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River Water Level Prediction in Satellite Images using Support Vector Machine

by R.kalaivani, P.thangaraj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 23
Year of Publication: 2012
Authors: R.kalaivani, P.thangaraj
10.5120/6421-8929

R.kalaivani, P.thangaraj . River Water Level Prediction in Satellite Images using Support Vector Machine. International Journal of Computer Applications. 43, 23 ( April 2012), 27-33. DOI=10.5120/6421-8929

@article{ 10.5120/6421-8929,
author = { R.kalaivani, P.thangaraj },
title = { River Water Level Prediction in Satellite Images using Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 23 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 27-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number23/6421-8929/ },
doi = { 10.5120/6421-8929 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:07.046625+05:30
%A R.kalaivani
%A P.thangaraj
%T River Water Level Prediction in Satellite Images using Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 23
%P 27-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent days, the impact of satellite image processing in various researches is greater because of the wide variety of applications in astronomy, GIS, Agriculture monitoring and Disaster management. Besides other, the disaster management is important, since it is very useful in protecting the living beings. In this paper, river water level identification is done using support vector machines. In order to achieve this, the input satellite image is preprocessed and subsequently the segmentation is carried out with the aid of the anisotropic diffusion segmentation. Support Vector Machine (SVM) is utilized to identify the river spot in the input image in which contains land also and then the morphological operation is utilized to smooth the image. Consequently, in the testing phase, the image is tested with the SVM for water region identification and also another one SVM is utilized for the identification of the river stage.

