To report changes in land use, the forestry sector, and land-use change matrix (LUCM), monitoring is necessary in South Korea to adequately respond to the Post-2020 climate regime. To calculate the greenhouse gas statistics observing the principle of transparency required by the Climate Change Convention, a consistent nationwide land-use classification and LUCM are required. However, in South Korea, land-use information is available from the 5th National Forest Inventory conducted in 2006 onwards; therefore, developing methods to determine historical LUCM information, including the base year required by the Intergovernmnetal Panel on Climate Change (IPCC), is essential. To determine the optimal sampling intensity for measuring systematic land-use changes and to estimate the corresponding area of land-use categories for previously unmeasured years, seven intensities—2 × 2 km to 8 × 8 km—were tested using the areas of the 3rd and 4th aerial photographs in time series for forestland, cropland, grassland, wetland, and settlements, according to their standard deviations and estimates of uncertainty. Analyses of statistical accuracy, statistical efficiency, economic efficiency, and convenience showed that a sampling intensity of 4 × 4 km was ideal. Additionally, the categorized areas of unmeasured land-use years were calculated through linear interpolation and extrapolation. Our LUCM can be utilized for developing a national greenhouse gas inventory.

In order to address the enhanced transparency framework in the Paris Agreement, the completeness of the National GHG Inventory should be ensured. Up-to-date information on changes in both land-use categories and area by land-use conversion must be included in the Land-Use Change Matrix (LUCM), which contains critical activity data for the LULUCF (Land Use, Land-Use Change and Forestry) sector. This study was conducted to determine the optimal sampling intensity and develop the LUCM through a comparison of different sampling intensities. In this study, an empirical analysis was based on relative standard error and relative efficiency in uncertainty assessment for seven sampling intensities from 2 to 8 km. The findings indicate no clear difference in the uncertainty by sampling intensity concerning forest land and cropland, which account for large areas of Gangwon-do and Jeollanam-do. In contrast, the uncertainties for grassland and wetlands, each of which covers less than 10% of the total area, were decreased with increasing sampling intensity, but no statistical significance was found. To improve the LUCM at the national level, it is therefore necessary to select an efficient sampling intensity because there are trade-offs between statistical accuracy and cost regarding the application of different sampling approaches.

The greenhouse gas reduction function of forests is crucial globally in ameliorating climate change. Varying research attempts to assess dead organic matter and carbon stock volume in soil have been conducted. The purpose of this study was to analyze changes in the occurrence of coarse woody debris (CWD) and related carbon stocks using data from the National Forest Inventory (NFI). To monitor changes in forest resources over time, this study used NFI data (2006-2020) that were collected from permanent sample plots every five years; 1,903 sample plots in which CWD occurred were analyzed at each time point and CWD volume was calculated based on tree stem volume. Carbon stocks of CWD were estimated by applying basic woody density and carbon fraction to CWD by tree type and tree decay level. The average volume of CWD decreased from 23.04 to 14.83 ㎥ haSUP-1/SUP and carbon stocks of CWD were also reduced from 3.36 to 1.86 ton C haSUP-1/SUP. This analysis estimated carbon stocks of CWD in forests nationwide and the results can be utilized to build a greenhouse gas inventory. Long-term monitoring and research are needed to identify the changing characteristics of CWD carbon storage. As carbon storage in forests is interconnected, monitoring and model development should include trees, CWD, forest floor litter, and soil carbon cycles. Furthermore, an analysis of the effect of anthropogenic activities on carbon cycles in future research would be useful.