• Korean Journal of Soil Science and Fertilizer
• /
• v.42 no.3
• /
• pp.160-166
• /
• 2009

We estimated site productivity for unstocked land based on the relationship between site index (i.e., average height of dominant trees at fixed age) and soil physico-chemical properties of Pinus densiflora stands. Site index relates to a direct method of determining a tree's response to a specific environment such as forest soil and climate conditions. We selected 78 sites in 22 P. densiflora stands of central temperate forest zone, and sampled soils for physicochemical analyzing. And 13 properties of soils were statistically treated by stepwise regression. In the degree of contribution of the variables to site index, the highly effective variables in A horizon were OM, clay content, sand content, available $P_2O_5$, and Exch. $Ca^{{+}{+}}$ inorder, and in B horizon T.N., O.M., Soil pH, cation exchange capacity(C.E.C.), and sand content in order. In both A and B horizon of the soil for P. densiflora stands, the variables commonly contributed to the site index were sand content and OM. These results may be useful to provide not only important criteria for establishment of Pinus densiflora stand sespecially in unstocked land but also aguidance for reforestation.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.4
• /
• pp.81-99
• /
• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.2
• /
• pp.44-55
• /
• 2018

The importance of establishing a greenhouse gas inventory is emerging for policymaking and its implementation to cope with climate change. Thus, it is needed to establish Approach 3 level Land Use, Land-Use Change and Forestry (LULUCF) matrix that is spatially explicit regarding land use classifications and changes. In this study, four types of spatial information suitable for establishing the LULUCF matrix were analyzed - Cadastral Map, Land Cover Map, Forest Map, and Biotope Map. This research analyzed the classification properties of each type of spatial information and compared the quantitative and qualitative characteristics of the maps in Boryeong city. Drawn from the conclusions of the quantitative comparison, the forest area showed the maximum difference of 50.42% ($303.79km^2$) in the forest map and 46.09%($276.65km^2$) in the cadastral map. The qualitative comparison drew five qualitative characteristics: data construction scope difference, data construction purpose difference, classification standard difference, and classification item difference. As a result of the study, it was evident that the biotope map was the most appropriate spatial information for the establishment of the LULUCF matrix. In addition, if the LULUCF matrix is made by integrating the biotope, the forest map, and the land cover map, the limitations of each spatial information would be improved. The accuracy of the LULUCF matrix is expected to be improved when the map of the level-3 land cover map and the biotope map of 1:5,000 covering the whole country are completed.

• Journal of Korean Society of Rural Planning
• /
• v.11 no.4 s.29
• /
• pp.47-57
• /
• 2005

The goal of this research is to evaluate landscape-ecological characteristics of watersheds in the Nakdong River Basin by using Geogaphic Information System (GIS) and landscape indices for integation of spatio-temporal informations and multivariate statistical techniques for quantitative analysis of forest landscape. Fragmentation index and change matrix techniques using factor analysis and grid overlay method were used to efficiently analyze and manage huge amount of information for ecological-environmental assessment (land-cover and forest landscape patterns). According to the results based on the pattern analysis of land-cover changes using the change detection matrix between 1980s and 1990s, addition on 750km$^2$ became urbanized areas. The altered 442.04km$^2$ was agricultural areas which is relatively easy for shifting of land-use, and 205.1km$^2$ of forests became urbanized areas, and average elevation and slope of the whole altered areas were 75m and 4$^{\circ}$. On the other hand, 120km$^2$ of urban areas were changed into other areas (i.e., agricultural areas and green space), and fortunately, certain amount of naturalness had been recovered. But still those agricultural areas and fallow areas, which were previously urban areas, had high potential of re-development for urbanization due to their local conditions. According to the structural analysis of forest landscape using the landscape indices, the forest fragmentation of watersheds along the main stream of the Nakdong River was more severe than my other watersheds. Furthermore, the Nakdong-sangju and Nakdong-miryang watersheds had unstable forest structures as well as least amount of forest quantity. Thus, these areas need significant amount of forest through a new forest management policy considering local environmental conditions.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.1300-1304
• /
• 2008

