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Saemangeum, located on the southwest coast of the Korean peninsula, is a 40 100 ha ongoing "reclamation" project in
South Korea, concomitance damming the estuaries of the Mangyong and Dongjin rivers, replacing vast tidal land and
sea-shallows with land and a huge freshwater reservoir. In 1991, the South Korean government announced that a seawall
(dyke) would be constructed to link two headlands just south of the South Korean industrial port city of Gunsan and
Buan, 270 kilometers southwest of Seoul, to create 400 km2 of farmland and a freshwater reservoir. Started in 1991, the
33km long seawall was finally completed on April 2006. Chlorophyll-a concentration, Suspended solids (SS), Sea
surface temperature (SST), and turbidity are four important water quality variables, among other environmental factors
such as salinity and pH, for tidal land production in Saemangeum. Change detection of the SST and SS during
Saemangeum seawall construction was carried out by using LANDSAT TM and ETM imagery data. The spatial and
temporal distribution of SST and SS are estimated and mapped with various degrees of success in Saemangeum area.
Here we assessed the potential of these data to derive water quality parameters in a reclaimed estuary environment. We
found that the evolution of the estuary, coastline, delta, and change detection results derived from LANDSAT TM and
ETM images recorded in 1989, 2001 and 2008, respectively. Due to the limitations of image acquisition and noise, many
researchers have employed the image processing technique to improve satellite data in order to assess water quality. The
interpolation approach is a useful tool for the analyses and assessment on SST and SS on the basis of available satellite
imagery data. Ordinary kriging (OK) were used to improve the SST and SS images in the study area. Results indicate
that sedimentary transport, SS, and SST in Saemangeum has significantly changed during the past 20 years, with a
dramatic increase in the amount of sediment moved by the river, and deposited in the estuary and in river mouth. The
analysis of the spatial structure showed that SST and SS in the study area were spatially correlated and therefore spatial
interpolation was valid. Also, we recognized that LANDSAT TM and ETM data have sufficient sensitivity for estuary
environmental monitoring.
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