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 Far...
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| Published in | 한국기후변화학회지 Vol. 15; no. 1; pp. 15 - 34 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Korean |
| Published |
한국기후변화학회
01.02.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2093-5919 2586-2782 |
| DOI | 10.15531/KSCCR.2024.15.1.015 |
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| Abstract | 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. KCI Citation Count: 0 |
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| AbstractList | 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. KCI Citation Count: 0 |
| Author | 이우균(Lee, Woo-Kyun) 최솔이(Choi, Sol-E) 송철호(Song, Chol-Ho) 김휘진(Kim, Whijin) 임종수(Yim, Jong-Su) 이선정(Lee, Sun Jeong) |
| Author_xml | – sequence: 1 fullname: 최솔이(Choi, Sol-E) – sequence: 2 fullname: 송철호(Song, Chol-Ho) – sequence: 3 fullname: 김휘진(Kim, Whijin) – sequence: 4 fullname: 이선정(Lee, Sun Jeong) – sequence: 5 fullname: 임종수(Yim, Jong-Su) – sequence: 6 fullname: 이우균(Lee, Woo-Kyun) |
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| DocumentTitleAlternate | Spatial data overlap analysis for constructing a land-use and land-use-change matrix: A focus on Gyeonggi-do |
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| Keywords | Land-use and Land-use Change Matrix LULUCF LULUCF’s Approach Levels Spatial Data Matching for LULUCF National Inventory Report Greenhouse Gas Inventory TACCC Principles |
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| Title | 토지이용변화 매트릭스 구축을 위한 공간자료 간 중첩 분석: 경기도 지역을 중심으로 |
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