The fact that soil loss causing to increase muddy water and devastate an ecosystem has been appearing upon a hot social and environmental issues which should be solved. Soil losses are occurring in most agricultural areas with rainfall-induced runoff. It makes hydraulic structure unstable, causing environmental and economical problems because muddy water destroys ecosystem and causes intake water deterioration. One of three severe muddy water source areas in Soyanggang-dam watershed is Jawoon-ri region, located in Hongcheon county. In this area, many cash-crops are planted at illegally cultivated agricultural fields, which were virgin forest areas. The purpose of this study is to estimate soil loss with current land uses (including illegal cash-crop cultivation) and soil loss reduction with land use conversion from illegal cultivation back to forest. In this study, the Sediment Assessment Tool for Effective Erosion Control (SATEEC) ArcView GIS system was utilized to assess soil erosion. If the illegally cultivated agricultural areas are converted back to forest, it is expected to 17.42% reduction in soil loss. At the Jawoon-ri region, illegally cultivated agricultural areas located at over 30% and 15% slopes take 47.48 ha (30.83%) and 103.64 ha (67.29%) of illegally cultivated agricultural fields respectively. If all illegally cultivated agricultural fields are converted back to forest, it is expected that 17.41% of soil erosion and sediment reduction, 10.86% reduction with forest conversion from 30% sloping illegally agricultural fields, and 16.15% reduction with forest conversion from 15% sloping illegally agricultural fields. Therefore, illegally cultivated agricultural fields located at these sloping areas need to be first converted back to forest to maximize reductions in soil loss reduction and muddy water outflow from the Jawoon-ri regions.

• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2003.11a
• /
• pp.123-126
• /
• 2003

This study was to analyze land use tendency of the apartment complexes in Banpo in Seoul, Bundang, and Keureng in Chungju. The results of this study were followings. The patterns of Land use in the apartment complexes have been diversified and open spaces have been increased since 1990. In addition, land use relating facilities also has been increased. In the apartment complexes in large cities, park spaces also have been increased. The results of this study indicated that the tendency of apartment complexes is not just residential areas but places for quality of life.

• Journal of Korean Society of Forest Science
• /
• v.108 no.1
• /
• pp.50-58
• /
• 2019

This study was carried out to analysis the landform characteristics of land creep areas in south Korea. Aspect ratio in 17 areas (approximately 46.0 %) among total land creep areas (37 areas) was ranged from 0.37 to 0.92. Also, aspect ratio in 36 areas (approximately 97.0 %) was less than 2. Longitudinal section form ratio of 15 areas (approximately 41.0 %) was less than 1.0, whereas 22 areas (approximately 59.0 %) were more than 1.0. Horseshoe hoof form in land creep areas were mostly appeared to flat land types, whereas convex terrain ground form was prevailed to micro-topography. Mean contour intervals were higher in micro-topography (mean 29.4 m, range 9.5 m ~ 83.2 m) than in except micro-topography (mean 24.3 m, range: 14.4 m ~ 59.4 m) in land creep areas. The contour intervals were slightly wider in micro-topography (mean 5.1 m, range: 4.9 m ~ 23.8 m) than in except micro-topography in land creep areas. The results indicate that contour intervals were significantly different (P < 0.05) between micro-topography and except micro-topography in land creep areas.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.4
• /
• pp.113-126
• /
• 2021

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season's RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region's forest cooperation strategies by providing forest spatial information on the North Korea's DMZ.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.574-577
• /
• 2006

In this paper, we developed a forest fire detection algorithm which uses a regression function between NDVI and land surface temperature. Previous detection algorithms use the land surface temperature as a main factor to discriminate fire pixels from non-fire pixels. These algorithms assume that the surface temperatures of non-fire pixels are intrinsically analogous and obey Gaussian normal distribution, regardless of land surface types and conditions. And the temperature thresholds for detecting fire pixels are derived from the statistical distribution of non-fire pixels’ temperature using heuristic methods. This assumption makes the temperature distribution of non-fire pixels very diverse and sometimes slightly overlapped with that of fire pixel. So, sometimes there occur omission errors in the cases of small fires. To ease such problem somewhat, we separated non-fire pixels into each land cover type by clustering algorithm and calculated the residuals between the temperature of a pixel under examination whether fire pixel or not and estimated temperature of the pixel using the linear regression between surface temperature and NDVI. As a result, this algorithm could modify the temperature threshold considering land types and conditions and showed improved detection accuracy.

• Journal of Korean Society of Forest Science
• /
• v.112 no.3
• /
• pp.267-279
• /
• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.