PERFORMANCE OF INTRINSIC AND SOIL LINE-BASED VEGETATION INDICES IN MANGROVE MAPPING IN MALAYSIA

The use of vegetation indices of remote sensing data in vegetation mapping has been long recognised. However the accuracy of mapping by using vegetation indices model has limitation, and has so far not been investigated. This study analysed the performance of the several intrinsic-based vegetation indices (Normalized Difference Vegetation Index-NDVI and Ratio Vegetation Index- RVI) and soil line-based vegetation indices (Perpendicular Vegetation Index-PVI, Soil-Adjusted Vegetation Index-SAVI and Modified Soil-Adjusted Vegetation Index-MSAVI) for mangrove mapping in Kelantan Delta, Malaysia. Landsat TM was used as a primary data to derive mangrove vegetation class from five vegetation indices model. A total of five mangrove classes consist of Avicennia-Sonneratia, Avicennia, Acanthus-Sonneratia, Mixed-Acrostichum and Mixed Sonneratia with accuracy 72.67% were determine from unsupervised classification. Then the models were applied on classified image, resulted a mangrove classes were mapped into three and four classes, respectively. The performance each VI’s were analysed in accuracy assessment. The accuracy assessment of vegetation indices were ranged from 69.17% to 79.14%. The results revealed that the SAVI was better performance discriminate mangrove classes in four classes compared to others indices with accuracy 79.14%. It might due to sensitiveness of SAVI model in discriminate the full range of vegetation covers in muddy area. The capability of Landsat TM in mapping mangrove in this study using VI’s models showed the better result , however the performance of VI’s is need to be further investigated for specific use of mangrove resources. This is important where accurate information on mangrove biodiversity status in all habitat level is needed for conservation and monitoring towards achieving sustainable development to the country