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The Sunderban Biosphere Reserve of southern West Bengal, India offers an ideal locale where Hyperspectral Remote Sensing may be applied for mapping diverse range of mangrove plantations that are unique to this pristine ecological system. This delta is characterized by both 'pure' and 'mixed' mangrove forest patches where photons interact with multiple species within the instantaneous field of view of the hyperspectral sensor, and multiple scattering between the vegetation canopies becomes significantly nonlinear. This paper attempts to apply the principle of multiple scattering of light in naturally occurring conditions and see how best they describe the resultant mixed spectra for certain endmember distributions. It is observed that natural forests, mixed mangrove forest in this case, are better suited for nonlinear scattering models as compared to linear models. The non-linear model has successfully identified areas of interaction of mangrove mixtures such as ceriops-excoecariaphoenix, excoecaria-avicennia alba avicennia officinalis etc. in the study area.

ABSTRACT:Hyperspectral image enhancement has been a concern for the remote sensing society for detailed end member detection. Hyperspectral remote sensor collects images in hundreds of narrow, continuous spectral channels, whereas multispectral remote sensor collects images in relatively broader wavelength bands. However, the spatial resolution of the hyperspectral sensor image is comparatively lower than that of the multispectral. As a result, spectral signatures from different end members originate within a pixel, known as mixed pixels. This paper presents an approach for obtaining an image which has the spatial resolution of the multispectral image and spectral resolution of the hyperspectral image, by fusion of hyperspectral and multispectral image. The proposed methodology also addresses the band remapping problem, which arises due to different regions of spectral coverage by multispectral and hyperspectral images. Therefore we apply algorithms to restore the spatial information of the hyperspectral image by fusing hyperspectral bands with only those bands which come under each multispectral band range. The proposed methodology is applied over Henry Island, of the Sunderban eco-geographic province. The data is collected by the Hyperion hyperspectral sensor and LISS IV multispectral sensor.

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