sharpened Ikonos data, with a spatial resolution approaching 1 meter, to classify potential mosquito larval habitats for a test site in South Korea. The test site is in a predominantly agricultural region. When spatial characteristics were used in conjunction with spectral data, reasonably good classification accuracy was obtained for the test site. In particular, irrigation and drainage ditches are important larval habitats but their footprints are too small to be detected with the original spectral data at 4-meter resolution. We show that the ditches are detectable using automated classification on pan-sharpened data.

Paper Details

Date Published: 23 September 2003
PDF: 9 pages
Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); doi: 10.1117/12.487016
Show Author Affiliations
Richard K. Kiang, NASA Goddard Space Flight Ctr. (United States)
Stephanie M. Hulina, NASA Goddard Space Flight Ctr. (United States)
Science Systems and Applications, Inc. (United States)
Penny M. Masuoka, NASA Goddard Space Flight Ctr. (United States)
Uniformed Services Univ. of the Health Sciences (United States)
David M. Claborn, Navy Disease Vector Ecology and Control Ctr. (United States)


Published in SPIE Proceedings Vol. 5093:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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