
Proceedings Paper
A new method for SARAL/AltiKa waveform classification: contextual analysis over the Maithon Reservoir, Jharkhand, IndiaFormat | Member Price | Non-Member Price |
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Paper Abstract
The Indian Space Research Organisation (ISRO) and the Centre National d'etudes Spatiales (CNES) jointly launched
SARAL/AltiKa (Satellite with ARgos and ALtiKa) in February 2013. AltiKa is the first mono frequency (Ka-band) radar
altimeter with dual frequency radiometer. SARAL/AltiKa promises reliable results on retrieving water level of inland
water and coastal bodies, though recognition pattern as well as interpreting and modeling of AltiKa waveforms at land
water boundary is still a challenge. Different Retracking methods are widely used for determining the water level more
correctly. An altimetry waveform also gives vital information about the reflecting surface. So, waveform classification is
many times needed for retrieving surface information or before applying retracking method. In this paper, SARAL/AltiKa
40 Hz waveform dataset (Pass #152) over the Maithon Reservoir, Jharkhand, India were classified using evolutionary
minimize indexing function (EMIF) with k-means. A fitness function was used in EMIF to map sampled AltiKa waveforms
into single valued scalar. Four waveform groups were identified according to reflection from water, land and land-water
boundary. Land-water boundary again divided into two classes viz., land-to-water and water-to-land based on direction of
the AltiKa pass over the reservoir. Normalized Differenced Water Index (NDWI) derived from Landsat 8 OLI and Google
Earth imagery of nearest date of AltiKa pass was used for accuracy assessment of the proposed method. It was found that
the waveforms were classified with 85.7 kappa accuracy. The results of the proposed EMIF will be helpful for identify the
SARAL/AltiKa waveforms classes over the inland water bodies.
Paper Details
Date Published: 7 May 2016
PDF: 7 pages
Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges, 98780G (7 May 2016); doi: 10.1117/12.2223777
Published in SPIE Proceedings Vol. 9878:
Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges
Robert J. Frouin; Satheesh C. Shenoi; K. H. Rao, Editor(s)
PDF: 7 pages
Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges, 98780G (7 May 2016); doi: 10.1117/12.2223777
Show Author Affiliations
Surajit Ghosh, Indian Institute of Remote Sensing (India)
Praveen Kumar Thakur, Indian Institute of Remote Sensing (India)
Suvajit Dutta, Indian Institute of Remote Sensing (India)
Rashmi Sharma, Space Applications Ctr. (India)
Praveen Kumar Thakur, Indian Institute of Remote Sensing (India)
Suvajit Dutta, Indian Institute of Remote Sensing (India)
Rashmi Sharma, Space Applications Ctr. (India)
Subrata Nandy, Indian Institute of Remote Sensing (India)
Vaibhav Garg, Indian Institute of Remote Sensing (India)
Shivprasad Aggarwal, Indian Institute of Remote Sensing (India)
Soumya Bhattacharyya, National Institute of Technology, Durgapur (India)
Vaibhav Garg, Indian Institute of Remote Sensing (India)
Shivprasad Aggarwal, Indian Institute of Remote Sensing (India)
Soumya Bhattacharyya, National Institute of Technology, Durgapur (India)
Published in SPIE Proceedings Vol. 9878:
Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges
Robert J. Frouin; Satheesh C. Shenoi; K. H. Rao, Editor(s)
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