Use of IKONOS and Landsat for malaria control in the Republic of Korea

Abstract

Malaria reemerged in the Republic of Korea (ROK) in 1993. While limited numbers of U.S. soldiers in high-risk areas use chloroquine/ primaquine chemoprophylaxis to prevent malaria, control of mosquito larvae through larviciding also can be used to reduce the risk of malaria transmission. In order to estimate the cost of larviciding, accurate estimates of the spatial extent of mosquito larval habitats are necessary. The purpose of this study was to determine whether an accurate estimate of the area covered by mosquito larval habitats can be obtained using Landsat 7 Enhanced Thematic Mapper+ (ETM+) and/or IKONOS data for the Korean test site.To estimate the area covered by larval habitats near Camp Greaves [Paekyeon-Ri, near Tongil-Chon (village)] in the ROK, an IKONOS and a Landsat 7 ETM+ image were classified using a parallelepiped classification. In a comparison with rice paddy field sites, 24 (92%) of the sites were classified correctly on the IKONOS image and 17 (65%) were classified correctly on the Landsat image. Comparing the classifications on a pixel-by-pixel basis, the agreement between the two classifications was 79%. Part of the disagreement was due to the difference in resolution of the two images. In spite of local differences, the two classifications produced similar area estimates.Although either Landsat or IKONOS could be used in Korea for a reasonable estimate of habitat area, only IKONOS can resolve small irrigation ponds. While ponds represent a small portion of the total larval habitat, they are an important source for mosquito breeding during the late rice-growing season in the ROK since they contain higher larval densities. High-resolution imagery, such as IKONOS, would be necessary for planning and implementing treatment of these smaller habitats. D

Hydrological and geomorphological controls of malaria transmission

“…Remote sensing data are often employed to develop statistical land-cover associations and create maps of malaria hazard; Machault et al (2011) provide a recent review. Land-cover classifications have been related to vector abundance using a range of data sources including LANDSAT TM (DiukWasser et al, 2004;Bøgh et al, 2007;Charoenpanyanet and Chen, 2008), SPOT (Thomas and Lindsay, 2000;Dambach et al, 2009), ASTER, Quickbird (Stoops et al, 2008), RADARSAT (Kaya et al, 2004) and IKONOS (Masuoka et al, 2003;Minakawa et al, 2005b;Mutuku et al, 2009).…”

Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach

“…In 2003, Masuoka et al compared the Landsat 7 Enhanced Thematic Mapper (ETM)+, with a spatial resolution of 30 m, to IKONOS imagery, which has a spatial resolution of 4 m, to determine their respective effectiveness in malaria control [10]. They found that both the Landsat 7 ETM+ and IKONOS imagery could be used to reasonably estimate habitat area, but only the IKONOS imagery could detect the presence of smaller ponds, which could be a significant source of water in which mosquitoes could breed.…”

The use of remotely sensed environmental data in the study of malaria

“…sinseni around two military camps. In this case, some pools were better detected with high-resolution Ikonos images (1 m resolution), even if no SWIR band was available (Masuoka et al, 2003). An example from the Kenyan highlands, which represents a very heterogenic ecosystem, is of interest in this connection, since the photo-interpretation of Ikonos images allowed the detection of 41% of the water collections, whereas the Landsat images (30 m resolution) did not provide any useful information (Mushinzimana et al, 2006).…”