Comparison of several vegetation indices for mangrove mapping using remotely sensed data (original) (raw)

Abstract

Application of remote sensing techniques for mangrove mapping and monitoring is increased and recognized for sustainable management of the resources to the country. Over the past few decades, the emergence of several vegetation index (VI) on remotely sensed data has certainly give significant impacts on mapping of the natural resources such as mangrove. On the other hand, the vegetation index (VI) has been used over last decade for the most suitable vegetation index in remote sensing studies. The objective of this study was to compare the performance of the several VI’s for mapping mangrove area using Landsat TM data. Each VIs can differentiate the mangrove classes based on their reflectance characteristics. In general the mangrove area was classified into five classes namely Avicennia, Avicennia-Sonneratia, Acanthus-Sonneratia, Mixed Sonneratia and Mixed Acrostichum. Results from several indices such as Normalized Difference Vegetation Index (NDVI), Infrared Percentage Vegetation Index (IPVI), Different Vegetation Index (DVI), Ratio Vegetation Index (RVI), Perpendicular Vegetation Index (PVI), Soil-Adjusted Vegetation Index (SAVI) and Modified Soil-Adjusted Vegetation Index (MSAVI) were compared and evaluated. It was found that SAVI performed the best followed by MSAVI, NDVI, PVI, IPVI, RVI and DVI with accuracies of 79.17%, 78.89%, 74.44%, 74.44%, 72.22%, 69.17% and 69.17% respectively. Keywords: remote sensing, vegetation indices, performance, mangrove, mapping.

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