Abstract:
Estimation of reservoir water-spread area is
often carried out by field surveys which are cumbersome,
time consuming, expensive and involves more man power.
Hence, such surveys cannot be carried out periodically. To
overcome this issue, satellite images are used, wherein the
reservoir water-spread is estimated by conventional perpixel
classification such as the maximum likelihood and
minimum distance to mean approaches that often results in
inaccurate estimate of water-spread area due to the presence
of mixed pixels. High cost and non-availability of
high resolution images demands the use of an alternative
approach that can give accurate information about the
reservoir water-spread area. In this work, IRS, LISS III
images of moderate (24 m) resolution were used for
accurate estimation of the water-spread area of Singoor
reservoir, southern India. The reservoir water-spread areas
were extracted using per-pixel classification, sub-pixel
classification and super resolution mapping approaches.
These results were validated with the water-spread areas
obtained from field data of the same dates. The error produced
by the per-pixel approach was 6.66%, while it was
4.37% for the sub-pixel approach and a meagre 1.71% for
the super-resolution approach. Fairly less error produced
by the super resolution mapping technique implies that it is
an efficient approach for accurate quantification of reservoir
water-spread area. The estimated water-spread can be
used in a simple volume estimation formula to estimate the
capacity of the reservoir.