References
  1. Laurence C. Smith, "Satellite Remote Sensing of River Inundation Area, Stage, And Discharge: A Review", Hydrological Processes, Vol. 11, pp. 1427-1439, 1997
  2. Frederic Frappart, Fabrice Papa, James S. Famiglietti, Catherine Prigent, William B. Rossow and Frederique Seyler, Interannual variations of river water storage from a multiple satellite approach: A case study for the Rio Negro River basin", Journal Of Geophysical Research, Vol. 113, 2008
  3. C. Tzimopoulos, P. Ginidi, "Optimized Aquifer Management, Using Linear Programming. AN Application To The Agia Varvara Aquifer, drama, Greece", Global NEST Journal, Vol 7, No 3, pp 395-404, 2005
  4. R. Chopra, V. K. Verma and P. K. Sharma, "Mapping, monitoring and conservation of Harike wetland ecosystem, Punjab, India, through remote sensing", int. j. remote sensing, vol. 22, no. 1, pp. 89–98, 2001
  5. Michael T. Coe, "Calculation of river discharge and prediction of lake height from satellite radar altimetry: Example for the Lake Chad basin", Water Resources Research, Vol. 40, 2004
  6. Douglas E. Alsdorf, Laurence C. Smith, and John M. Melack, "Amazon Floodplain Water Level Changes Measured with Interferometric SIR-C Radar", IEEE Transactions On Geoscience And Remote Sensing, Vol. 39, NO. 2, pp. 423-431, February 2001
  7. M. Govender , K Chetty 2 and H Bulcock , "A review hyperspectral remote sensing and its application in vegetation and water resource studies", Water Research Commission, Vol. 33, No. 2, PP. 145-152, 2007.
  8. Douglas E. Alsdorf, John M. Melack, Thomas Dunne, Leal A. K. Mertes, Laura L. Hess & Laurence C. Smith, "Interferometric radar measurements of water level changes on the Amazon flood plain", Nature, Vol. 404, 9 March 2000
  9. Nageswara Rao. K ,Swarna Latha. P , Arun Kumar. P, Hari Krishna. M , "Morphometric Analysis of Gostani River Basin in Andhra Pradesh State, India Using Spatial Information Technology", International Journal Of Geomatics And Geosciences, Vol. 1, No. 2, 2010
  10. Jean-François Cretaux , Muriel Berge-Nguyen , Marc Leblanc , Rodrigo Abarca Del Rio, Francois Delclaux Nelly Mognard , Christine Lion, Rajesh Kumar Pandey, Sarah Tweed , Stephane Calmant , and Philippe Maisongrande , "Flood Mapping Inferred From Remote Sensing Data",In proceeding of the Fifteenth International Conference on Water Technology , Alexandria, Egypt, 2011
  11. Arjen Y. Hoekstra, "The Global Dimension of Water Governance: Why the River Basin Approach Is No Longer Sufficient and Why Cooperative Action at Global Level Is Needed", Water, Vol. 3, pp. 21-46, 2011
  12. Jiqun Zhang, Kaiqin Xu, Masataka Watanabe, Yonghui Yang & Xiuwan Chen, "Estimation of river discharge from nontrapezoidal open channel using QuickBird-2 satellite imagery", Hydrological Sciences–Journal–des Sciences Hydrologiques, Vol. 49, No. 2, April 2004.
  13. Frederic Frappart , Frederique Seyler , Jean-Michel Martinez , Juan G. Leon , Anny Cazenave , "Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels", Elsevier, Vol. 99, pp. 387 – 399, 2005
  14. Cazenave A. Milly, Douville H. , Beneveniste J. , Lettenmaier D. and Kosuth P. , "International workshop examines the role of space techniques to measure spatio- temporal change in terrestrial waters" , AGU Trans. , Vol 85, No. 6, 2004
  15. Hahn Chul Jung and Doug Alsdorf, "Repeat-pass multi-temporal interferometric SAR coherence variations with Amazon floodplain and lake habitats", International Journal of Remote Sensing, Vol. 31, No. 4, pp. 881–901, 20 February 2010
  16. Michael T. Coe, "Calculation of river discharge and prediction of lake height from satellite radar altimetry: Example for the Lake Chad basin", Water Resources Res
  17. Smadi, "Pavement Management and Information Technology: Remote Sensing, GIS, and GPS", In Proceeding of the 6th International Conference on Managing Pavements, 2004
  18. D. H. A. Al-Khudhairy, C. Leemhuis, V. Hoffmann, Calaon, I. M. Shepherd, "Monitoring wetland ditch water levels in the North Kent Marshes, UK, using Landsat TM imagery and ground-based measurements", Hydrological Sciences-Journal-des Sciences Hydrologiques, Vol. 46, No. 4, August 2001
  19. Douglas E. Alsdorf, "Water Storage of the Central Amazon Floodplain Measured with GIS and Remote Sensing Imagery", Annals of the Association of American Geographers, Vol. 93, No. 1, pp. 55–66, 2003.
  20. Benktesh D Sharma, Jan Clevers, Reitze De Graaf and Nawa R Chapagain, "Assessing the land cover situation in Surkhang, Upper Mustang, Nepal, using an ASTER image", Special Reference to Natural Hazard Vulnerability Assessment ", International Scientific Research Journal, Vol. 3, No. 2, 2011
  21. R. . Kalaivani, P. Thangaraj, "An Efficient MechanismPredict the Stage of River using Artificial Neural Networkn Satellite Images", European Journal of Scientific Research, Vol. 50, No. 3 , pp. 380-394, 2011.
  22. Renaud Hostache, Xijun Lai, Jerome Monnier, Christian Puech, "Assimilation of spatially distributed water levels into a shallow-water flood model. Part II: Use of a remote sensing image of Mosel River", Elsevier, Vol. 390, pp. 257– 268, 2010.
  23. Ms. Venu Shah, Archana Choudhary and Prof. Kavita Tewari, "River extraction from satellite image "International Journal of Computer Science Issues, Vol. 8, No 2, July 2011.
  24. Scott L. Powell, Rick L. Lawrence, Christine Sommers Austin, and Shana Wood, "A Flexible Approach to Help Overcome Limitations of Moderate Resolution Satellite Imagery for Mapping Invasive Saltcedar on the Bighorn Special Reference to Natural Hazard Vulnerability Assessment ", International Scientific Research Journal, Vol. 3, No. 2, 2011
  25. Darrien Yau Seng Mah, Ching Poon Hii, Frederik Josep Putuhena and Sai Hin Lai, "River modelling to infer flood management framework", South African water research commission, Vol. 37, No. 1, January 2011
  26. R. K. Goswami, "Influence of Landform and Geomorphic Process On Topographic Evolution Of A River Island",International Journal of Engineering Science and Technology (IJEST), Vol. 3 No. 7 July 2011
  27. Pradeep K. Rawat, P. C. Tiwari and Charu C. Pan, , " Morphometric Analysis of Third order River Basins using High Resolution Satellite Imagery and GIS Technology:
  28. Simon Tong and Daphne Koller, "Support Vector Machine Active Learning with Applications to Text Classification", Journal of Machine Learning Research, pp. 45-66, 2001
  29. Kalaivani and Thangaraj, "An Effective Technique to Identify River's Stage through Satellite Images by Means of RBFNN", Computational Intelligence and Information Technology, Vol. 250, No. 3, pp. 822-825, 2011
  30. Angayarkkani and Radhakrishnan, "Support Vector Machines (SVM) Based Supervised System for Effective Forest Fire Detection Using Spatial Data", International Journal of Computer Engineering and Software Technology, Vol. 1, No. 2, pp. 57-71, 2010
  31. Hur and Jason Weston, "A User's Guide to Support Vector Machines", Technical Report, pp. 1-18, 2009
Index Terms

Computer Science
Information Sciences

Keywords

Satellite Image Processing River Stage Support Vector Machine (svm) Morphological Operation

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