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Summary of accuracy assessment of seagrass AGC mapping using various inputs

Summary of accuracy assessment of seagrass AGC mapping using various inputs

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Figure 2. Research flowchart of mapping seagrass biodiversity...
Figure 3. Benthic habitat classification using RF algorithm with ntree...
Figure 4. Seagrass PC map with 17.1% RMSE derived from combined inputs...
Figure 6. Scatter plot between reference and estimated seagrass AGC (g...
+4 Summary of field seagrass data collected in the field. All data have...
Mapping Seagrass Biodiversity Indicators of Pari Island using Multiple WorldView-2 Bands Derivatives
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  • Aug 2023
Comprehensive information on seagrass biodiversity indicators, such as species composition, percentage cover, and biomass carbon stock, remains limited across various regions globally. Mapping these indicators using remote sensing images requires extracting maximum information from the input images to achieve effective results. This study aims to m...
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Context 1
... results of seagrass AGC mapping is consistent between input and ntree scenario ( Table 6). The most accurate map obtained from combined input with RMSE 5.0 g C m -2 , but the RMSE difference between the most and least accurate result is only 0.6 g C m -2 . ...
Context 2
... results of seagrass AGC mapping is consistent between input and ntree scenario ( Table 6). The most accurate map obtained from combined input with RMSE 5.0 g C m -2 , but the RMSE difference between the most and least accurate result is only 0.6 g C m -2 . ...