Comparison of Three Kinds of Methods on Estimation of Forest Carbon Stocks Distribution Using National Forest Inventory DB and Forest Type Map

Kim, Kyoung-Min; Roh, Young-Hee; Kim, Eun-Sook

doi:10.11108/kagis.2014.17.4.069

Cited by 10 publications

(5 citation statements)

References 18 publications

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“…In the case of s3, Moran's I, values of the OLS and GWR models were close to 0, and thus, there was no spatial autocorrelation. Similarly to that reported by Kim et al, (47) Moran's I was lower in GWR than in OLS and the vegetation distribution characteristics were differently composed with clusters. Therefore, the GWR model is more suitable when considering the spatial effect in the current study area, as shown in Table 4.…”

Section: Evaluating Model Fitnesssupporting

confidence: 84%

Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model

Jeongmook¹,

Choi²,

Lee³

2019

Sensors and Materials

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The objective of this study is to evaluate the spatial distribution patterns of species diversity at different spatial scales, focusing on the Baekdudaegan Protected Area, which is a biodiversity hotspot in the Republic of Korea. The tree species diversity index (Shannon-Weaver index; H′) was calculated using tree species data from a 1:5k forest-type map, and the spatial analysis was performed with a 1 × 1 km 2 grid. Ten factors were selected to estimate the impact of topographic (elevation, slope, northern slope, curvature, wetness, and relief) and geographic (distances from water, road, forest road, and urban area) factors on H′ using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. H′ increased with the spatial scale. Also, the coefficient of determination (R²) of the GWR and OLS models increased proportionally and the R² of the GWR model was higher than that of the OLS model. Corrected Akaike information criterion (AICc) was lower in the GWR model than in the OLS model, which indicates that the GWR model fits the calculated H′ better than the OLS model. Thus, the GWR model is considered to be more practical than the OLS model for understanding the effects of topographic and geographic factors on H′ at different scales.

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Section: Evaluating Model Fitnesssupporting

confidence: 84%

Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model

Jeongmook¹,

Choi²,

Lee³

2019

Sensors and Materials

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“…In this study, the loss proportion for national forests was much higher than that for privately owned forests. It is recommended in the narrow approach of the IPCC guideline that spatial data be presented in the case of forest management activities [15,23]. Currently, however, the text-based data on forest management activities applied in Korea has its limitations in underestimation due to loss of data when the data are formed.…”

Section: Estimation Of Forest Management Ratiomentioning

confidence: 99%

“…The Japanese government has applied a forest management ratio-managed area to total forest area-to demonstrate their additional efforts on forest management over the country. The forest management activities should, however, be clearly classified from spatial, administrative, and ecological perspectives [20,23]. Japan has established not only its system to measure the amount of carbon stored in sinks resulting from forest management activities but also its own method to verify objective estimation of the amount, thereby implementing its annual plans for carbon accounting [24].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Patterns of Forest Management Activities from 1990 to 2019 to Demonstrate Additionality for Climate Change Mitigation in the Forest Sector of South Korea

Lee

Han

et al. 2021

Forests

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Forest management is key to maintaining and increasing carbon sinks in forests. In the context of climate change mitigation, the exact number of carbon sinks associated with forest management is estimated as the additionality of activities, which means net greenhouse gas (GHG) removals or carbon sequestration over and above those that would have arisen even in the absence of a given activity. This study analyzes the spatial and temporal patterns of forest management activities to present the forest management ratio, of managed area to the total forest area, as an indicator of additionality in forest management in South Korea. Forest management activities based on the IPCC guidelines were spatially constructed, and the characteristics of managed and protected forests from 1990 to 2019 were analyzed. The results indicate that between the managed forests and roads, 90% of the management activities in private forests occurred within 214 m of the road, and 70% of the activities in the national forest occurred within 234 m. Management took place in easy-to-access places with gentle slopes and low elevations. The proportion of protected forests above 40 years old is 87.2%, higher than the average of 72% in South Korea, and it is expected that most forests will age and their carbon absorption capacity will decrease by 2050. The area of tree planting and thinning is approximately 290 thousand ha per year, which could potentially increase the forest management ratio by up to 4.5% per year. However, the actual increase was at an average of 1.4%, owing to the omission of exact information on management activities, such as spatial coordinates and overlapping practices in the same management unit. The forest management ratio in South Korea as of 2019 was 53.4%; therefore, the amount of GHG removal in the forest sectors was 53.4% of total absorption per year. Thus, it is necessary to make efforts to increase the ratio to enhance the contribution of forest sectors to climate change mitigation for the country.

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“…For example, in South Korea, SDPT v1.0 included planted forest and tree crop species information from the Korean Forest Service. For v2.0, we discovered an additional planted forest dataset by Kim et al (2009). We appended this dataset to the Korean Forest Service data from v1.0 as it did not use more recent source imagery, did not have species information, and did not have more extensive geographic coverage.…”

Section: Boundary Data Cleaning and Processingmentioning

confidence: 99%

“…These data are supplemented by a study from Kim et al (2009) on forest-type map production in Korea that includes planted forest data.…”

Section: South Koreamentioning

confidence: 99%

Spatial Database of Planted Trees (SDPT Version 2.0)

Richter,

Goldman,

Harris

et al. 2024

WRIPUB

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This paper describes the methods for updating the Spatial Database of Planted Trees (SDPT) in three areas: boundaries, to spatially differentiate planted forests and tree crops from natural and seminatural forests on a global scale; tree species information, to help screen for the illegal exportation of timber products; and carbon sequestration rates, or removal factors, to improve maps of atmospheric carbon dioxide sequestration by planted trees.

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Comparison of Three Kinds of Methods on Estimation of Forest Carbon Stocks Distribution Using National Forest Inventory DB and Forest Type Map

Cited by 10 publications

References 18 publications

Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model

Spatial Distribution Characteristics of Species Diversity Using Geographically Weighted Regression Model

Spatial and Temporal Patterns of Forest Management Activities from 1990 to 2019 to Demonstrate Additionality for Climate Change Mitigation in the Forest Sector of South Korea

Spatial Database of Planted Trees (SDPT Version 2.0)

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