• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.133-141
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• 2009

This study was conducted to support for determining an efficient sampling design for forest resources assessments in South Korea with respect to statistical efficiency. For this objective, different systematic sampling designs were simulated and compared based on an artificial forest population that had been built from field sample data and satellite data in Yang-Pyeong County, Korea. Using the k-NN technique, two thematic maps (growing stock and forest cover type per pixel unit) across the test area were generated; field data (n=191) and Landsat ETM+ were used as source data. Four sampling designs (systematic sampling, systematic sampling for post-stratification, systematic cluster sampling, and stratified systematic sampling) were employed as optimum sampling design candidates. In order to compute error variance, the Monte Carlo simulation was used (k=1,000). Then, sampling error and relative efficiency were compared. When the objective of an inventory was to obtain estimations for the entire population, systematic cluster sampling was superior to the other sampling designs. If its objective is to obtain estimations for each sub-population, post-stratification gave a better estimation. In order to successfully perform this procedure, it requires clear definitions of strata of interest per field observation unit for efficient stratification.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.457-466
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• 2011

The objectives of this study are to produce level 3 type LULC map and analysis of phenological features of North Korea, ISODATA clustering of the 88scenes of MVC of MODIS NDVI in 2008 and 8scenes in 2009 was carried out. Analysis of phenological phases based mapping method was conducted, In level 2 type map, the confusion matrix was summarized and Kappa coefficient was calculated. Total of 27 typical habitat types that represent the dominant species or vegetation density that cover land surface of North Korea in 2008 were made. The total of 27 classes includes the 17 forest biotopes, 7 different croplands, 2 built up types and one water body. Dormancy phase of winter (${\sigma}^2$ = 0.348) and green up phase in spring (${\sigma}^2$ = 0.347) displays phenological dynamics when much vegetation growth changes take place. Overall accuracy is (851/955) 85.85% and Kappa coefficient is 0.84. Phenological phase based mapping method was possible to minimize classification error when analyzing the inaccessible land of North Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.65-81
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• 2019

This study analyzed the relationship of land cover type, urban temperature in Gimhae city, Gyeongsangnam-do, South Korea. Date were used for land cover map, MODIS LST, and detailed temperature data on the Korean Peninsula based on RCP between 2000 and 2010. The correlation between urban area and surface temperature was 0.417, 0.512 for agricultural area and -0.607 for forest area. The correlation between surface temperature and air temperature was 0.301. The relationship with air temperature was analyzed as 0.275 for urban area, agriculture area 0.226, forest area 0.350. Urban and agricultural areas showed increased surface and air temperature as the area increased, while forest areas showed opposite improvements. In structural equation models, urban and agricultural areas had direct effects on the rise of surface temperature, whle forest areas had direct effects on the reduction of air temperature. In the future, it is necessary to use measured temperature data near the surface to understand the relationship between surface temperature and temperature according to the changes in spatial characteristics, which will prepare measures for urban heat island mitigation at the level of urban and environmental planning.

• Journal of Environmental Science International
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• v.30 no.10
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• pp.779-787
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• 2021

This study analyzes structural landscape changes over a time-series for a small and medium-sized city, Gangneung-Si, based on area and distribution patterns, and according to the type of land cover. Among the types of land cover, the area ratio of urbanized areas increased by 2.02% in the late 2010s as compared to the late 1980s, while there was a decrease of 2.69% in farmland and 0.69% in grassland areas. On analyzing the changes in land cover use by applying the Fragstats program, it was confirmed that landscape changes in urban and management areas were relatively severe according to the Landscape Shape Index, Largest Patch Index, and Aggregation Index. A pattern of concentrated expansion was also found around certain areas. In particular, from the analysis, it was established that the proportion of urbanized area had considerably increased and that the extent of farmland damage to management areas, including planned management areas, was large. Additionally, the Total Core Area generally indicated a reduction in the core areas of farmland and forest within urban and management areas. A medium-sized city showed significant changes besides large cities in terms of landscape structure. The developmental pressure on management areas, in particular, was quite high.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.97-104
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• 2018

This study investigated the effect of forest type changes in Daegu, the hottest city in Korea, on the land surface temperature (LST). The LST change by forest type was analyzed by 2scene of Landsat TM image from 1990 to 2007. The land cover types were classified into 4 types; forest areas, urban areas, cultivated areas and other areas, and water areas. The forest areas were further classified into the coniferous tree areas and the broadleaf tree areas. The result of the statistical analysis of the LST change according to the forest type showed that the LST increased when the forest was changed to the urban area. The LST increased by about $0.6^{\circ}C$ when a broadleaf tree area was changed to an urban area and about $0.2^{\circ}C$ when a coniferous tree area was changed to an urban area. This was the temperature change as the result of the simple type change for 17 years. The temperature change was larger when considering both cases of the forest type being retained and changed. The LST increased by $2.3^{\circ}C$ more when the broadleaf tree areas were changed to the urban areas than when broadleaf trees were maintained. The LST increased by $1.9^{\circ}C$ more when the coniferous tree areas were changed to the urban areas than when the coniferous tree areas were maintained. The LST increased by $0.4^{\circ}C$ more when the broadleaf tree areas were destroyed than when the coniferous tree areas were destroyed. The results confirmed that the protection of broadleaf trees in urban forests was more effective for mitigating climate change.

• The Korean Journal of Ecology
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• v.24 no.6
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• pp.341-348
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• 2001

Population dynamics of the oldest relic stand of Pinus densiflora for. erecta which remains as a status of patch in Sokwang-Ri area, Uljin-Gun, was studied to provide the basic data for conservation of the oldest pine stand in Korea. The upper slope site and ridge site including total 12 plots mainly represented Pinus densiflora for. erecta and Quercus mongolica. These two tree species showed reverse J-shaped distribution. From this information, it was concluded that intensive interspecific competition between two species could be occurring. Age distribution of P. densiflora for. erecta on the sites above middle slope area was indicated bi-modal type or tri-modal type which was known as an age structure of climax forest. Therefore, it was estimated that Pinus densiflora for. erecta population could be continuously maintained in the each patch above middle slope area. In the valley sites, hardwood species such as Q. mongolica, Q. variabilis, Styrax obassia and Acer pseudosieboldianum occupied most part of the under crown-cover area and their seedlings and saplings were developing into the closed upper layer crown because the height of upper layer crown reached about 35 meters and such a high crown height was more suitable for light utilization by plants of under layer. The growth patterns were mainly fluctuated for the entire life time of the oldest tree caused by frequent disturbance. And the initial growth curves of the mature trees and suppressed juvenile trees showed different tendencies along the sites.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.63-63
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• 2003

The aim of this study is to apply and verify of Bayesian probability model, the likelihood ratio and statistical model, at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the likelihood ratio coefficient were overlaid for landslide susceptibility mapping, Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.