| Abstrak/Abstract |
The condition of benthic habitats in optically shallow sea waters becomes important
information in the inventory and processing of coastal resources. Remote sensing is effective
and efficient in mapping benthic habitats. This study aims to apply absolute and relative water
column correction methods in order to map benthic habitats on Parang Island using
PlanetScope image. The benthic habitat classification scheme used consists of coral reefs,
seagrass, macroalgae, and substrate. We compared the accuracy of benthic habitat map based
on absolute and relative water column correction methods. The classification methods used are
the Maximum Likelihood (ML) algorithm and Support Vector Machine (SVM). The results
showed that benthic habitat map with the highest accuracy was obtained by a combination of
Lyzenga-ML at 61.63% followed by Purkis-SVM at 59.18%, Lyzenga-SVM at 41.90%, and
Purkis-ML 16.87%. The results show that the Lyzenga water column correction method is the
best choice in mapping benthic habitats. |
