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Estimating tropical forest stand volume using Sentinel-2A imagery

Forest stand volume is one of the important variables to assess forest management. In this study, the integration of Sentinel-2A images and forest field data was used to estimate the forest volume for separate stratum and for the entire area of the study area. Accordingly, the forest area was divided into relative homogeneous strata as dense forests and open forests. A total of 202 sample plots were placed throughout the forest strata to measure relevant variables such as diameter at breast height and tree height. Spectral bands and vegetation indices within the plot were also extracted to correlate with forest stand volume. The predictions were separately tested for the entire area and for each forest stratum. The result indicated 8 out of 21 predictor variables (spectral and vegetation indices) were selected as optimal variables to build the estimate models. The results show that when separable stratum prediction is used instead of entire area estimation, the accuracy of estimates is more likely to be improved, especially with the forest stand under low disturbance. The accuracy of open forest was also found higher dense forest.