A new method for SARAL/AltiKa waveform classification: contextual analysis over the Maithon Reservoir, Jharkhand, India

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.