ANALYSIS OF CLASSIFICATION METHODS FOR MAPPING SHALLOW WATER HABITATS USING SPOT-7 SATELLITE IMAGERY IN NUSA LEMBONGAN ISLAND, BALI
DOI:
https://doi.org/10.30536/j.ijreses.2022.v19.a3748Keywords:
object-based, pixel-based, coral, seagrass, macroalgae, Lyzenga 2006Abstract
Shallow water habitat maps are crucial for the sustainable management purposes of marine resources. The use of a better digital classification method can provide shallow water habitat maps with the best accuracy rate that is able to indicate actual conditions. Experts use the object-based classification method as an alternative to the pixel-based method. However, the pixel-based classification method continues to be relied upon by experts in obtaining benthic habitat conditions in shallow water. This study aims to analyze the classification results and examine the accuracy rate of shallow-water habitats distribution using SPOT-7 satellite imagery in Nusa Lembongan Island, Bali. Water column correction by Lyzenga 2006 was opted, while object-based and pixel-based classification was used in this study. The benthic habitat classification scheme uses four classes: substrate, seagrass, macroalgae, and coral. The results show different accuracy is obtained between pixel-based classification with maximum likelihood models and object-based classification with decision tree models. Mapping benthic habitats in Nusa Lembongan, Bali, with object-based classification and decision tree models, has higher accuracy than the other with 68%.
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