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Reseach Article

Object-Oriented Approach of Landsat Imagery for Flood Mapping

by Kanta Tamta, H.s.bhadauria
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 16
Year of Publication: 2015
Authors: Kanta Tamta, H.s.bhadauria

Kanta Tamta, H.s.bhadauria . Object-Oriented Approach of Landsat Imagery for Flood Mapping. International Journal of Computer Applications. 122, 16 ( July 2015), 6-9. DOI=10.5120/21782-5059

@article{ 10.5120/21782-5059,
author = { Kanta Tamta, H.s.bhadauria },
title = { Object-Oriented Approach of Landsat Imagery for Flood Mapping },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 16 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { },
doi = { 10.5120/21782-5059 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:10:41.896327+05:30
%A Kanta Tamta
%A H.s.bhadauria
%T Object-Oriented Approach of Landsat Imagery for Flood Mapping
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 16
%P 6-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

This study introduced an object-oriented approach to flood mapping and affected field estimation in central Cambodia. Traditional pixel-based image algorithms for flood mapping and land use and land cover classification endure from low accuracy, sub-pixel problems, and the cover noise effect in the resulting images On the other hand, the object-based image analysis (OBIA) approach has been thoroughly developed in the last two decades to overcome the limitations and disadvantages of the traditional pixel-based approaches by generating and analyzing meaningful image objects instead of individual pixels and reducing the speckle noise effect. The OBIA approach was applied for the image classification with a new improved estimation algorithm with multi scale parameter in the segmentation process to obtain more accurate results in the flood mapping. Flooding can be recognized using a variety of approaches such as statistics, ground-based measuring, prediction model, remote sensing techniques.

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Index Terms

Computer Science
Information Sciences


Change Detection Classification Flood Mapping Object-Based Approach Segmentation