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• W2001171433 abstract "Traditional approaches of image classification, such as maximum likelihood and the band thresholding method, involve the per-pixel approach to delineate the water spread area of a reservoir. One of the limitations of these approaches is that the pixels representing the reservoir border, containing a mixture of water, soil and vegetation, are classified entirely as water, thereby resulting in inaccurate estimates of the water spread area. To compute the water spread area accurately, the sub-pixel approach has been used in this study. The water spread areas extracted using per-pixel and sub-pixel approaches from IRS-1D and P6 satellite image data were in turn used to quantify the capacity of the Singoor reservoir, Andhra Pradesh, India. The estimated capacity of the reservoir using the per-pixel and sub-pixel approaches was 727.75 Mm3 and 716.11 Mm3, respectively. The validation shows that the sub-pixel approach produced much less error (1.08%) than the per-pixel based approach (3.14%)." @default.
• W2001171433 created "2016-06-24" @default.
• W2001171433 creator A5038797477 @default.
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• W2001171433 date "2011-07-01" @default.
• W2001171433 modified "2023-09-29" @default.
• W2001171433 title "Reservoir capacity estimation of Singoor reservoir, India, by per-pixel and sub-pixel processing of multi-date satellite images" @default.
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• W2001171433 doi "https://doi.org/10.1080/10106049.2011.556755" @default.
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