• Journal of Wetlands Research
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• v.24 no.2
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• pp.93-101
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• 2022

This study was conducted to analyze the distribution characteristics of abandoned paddy wetlands according to topography and land cover. In Seosan-si, Dangjin-si, Boryeong-si, and Taean-gun, Chungcheongnam-do, abandoned rice wetlands were found through GIS and field surveys, and the distribution status according to slope, elevation and land cover type was analyzed. As a result of the study, a total of 106 abandoned paddy wetlands were identified, and the average elevation of each abandoned paddy wetlands was 38.85m (S.D.32.76), the average slope was 6.27˚ (S.D.5.39), and the total area was 24,200km². 90 sites (84.9%) of abandoned paddy wetlands were distributed on flat land with less than 5˚ slope, 63 sites (12,121.07km²), and 27 sites(9,524.15km²) at 5-10˚ (9,524.15km²) on flat land with less than 10˚. The area is 21,645.22km²(89.5%) of the total area of abandoned paddy wetlands. 48 sites(12,326km²) in the lowlands with an altitude of less than 25 m, 29 sites(4,909.4km²) below 50m. It accounts for 71.2% of the total area of abandoned paddy wetlands. Among environmental factors of abandoned paddy wetlands, there was no statistically significant correlation between slope and altitude. According to the land cover classification, it was widely distributed in artificial grasslands (38), paddy fields (33), and fields (22).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.493-504
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• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

• Journal of Environmental Impact Assessment
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• v.19 no.2
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• pp.117-125
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• 2010

Korea's researchers have recently studied the prediction of forest change, but they have not considered landuse/cover change compared to distribution of forest vegetation. The purpose of our study is to predict forest vegetation based on landuse/cover change on the Korean Peninsula in the 2090's. The methods of this study were Multi-layer perceptrom neural network for Landuse/cover (water, urban, barren, wetland, grass, forest, agriculture) change and Multinomial Logit Model for distribution prediction for forest vegetation (Pinus densiflora, Quercus Spp., Alpine Plants, Evergreen Broad-Leaved Plants). The classification accuracy of landuse/cover change on the Korean Peninsula was 71.3%. Urban areas expanded with large cities as the central, but forest and agriculture area contracted by 6%. The distribution model of forest vegetation has 63.6% prediction accuracy. Pinus densiflora and evergreen broad-leaved plants increased but Quercus Spp. and alpine plants decreased from the model. Finally, the results of forest vegetation based on landuse/cover change increased Pinus densiflora to 38.9% and evergreen broad-leaved plants to 70% when it is compared to the current climate. But Quercus Spp. decreased 10.2% and alpine plants disappeared almost completely for most of the Korean Peninsula. These results were difficult to make a distinction between the increase of Pinus densiflora and the decrease of Quercus Spp. because of they both inhabit a similar environment on the Korean Peninsula.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.397-404
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• 2012

Jeju where concentrates on agriculture and tourism, conversion of outdoor culture into cultivation under structure happens actively for the purpose of increasing profit so continuous examination on house cultivation area is very important for this region. This paper is to suggest the effective image classification method using high resolution satellite image to detect the greenhouse. We carried out classification of greenhouse using the supervised classification and rule-based classification method about Formosat-2 images. Connecting result of two classification try to find accuracy improvement for greenhouse detection. Results about each classification method were calculated the accuracy by comparing with the result of visual detection. As a result, mahalanobis distance among the supervised methods was resulted in the highest detection. Also, it could be checked that detection accuracy was improved by tying with result of supervised method and result of rule-based classification. Therefore, it was expected that effective detection of greenhouse would be feasible if henceforward further study is performed in the process of connecting supervised classification and rule-based classification.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.471-479
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• 2011

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.17-24
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• 2011

Global warming and climatic changes due to human activities impact on marine and terrestrial ecosystems, which feedbacks to climate system. These negative feedbacks amplify or accelerate again global climate change. In particular, it is important to analyze vegetation change. This study attempts to analyze quantitatively vegetation change in Korea peninsula by using harmonic analysis. Harmonic-Analysis based on Fourier Transform is the method to effectively demonstrate for time series data. Especially, Harmonic-Analysis is very suitable method to analyze vegetation change because the vegetation repeats the cycle growth and extinction every year. The result of harmonic-analysis shows vegetation change as time passes. In this study, SPOTNEGETATION S10 MVC NDVI data was used during last 10 years (1999-2008) in Korea Peninsula. Also, land type classification used MODIS Land Cover Map data. The study estimated that phase values moved up approximately 0.5 day per year in cropland and 0.8 day per year in forest.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.39-44
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• 2009

To analysis the LST distribution of Jeju island, remote sensing techniques using Landsat TM band 6 data were used. In this study, we made the LST distribution map based on the NASA. The study areas are the Jeju and Seogwipo cities of the Jeju Island. And we analyzed the correlation between the LST and NDVI which was calculated from the Landsat TM band 3 and ban 4. From the result, we found that the coefficients of the correlation were -0.77 and -0.74 on the Jeju and the Seogwipo cities, respectively. Finally, from the correlation between the land cover and LST, we also found that an inverse relationship between the LST and NDVI was exist.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.269-282
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• 2016

Watershed area can be submerged due to constructions and management of dams, and these change can impact not only on ecosystem and environment of river basin area but also on local climate. This study is conducted to construct and classify climate zones of Andong Dam watershed where the area is submerged due to the construction of the dam. By applying Principal Components Analysis (PCA) and Getis-Ord $Gi^*$ statistics, three climate zones were classified for the result. Each zone was then analyzed and validated with climatic and geological features including topography, land cover, and forest type map. As a result of the analysis, there was a difference in temperature, elevation, precipitation and tree species distribution among the zones. Also, an analysis of land cover map showed that there were more agricultural land near Andong Reservoir. This study on the climatic classification is considered to be useful as the basis for decision-making or policy enforcement regarding ecosystem, environmental management or climate change response.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.3
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• pp.77-85
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• 1990

This report is a study concerning the classification of the surface cover data applying the data of LANDSAT TM (Thematic Mapper). The purpose of this study was to reduce the cost of use for LANDSAT data and increase the accuracy of land cover classification. Especially, a using mehtod adopted in this paper was a unique optical method using OHP(Over Head Projector). It was found that a unique optical method can have significant effects upon the responses according to the present results in this study.

• 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.