Identification of Mangrove Cover in Banten Bay using Google Earth Engine
Abstract
The existence of mangroves is a factor in the natural preservation of an area. The goal of this research is to identify the mangrove forest cover in Teluk Banten using guided classification based on machine learning available in GEE.The method used in this research is to visually analyze the spectral value of Sentinel 2A. The composite images used in the analysis include Bands 8A114 and Bands 8A115. Determination of subset images (cropping) is carried out to accommodate the size of the image according to the size of the research location to determine its distribution, extent and changesMangrove classification can be done using various digital image classification approaches, including pixel-based classification, object-based classification, and supervised and unsupervised learning. The choice of classification scheme depends on the purpose of the study and the available data. The mangrove cover area that is seen in red shows that the results of using the CART model can determine the area that is included in the mangrove class.Mangrove identification using GEE machine learning can produce mangrove cover. The result of mangrove cover area depends on how much training area is given. Training areas are used by CART in determining which areas are categorized as mangrove cover.
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References
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