Automatic identification of saline blanks and pattern of related mangrove species on hyperspectral imagery

S. Chakravortty, D. Ghosh
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引用次数: 3

Abstract

This research attempts to apply hyper spectral imagery to identity saline blank patterns within mixed mangrove forest of the Sunderban Bio-geographic Province of West Bengal, India. Identification of patterns of changing mangrove species around saline blanks on hyperspectral image has also been attempted. This research uses derivative analysis to identify hyperspectral wavelengths that are sensitive to the presence of minerals comprising saline blanks. These wavelengths have been considered for development of a new saline blank identification model. Spectral signatures of mangrove species endmembers have been automatically extracted using NFINDR algorithm and considered as input for spectral unmixing of saline blank and mangrove endmembers. The fractional abundance estimates of spectral unmixing applied on time series hyperspectral data of the study area indicate that, over the years, as saline blanks become more abundant in the region, the presence of mangrove species (even the salt tolerant ones) gets reduced. However, in areas where the mangrove species still dominate and saline blanks are in its formative stage, there is still a possibility of re-growth of the saline prone mangrove species. It is found that mangrove species namely, Excoecaria agallocha and Ceriops Decandra are prevalent around the saline blank areas. Others like Avicennia marina and Avicennia alba also exist in certain locations of saline blanks.
基于高光谱影像的盐水空白区自动识别及相关红树林物种模式
本研究试图应用高光谱图像来识别印度西孟加拉邦桑德班生物地理省混合红树林中的盐水空白模式。利用高光谱图像识别盐碱地周围红树林物种的变化模式也进行了尝试。本研究使用衍生分析来识别高光谱波长,这些波长对含盐空白的矿物的存在很敏感。这些波长已被考虑用于开发新的盐水空白识别模型。利用NFINDR算法自动提取红树林物种端元的光谱特征,并将其作为盐水空白和红树林端元光谱分离的输入。应用于研究区时间序列高光谱数据的光谱分解的分数丰度估计表明,随着时间的推移,随着该地区盐空白的丰富,红树林物种(即使是耐盐物种)的存在也减少了。然而,在红树林物种仍然占主导地位,盐水空白处于形成阶段的地区,仍有可能重新生长出易含盐的红树林物种。研究发现,在盐碱地空白区周围,红树种类主要有红树、红树和红树。其他的如海棠和白海棠也存在于盐水空白的某些位置。
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