• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.107-109
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• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.566-569
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• 2004

This study is to trace the change of stream shape using the past series of aerial photographs, and to compare the land use changes of riparian area along the stream. For the Gyeongan national stream, aerial photographs of 1966, 1981 and 2000 were selected and ortho photographs were made with interior orientation and exterior orientation, respectively. As apparent changes of the stream, the consolidated reaches of stream with levee construction were straightened and their stream widths were widened. Especially the stream width of inlet part of Paldang lake was widened almost twice because of the rise of water level by dam construction in 1974. The land use maps (1966, 1981,2000) of riparian areas were also made, respectively and classified into 6 categories (water, forest, agricultural land, urban area, road, sandbar) by digitizing. The area of forest and agricultural land decreased and urban area increased as the stream maintenance was performed.

• Journal of Korean Society of Rural Planning
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• v.6 no.2 s.12
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• pp.50-58
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• 2000

The purposes of the study were to detect and evaluate the historical land use and land cover changes on the Balan watersheds from three thematic mapper (TM) data, which were taken in 1985, 1993, and 1996. The supervised and unsupervised classification methods were adopted to classify five land cover categories: Paddy, upland, forest, residential, and water. The results indicated residential areas increased significantly during the past eleven years, Forest and paddy were converted to the urban areas. Future land cover patterns were forecasted using a Markov chain method, and the simulated land coiler change ratios presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.spc4_2
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• pp.421-430
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• 2014

Aerial imagery, Satellite imaging and Hyperspectral imaging(HSI) are widely using at mapping those of agriculture, woodland, waters shoreline, and land cover, but are rarely applied at the Cadastre. There are many study cases on the overlay of aerial imagery and satellite imaging with Cadastral Map and the upgrade and registration of Cadastre' Land Category, however, reported as successful. Therefore, this study has been aimed to show the use of the Hyperspectral Imaging technology for Cadastre, especially for the land category. Also, the HSI sensor could function as a geospatial acquisition tool for error checks of the existed land categories, and as a helpful tool for acquiring the attributes and spatial data, such as the agriculture, soil, and vegetation, etc. This result indicates that HSI sensor can implement the Multipurpse Cadastre(MPC) by fusing with the cadastral information.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.99-110
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• 2023

Land surface temperature (LST) is a critical environmental indicator affected by land cover (LC) changes. Currently, the most convenient and fastest way to retrieve LST is to use remote sensing images due to their continuous monitoring of the Earth's surface. The work intended to investigate land cover change and temperature response inAn-Najaf province. Landsat multispectral imageries acquired inAugust 1989, 2004, and 2021 were employed to estimate land cover change and LST responses. The findings exhibited an increase in water bodies, built-up areas, plantations, and croplands by 7.78%, 7.27%, 6.98%, 3.24%, and 7.78%, respectively, while bare soil decreased by 25.27% for the period (1989-2021). This indicates a transition from barren lands to different land cover types. The contribution index (CI) was employed to depict how changes in land cover categories altered mean region surface temperatures. The highest LSTs recorded were in bare lands (42.2℃, 44.25℃, and 46.9℃), followed by built-up zones (41.6℃, 43.96℃, and 44.89℃), cropland (30.9℃, 32.96℃, and 34.76℃), plantations (35.4℃, 36.97℃, and 38.92℃), and water bodies (27.3℃, 29.35℃, and 29.68℃) respectively, in 1989, 2004, and 2021. Consequently, these changes resulted in significant variances in LST between different LC types.

• Journal of the Korea Furniture Society
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• v.18 no.2
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• pp.129-137
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• 2007

Total forest land in Bangladesh is about 2.5 million hectare which is 17% of total land area. Bangladeshi forest is mainly classified into three categories- 1) Hill forest 2) Sal forest and 3) Mangroves. This forest land area is decreasing day by day. But in past decayed due to some policies, the total forest land area is increasing slowly. By this planning both government and the local people in the community are being benefited. This paper mainly discussed about the past, present and future trend of forest condition, forest land uses, sustainable forest planning and forest management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.581-590
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• 2014

With rapid land development, land category should be updated on a regular basis. However, manual field surveys have certain limitations. In this study, attempts were made to extract a feature vector considering spectral signature by parcel, PIMP (Percent Imperviousness), texture, and VIs (Vegetation Indices) based on RapidEye satellite image and cadastral map. A total of nine land categories in which feature vectors were significantly extracted from the images were selected and classified using SVM (Support Vector Machine). According to accuracy assessment, by comparing the cadastral map and classification result, the overall accuracy was 0.74. In the paddy-field category, in particular, PO acc. (producer's accuracy) and US acc. (user's accuracy) were highest at 0.85 and 0.86, respectively.

• Journal of Korean Society of Rural Planning
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• v.13 no.2
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• pp.85-92
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• 2007

This study aims to show how the urbanization of Korea has progressed for the last three decades, what its characteristics are, and how rural land use has changed by the national and district(cities and counties) level. The land use changes accompanying to the urbanization is analyzed through 3 indicators such as urbanization rate, the rate of cultivated and forest land and the rate of urbanized area. The statistical data are 30 years from 1976 to 2005 for time series analysis by the national level, and are for the two years of 1995 and 2005 by the district level. The relationship between urbanization and land use changes in the national level is analyzed using statistical analysis(Correlation Analysis). In order to analyze the dynamic and spatial urbanization and land use changes effectively in the district level, Z-score, Paired T-test, Correlation Analysis, Analysis of Variance and Chi-squire Test are used. The results show negative correlation between urbanization rate and the rate of cultivated and forest land, and positive correlation between urbanization rate and the rate of urbanized area respectively. In the aspect of the change of urbanization rate, four categories are examined. In addition, four types are characterized on the basis of the rate of cultivated and forest land and the rate of urbanized area between 1995 from 2005.

• Journal of Korean Society of Rural Planning
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• v.24 no.3
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• pp.43-54
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• 2018

The residential population of Jeju Island has increased more than 10% for last 10 years. Especially, the tourist population is more than twice comparing to 2005. The population growth of Jeju has brought about large-scale urban development and increased land demands for tourism services. The goal of this study is to analyze the human, social, and environmental status of Jeju Island and to evaluate the environmental capacity of land use using ecological footprint (EF) model. This study shows the changes in ecological deficits of Jeju Island through estimating ecological productive land (EPL) considering EF from 2005 to 2015. The categories of total EF consists of food land, built-up land, forestry, and energy consumption. In order to reflect the characteristics of resort island, we consider not only residential population but also tourist population who can increase land demands. The outputs of this study also provide the potential excess demands of EPL and suggest needs of sustainable management plans for the limited land of Jeju Island.

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