Development of a Land-Use Change Matrix at the National Level using the Point Sampling Method

Yim, Jong-Su; Moon, Ga Hyun; Shin, Man-Yong

doi:10.15531/ksccr.2019.10.4.299

Cited by 4 publications

(1 citation statement)

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“…Some nations calculate the optimal sampling intensity by considering national land-use characteristics [14]. In light of the IPCC policies and other national examples, South Korea should calculate the unmeasured areal extents of each land-use category using linear interpolation and extrapolation and employ these data in creating an LUCM [5,23,24]. To establish the systematic statistics of the national GHG inventory for the LULUCF, this study analyzed the sampling intensity most adequate for LUCM development in South Korea.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sampling Intensity in South Korea for a Land-Use Change Matrix Using Point Sampling

Moon

Yim

Moon

2021

Land

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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.

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Section: Introductionmentioning

confidence: 99%