토지이용변화 매트릭스 구축을 위한 공간자료 간 중첩 분석: 경기도 지역을 중심으로

This study focused on the development of a land-use matrix to improve the accuracy of greenhouse gas inventories in the LULUCF (Land Use, Land-Use Change and Forestry) sector. The matrix was constructed by analyzing land-use data from Digital Forest-Type Maps (DFTM), Land Cover Maps (LCM), Smart Farm Maps (SFM), and Cadastral Maps (CDM) adhering to Transparency, Accuracy, Completeness, Comparability, Consistency (TACCC) principles. The results of our analysis showed an overlap of 3.5% and an omission of 10.3% in the sample area, mainly due to the conflation of land-cover and land-use concepts, as well as different parcel criteria. The largest overlap (24.2% of the total) occurred between the DFTM and miscellaneous land on the CDM. Similarly, omissions, which constituted 10.3% of the area, were attributed to the mixing of land-use and land-cover concepts. To address this issue, we evaluated the agreement between CDM and LCM, which was 71.3%. This indicates the need for a clear definition of land classification to ensure consistency within land-use matrices. In addition, the importance of establishing a priority ranking for land classification when using different spatial data, especially for internationally-reported areas such as forest and cropland, is emphasized. Lastly, a cost-effective NFI sampling point method can be considered for periodic updates of land-use and land-use change matrices. Considering these aspects, a land-use and land-use-change matrix should be constructed at the Approach 3 level to track land-use change for GHG inventory reporting for the LULUCF sector.