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%).
