## 5 Discussion
### Stem Volume Method for CO\({}_{2}\) Sequestration Estimates
#### 5.3.2 Validity of the Method in Comparison  
For further knowledge, other estimation methods were investigated and compared to the results of this study. Four main methods were examined and compared; one is from this study, the second is from the conventional method by [PERSON] and [PERSON] [15], the third is the work conducted by [PERSON] and [PERSON] [7], and the last is from the National Institute for Environmental Studies (NIES) [8] of the IPCC report for the forest carbon sink. The total CO\({}_{2}\) estimation is summarized in Table 8 [7,8,15] for all four methods. For the conventional method, the sequestration value was used along with the total forest areas obtained from our work. The stem volume method used in this study, shows a result of 111.27 Mt-CO\({}_{2}\) by considering both forest type and tree age information (coniferous: 85.0 Mt-CO\({}_{2}\); deciduous broadleaf: 21.61 Mt-CO\({}_{2}\); evergreen broadleaf: 4.76 Mt-CO\({}_{2}\)). With the conventional method [15] using the averaged value compared to the results in this study, a large overestimation of the sequestration can be observed, because the sequestration value dumps everything into one category, omitting tree age information and ignoring lower sequestration stages, leading to high overestimation of the result. [PERSON] and [PERSON] [7] and NIES [8] show similar estimation values, however for the former study, the result is obtained by using the land use model and carbon stock growth model and estimates the sequestration value classifying the forests as planted and natural forests. Planted forests showed an estimation of 56.1 Mt-CO\({}_{2}\), while natural forests were estimated at 17.6 Mt-CO\({}_{2}\), and then summed for a total result of 73.7 Mt-CO\({}_{2}\). The most interesting result is from the NIES, whose approach used forest registration data from each prefectural government and differentiated the forests by tree type, collecting annual growth information for each, and then performing an estimation by multiplying the annual sequestration value by the total forested area of each tree type, which is similar to this work. They have not only made calculations for aboveground sequestration but also for the litter and soil. However, the majority of the sequestration results from the aboveground biomass (aboveground: 76.53 Mt-CO\({}_{2}\); litter: 0.41 Mt-CO\({}_{2}\); soil: 2.58 Mt-CO\({}_{2}\); dead tree: -1.85 Mt-CO\({}_{2}\)). If we assume that the methods used by the NIES [8] study are likely to be the most accurate estimation of the natural environment, the remote sensing method applied in this study shows only a 43% overestimation in comparison. This difference can be explained from the errors discussed in the previous section. If methods are developed to reduce those potential errors, our results may become somewhat similar to the results by the NIES. However, even though the NIES results raise some questions, such as the uncertainty of the total forest area, which is important as mentioned, total CO\({}_{2}\) is calculated by multiplying the sequestration value by the total forested areas. The data from prefectural government is sometimes unclear, especially in terms of the area that the forest covers, as researchers have noted (the uncertainty rate of NIES estimates shows 5% for forest areas without discriminating by forest type [8]), so there is a possibility that the NIES is underestimating forest capacity. What is significant about this work compared to the NIES is that this method can be performed throughout various seasons in the future in less time and with lower labor costs through the use of remote sensing data. The work performed by NIES is possible in countries where a large database of forest information is compiled for use in applications, but in countries where this is not the case, it will be very difficult to implement such a method. On the other hand, the method developed in this study can be applied in any country as long as the required data sets are available.