Pilot Study and Development of Activity Data for Greenhouse Gas Inventory of Settlement Categories in Korea: A Case of Incheon Seo-gu

Sol-E,; Ham, Boyoung; Song, Cholho; Park, Eunbeen; Kim, Jiwon; Lee, Woo‐Kyun

doi:10.15531/ksccr.2020.11.3.187

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…Therefore, it is necessary to investigate the relationship between land use and land cover to utilize the land cover map, and spatial thresholds or ranges must be set. However, as in this study, when land use boundaries are set using a cadastral map (parcel unit), it is typically necessary to construct activity data for GHG removal/emissions sources, particularly the tree biomass, compared with a land cover map [ 44 , 45 ]. This method is more labor- and cost-intensive than using land cover methods.…”

Section: Discussionmentioning

confidence: 99%

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

Choi

Hong

Song

et al. 2023

Carbon Balance Manage

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Background Five ministries are involved in estimating the greenhouse gas (GHG) inventory in the South Korean land use, land-use change, and forestry (LULUCF) sectors. However, these ministries have not established a consistent land classification standard between land-use categories. Therefore, the GHG inventory is estimated at the approach 1 level with no spatial clarity between land-use categories. Moreover, the settlements category is not estimated because activity data and the spatial scope are lacking. This study proposed a methodology for constructing a land-use change (LUC) matrix in the LULUCF sector for improving approach level and estimating the GHG inventory in the settlements. Result We examined 10 sets of spatiotemporal data in South Korea to construct a LUC matrix. To maintain consistency in the spatial land classification, we constructed a LUC matrix using cadastral maps, which provide useful data for consistent land-use classification in South Korea. The LUC matrix was divided into remaining and land-converted settlements between 2005 and 2019 with estimated areas of 878,393.17 and 203,260.42 ha, respectively. CO2 emissions, according to Intergovernmental Panel Climate Change’s Guideline Tier 1, were estimated at 18.94 MtCO2 for 15 years, with an annual CO2 emission of 1.26 MtCO2 yr−1. CO2 emission by land conversion type was found to be the largest at 16.93 MtCO2 in the case of forest converted to settlements. In addition, the area with the largest CO2 emission density was Sejong-si at 7.59 tCO2/ha. Conclusion Based on reviewing available spatial data in South Korea, it is possible to improve Approach 3, which is more advanced than previous Approach 1 in the settlement category. In addition, the national GHG inventory also can be estimated by our constructed LUC matrix and activity data in this study. Under the many discussions about developing the Approach system, this study can provide in-detail information on developing LUC in South Korea in the settlement category as well as suggesting a methodology for constructing the LUC matrix for countries with similar problems to South Korea.

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Section: Discussionmentioning

confidence: 99%

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

Choi

Hong

Song

et al. 2023

Carbon Balance Manage

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“…Constructing activity data requires clear definitions and spatial extents for land use classification, but South Korea has no precise definitions and spatial extents for settlements [25][26][27]. Thus, to define the spatial extent of settlements, we examined the 2006 IPCC GL, available spatial data in South Korea and MRV guidelines for land use, land use change, and forestry (LULUCF) sectors, which informed the construction of activity data.…”

Section: Definition and Spatial Extent Of Settlementsmentioning

confidence: 99%

Development of Activity Data for Greenhouse Gas Inventory in Settlements in South Korea

Choi,

Kim,

Son

et al. 2024

Land

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In South Korea, Agriculture, Forestry, and Other Land Use (AFOLU) collates greenhouse gas (GHG) inventories. However, the settlement category lacks a clear definition of land use and activity data. This study proposed a method for examining the settlement spatial extent and constructing activity data to estimate GHG emissions and absorption as a pilot calculation, as well as to provide data for land use classification. Utilizing cadastral maps (CDMs), settlement spatial extents were determined, with settlements occupying approximately 11% of the total land area in 2019, or 9% excluding overlaps. Activity data for settlements were established through a sampling method and analysis of aerial orthoimages from 2000 and 2019. After removing overlaps with digital forest type maps and smart farm maps, settlement activity data covered approximately 18.47% based on CDMs, or 12.66% excluding overlaps. In 2019, CO2 emissions and absorptions were estimated at 622.16 ktCO2yr−1 based on CDMs and 242.16 ktCO2yr−1, excluding overlaps. To enhance GHG inventory calculation consistency and compliance with TACCC principles, clear spatial extents for settlements must be established. This entails constructing activity data and assessing GHG inventories accordingly. GHG inventory statistics should also inform future nationally determined contributions.

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“…Therefore, it is necessary to investigate the relationship between land use and land cover to utilize the land cover map, and spatial thresholds or ranges must be set. However, as in this study, when land-use boundaries are set using a cadastral map (parcel unit), it is typically necessary to construct activity data for GHG removal/emissions sources, particularly the tree biomass, compared with a land cover map [29,30]. This method is more labor-and cost-intensive than using land cover methods.…”

Section: Ghg Emission Statisticsmentioning

confidence: 99%

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

Choi¹,

Hong²,

Song³

et al. 2022

Preprint

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Background: Five ministries are involved in estimating the greenhouse gas (GHG) inventory in the South Korean land use, land-use change, and forestry (LULUCF) sectors. However, these ministries have not established a consistent land classification standard between land-use categories. Therefore, the GHG inventory is estimated at the approach 1 level. Moreover, the settlements category is not estimated because activity data and the spatial scope are lacking.Result: We examined 10 sets of spatiotemporal data in South Korea to construct a land-use change matrix. To maintain consistency in the spatial classification within the LULUCF sectors, we constructed a land-use change matrix using cadastral maps, which provide useful spatial data for consistent land-use classification of the land-use change matrix in South Korea. The land-use change matrix from a cadastral map was divided into remaining and land-converted settlements between 2000 and 2019 with estimated areas of 878,393.17 and 203,260.42 ha, respectively. CO2 emissions, according to Intergovernmental Panel Climate Change’s Guideline Tier 1, were calculated 18,942,905.68 tCO2 for 20 years, with an annual CO2 emission of 1,262,860.38 tCO2 yr-1. Conclusion: The reviewed available spatial data, method of land-use change matrix, and GHG inventory will facilitate the use of approach 3 for the land-use change matrix in South Korea’s LULUCF sectors and more accurate estimations of the GHG inventory.

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Pilot Study and Development of Activity Data for Greenhouse Gas Inventory of Settlement Categories in Korea: A Case of Incheon Seo-gu

Cited by 8 publications

References 10 publications

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

Development of Activity Data for Greenhouse Gas Inventory in Settlements in South Korea

Construction of land-use change matrix and estimation of greenhouse gas inventory focusing on settlements in South Korea

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