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A new method for SARAL/AltiKa Waveform Classification: contextual analysis over the Maithon reservoir, Jharkhand, India

机译:SARAL / AltiKa波形分类的新方法:印度贾坎德邦Maithon水库的上下文分析

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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.
机译:2013年2月,印度空间研究组织(ISRO)和国家航天中心(CNES)共同发射了SARAL / AltiKa(卫星与ARgos和ALtiKa一起)。AltiKa是第一台具有双频的单频(Ka波段)雷达高度计频率辐射计。 SARAL / AltiKa有望在取得内陆水域和沿岸水体的水位方面取得可靠的结果,尽管识别模式以及对陆面水边界处AltiKa波形的解释和建模仍然是一个挑战。为了更正确地确定水位,广泛使用了不同的重新跟踪方法。高程波形还提供有关反射面的重要信息。因此,检索表面信息或应用重跟踪方法之前,需要多次进行波形分类。在本文中,使用具有k均值的演化最小索引函数(EMIF)对印度贾坎德邦Maithon水库的SARAL / AltiKa 40 Hz波形数据集(第152次通过)进行了分类。在EMIF中使用了适应度函数将采样的AltiKa波形映射为单值标量。根据水,陆地和陆地-水边界的反射,确定了四个波形组。根据AltiKa穿过水库的方向,陆水边界又分为两类,陆对水和水对陆。利用Landsat 8 OLI和AltiKa通行证最近日期的Google Earth影像得出的归一化差分水指数(NDWI)用于所提出方法的准确性评估。发现波形以85.7 kappa精度分类。拟议的EMIF的结果将有助于识别内陆水体的SARAL / AltiKa波形类别。

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