LAUSR

A research study is conducted to develop remote sensing index(s) for mapping mangrove forest on regional scale using Landsat 8 dataset and to compare with the available vegetation indices. The study proposes a new forest indexing technique, i.e., Landsat 8 Mangrove Index (L8MI), with its two variants, namely L8MI_1 and L8MI_2, that are used to enhance the separability of mangrove forest from other vegetation lands by utilizing the Advanced Slope-based Indexing Technique (ASIT) and performing the classification of mangrove forest with the help of Otsu’s thresholding method. Furthermore, modification in available Normalized Difference Mangrove Index (NDMI) has been proposed by combining it with Soil-Adjusted Vegetation Index (SAVI). In this research study, a comparative analysis is performed between six vegetation indices and three proposed mangrove indices in order to explore the potential of mangrove forest mapping technique along the coastal region of Karachi, Pakistan. To evaluate the accuracy of proposed mangrove indices, 2000 reference points are selected to determine producer’s accuracy (PA), user’s accuracy (UA), overall accuracy (OA), and kappa coefficient (K). The comparative analysis shows an overall accuracy of greater than 95% with kappa coefficient greater than 0.85, which is greater classification accuracy than available vegetation indices compared in this study.