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Turbid water of agricultural reservoir and downstream is getting worse and worse because the soil flows out from current
residential land development and road construction. Sediment loads, which fill the water bodies (lakes, agricultural
reservoir, dams, and aquatic ecosystems) are one of the most important environmental problems throughout the world.
Water turbidity is a commonly used index of the factors that determine light penetration in the water column. Consistent
estimation of water turbidity is crucial to design environmental and restoration management plans, to predict fate of
possible pollutants, and to estimate sedimentary fluxes into the ocean. Traditional methods monitoring fixed
geographical locations at fixed intervals may not be representative of the mean water turbidity in estuaries between
intervals, and can be expensive and time consuming. Although remote sensing offers a good solution to this limitation, it
is still not widely used due in part to required complex processing of imagery. The aims of this study were two folds: to
map water turbidity and estimate water turbidity level based on Landsat imagery. Based on field measurements and
principal component analysis (PCA), was examined the spatial variability of water turbidity in Lake Paldang by using the
Landsat satellite imagery collected on 2001~2007. The result of this study is that when we carried out PCA using
Landsat imagery, water turbidity had contributed at PC 2 which was similar to the in-situ data. A correlation formula
(water turbidity = 0.3169 × PC2 – 21.477, R2 = 0.6319) between the in-situ data and PC2. And we can now use formula to map the water turbidity distribution from the synchronously acquired Landsat imagery, and continue the discussion on
the inverse water turbidity results of the Landsat imagery. Because results from this type of study vary with season and
time of day, it is necessary to monitor continuously in-situ data as well as radiance feature of reflectance in order to
determine accurately the environmental factors of water quality.
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