Analysis Of The Mangrove Structure In The Dong Rui Commune Based On Multispectral Unmanned Aerial Vehicle Image Data

Abstract

Mangroves are one of the most important types of wetlands in coastal areas and perform many different functions. Assessing the structure and function of mangroves is a premise for the management, monitoring and development of this most diverse and vulnerable ecosystem. In this study, the unmanned aerial vehicle (UAV) Phantom 4 Multispectral was used to analyse the structure of a mangrove forest area of approximately 50 hectares in Dong Rui commune, Tien Yen district, Quang Ninh Province – one of the most diverse wetland ecosystems in northern Vietnam. Based on the visual classification method combined with the results of field taxonomic sampling, a mangrove tree classification map was established for UAV with three species, Bruguiera gymnorrhiza, Rhizophora stylosa, and Kandelia obovata, achieving an overall accuracy = 86.28%, corresponding to a Kappa coefficient =0.84. From the images obtained from the UAV, we estimated and developed maps and assessed the difference in tree height and four vegetation indices, including the normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), enhanced vegetation index (EVI), and green chlorophyll index (GCI), for three mangrove plant species in the flying area. Bruguiera gymnorrhiza and Rhizophora stylosa reach an average height of 4 to 5 m and are distributed mainly in high tide areas. Meanwhile, Kandelia obovata has a lower height (ranging from 2 to 4 m), distributed in low-tide areas, near frequent flows. This study confirms the superiority of UAV with red edge and near-infrared wave bands in classifying and studying mangrove structures in small-scale areas.