Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/3993
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dc.contributor.authorJeyakanthan, V. S.-
dc.contributor.authorSanjeevi, Shanmugam-
dc.date.accessioned2019-12-06T05:13:10Z-
dc.date.available2019-12-06T05:13:10Z-
dc.date.issued2011-
dc.identifier.citationGeocarto International Vol. 26, No. 4, July 2011, 305–320en_US
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/3993-
dc.description.abstractTraditional 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%).en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectReservoiren_US
dc.subjectWater spread areaen_US
dc.subjectCapacity estimationen_US
dc.subjectSub pixel approachen_US
dc.titleReservoir capacity estimation of Singoor reservoir, India, by per-pixel and sub-pixel processing of multi-date satellite images Veeraraghu S.en_US
dc.typeArticleen_US
Appears in Collections:Research papers in International Journals

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