The week's pick
Random Articles
Reseach Article
Object-Oriented Approach of Landsat Imagery for Flood Mapping
| 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 |
10.5120/21782-5059
|
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
Abstract
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.
References
- Iglseder, H. , Arensfischer, W. , Wolfensberger, W. 1995, "Small Satellite Constellations for Disaster Detection and Monitoring," Natural Hazards,volume 15, issue 11, pp. 79-85,
- Sanyal, J. ; Lu, X. 2004, "Application of remote sensing in flood management with special reference to Monsoon Asia: A review," Nat. Hazards, 33, 283–301
- Allenbach, B. et al. 2005, "Rapid EO Disaste Mapping Service: Added value,feedback and perspectives after 4 years of Charter actions, SERTIT,
- Kundzewicz, Z. W. and Schellnhuber, H. J. 2004, "Floods in the IPCC TAR perspective. Natural Hazards", 31:111-128,.
- Uddin, K. ; Gurung, D. R. ; Giriraj, A. ; Shrestha, B. 2013, "Application of remote sensing and gis for flood hazard management: A case study from Sindh Province, Pakistan," Am. J. Geogr. Inf. Syst. , 2, 1–5.
- Dronova, I. ; Gong, P. ; Wang, L. 2011, Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake,China. Remote Sens. Environ. , 115, 3220–3236.
- Anil. N. C and Jaishankar. G 2011, "Studies on Land Use/Land Cover and change detection from parts of South West Godavari District, A. PUsing Remote Sensing and GIS Techniques," J. Ind. Geophys. Union, Vol. 15, No. 4, pp. 187-194.
- Kuldeep and Kamalesh 2011, "Land Use / Land cover change detection in Doon valley (Dehradun Tehsil), Uttarakhand: using GIS& Remote Sensing Technique," International Journal of Geomatics & Geosciences, Vol. 2 Issue 1, pp. 34-41.
- Symeonakis. E and Koukoulas. S 2009, "A Land use Change and Land Degradation Study in Spain and Greece Using Remote Sensing and GIS," J. Ind. Geophysics. Union, Vol. 14, No. 4, pp. 180-190.
- Pacifici, F. , Chini, M. , Emery, W. J. , "A neural network approach using multi-scale textural metrics from very high-resolution panchromatic imagery for urban land-use classification", Remote Sensing. Environment,.
- eCognition User Guider 4, Defines Imaging, 2003
- Kiema, J. B. K. 2002, "Texture analysis and data fusion in the extraction of topographic objects from satellite imagery", International Journal of Remote Sensing,
- Xie 2005, "Object Oriented Classification, Remote Sensing Image Process and Analysis,".
Index Terms
Keywords