Comparison of mangrove canopy covering accuracy using landsat 8 and landsat 9 imagery based on several vegetation indices in West Bali National Park

Abstract

The remote sensing implementation is beneficial as a means of monitoring the ecosystem. Landsat imagery is a remote sensing (open access) based data source with a long and wide monitoring period with good image quality. This study compares the accuracy of Landsat 8 and Landsat 9 satellite images in detecting mangrove canopy cover using 13 different remote sensing vegetation indices in the West Bali National Park, Indonesia. The mangrove canopy cover data was collected with the hemispherical photography method. A linear regression test was conducted to determine the relationship between the remote sensing vegetation indices and the field's percentage of mangrove canopy cover. The result indicated that Landsat 8 was more accurate in detecting mangrove canopy cover than Landsat 9. Of the 13 remote sensing indices evaluated, the Chlorophyll Vegetation Index (CVI) had the highest accuracy, with R2 values of 0.86 and 0.75 for Landsat 8 and 9, respectively.*