A tool for SARAL/AltiKa waveform clustering

Surajit Dutta, Suvajit Ghosh, Praveen Kumar Thakur

Abstract


This article describes a classification tool to cluster the SARAL/AltiKa waveforms. The tool was made by a Python script. Radar altimetry systems (e.g., SARAL/AltiKa) determine the distance from the satellite to a target surface by measuring the satellite-to-surface round-trip time of a radar pulse. An altimeter waveform represents the energy reflected by the earth’s surface to the satellite antenna with respect to time. This tool clusters the altimetric waveforms data into desired groups. For the clustering, we used evolutionary minimise indexing function (EMIF) with k-means cluster mechanism. The idea is to develop a simple interface which takes the altimetry waveforms data from a folder as inputs and provides single value (using EMIF algorithm) for each waveform which will be further used for clustering. The tool is simple and easy to interact with the users, and it also takes very low disk space.


Keywords


SARAL/AltiKa waveforms; evolutionary minimize indexing function (EMIF); python

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References


Ghosh S, Thakur P, Dutta S, et al. A new method for SARAL/AltiKa Waveform Classification: contextual analysis over the Maithon reservoir, Jharkhand, India. In SPIE Asia-Pacific Remote Sensing International Society for Optics and Photonics 98780G-98780G, 2016.

Ghosh S, Thakur PK, Garg V, et al. SARAL/AltiKa Waveform Analysis to Monitor Inland Water Levels: A Case Study of Maithon Reservoir, Jharkhand, India. Marine Geodesy 2015; 38(1): 597-613.

Verron J, Sengenes P, Lambin J, et al. The SARAL/AltiKa altimetry satellite mission. Marine Geodesy 2015; 38(sup1): 2-21.

Chelton DB., Ries JC., Haines BJ, et al. Satellite altimetry. International Geophysics 2001, 69, 1-ii.

Guo JY, Hwang CW, Chang XT, et al. Improved threshold retracker for satellite altimeter waveform retracking over coastal sea. Progress in Natural Science 2006; 16(7): 732-738.




DOI: http://dx.doi.org/10.24294/jgc.v1i2.751

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