The 26 December 2004 Indian Ocean tsunami had major effects on coastal communities and ecosystems. An assessment of coastlines after the tsunami indicates that coastal vegetation such as mangroves and beach forests helped to provide protection and reduce effects on adjacent communities. In recent years, mangroves and other coastal vegetation have been cleared or degraded along many coastlines, increasing their vulnerability to storm and tsunami damage. Establishing or strengthening greenbelts of mangroves and other coastal forests may play a key role in reducing the effect of future extreme events.
This paper describes how remote sensing techniques were used to study the effect of mangroves and other woody coastal vegetation as a protective measure against the 2004 Indian Ocean Tsunami. Remote sensing made it possible to compare pre-and post-Tsunami images of large areas. A study site was selected based on medium resolution Landsat imagery and existing topographic maps. Selection criteria included substantial damages reported, presence of woody vegetated and non-vegetated shorelines, homogeneous bathymetry and good coverage of preand post-Tsunami satellite imagery. The Pichawaram mangrove, Tamil Nadu, India, matched these criteria. Pre-and post-Tsunami Ikonos and QuickBird images were compared through the visual interpretation of pre-Tsunami coastal vegetation and post-Tsunami damage. The results were validated in the field. The analysis showed that mangrove forests and coastal shelterbelts provided protection from the Tsunami. This was concluded from analysing the spatial distribution of damage relative to woody vegetation along the coast as well as transects detailing the amount of damage behind the coastline and the coastal woody vegetation.
Development of a spectral library is a prerequisite for the higher order classification of satellite data and hyperspectral image analysis to map any ecosystem with rich diversity. In this study, sampling methodology, collection of field and laboratory spectral signatures and post processing methodologies were investigated for developing an exclusive spectral library of mangrove species using hyperspectral spectroscopic techniques. Canopy level field spectra and leaf level laboratory spectra were collected for 34 species (25 true and 9 associated mangroves) from two different mangrove ecosystems of the Indian east coast.Post processing steps such as removal of water vapour absorption bands, correction of drifts which occur due to the thermal properties of the instrument during data collection and smoothing of spectra for its further utilization were applied on collected spectra. The processed spectra were then compiled as spectral library.
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