AMMI Automatic Mangrove Map and Index: An Analytical Study on Satellite Imageries at Aru Islands, Maluku, Indonesia
The spectral reflectance features in several vegetation indices have been used to generate mapping on mangroves utilising satellite imageries. Hundreds of scientific articles have used and implemented vegetation indices in mangrove research, however the majority still employ the manual digitization method. Satellite imaging is useful for reducing impediments in inaccessible stations caused by mangrove root system complexities, heavy mud, and lost location signals. The creation of a mangrove vegetation index capable of automatically tracing and recording mangroves with canopy density precision, as depicted visibly in satellite pictures, is a pressing need. The Aru Islands, which are part of Maluku Province, are the Indonesian archipelago’s farthest-flung islands. The western half of the islands is a jumble of corals and muds from nearby river mouths, while the eastern region contains small islands with mangrove vegetation surrounded by coral reefs. This study examines the spectral features of a variety of widely accessible satellite photos. The goal is to create an algorithm that accurately captures and traces the mangroves extent as depicted visually in the Red-Green-Blue composite image, is easy to use, fast, and displays the relative index of mangrove canopy density at the same time. As a result, the author offers the following algorithm: (NIR-Red)/(Red+SWIR1)*(NIR-SWIR1)/(SWIR1-0.65*Red)*(NIR-SWIR1)/(NIR-SWIR1)/(SWIR1-0.65*Red). The first equation (NIR-Red)/(Red+SWIR1) should trace the land, strengthen spectral vegetation, and weaken spectral features of the waters, such as coral reefs, mudflats, turbidity, and marine phenomena. The second equation (NIR-SWIR1)/(SWIR1-0.65*Red) is used to track and capture the spatial of mangroves, as well as display the canopy density index. The performance of Landsat 5 TM, Landsat 7 ETM, Landsat 8 OLI, and Sentinel 2 pictures in numerous mangrove forests has been proven. The technique automatically captures the area of mangroves, as demonstrated graphically in the Red Green Blue composite of satellite pictures. With an R2 of 0.99, the resulting index is substantially connected to two existing Vegetation Indices. The algorithm’s benefit is that it performs well, is simple to use, produces mangrove maps faster, informs the index, and efficiently monitors the changing conditions of mangroves over time.
Research Center for Oceanography, Indonesian Institute of Sciences, Jakarta, Indonesia.