• Journal of Korean Society of Forest Science
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• v.104 no.2
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• pp.239-247
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• 2015

Since 2006, new national forest inventory in Korea has been restructured to assess current status and and monitor the changes in forest resources based on permanent sample plots. The objective of estimate this study is to assess changes in forest resources such as land use/cover categories and forest stand variables. For this study, permanent plot data were collected between 2006-2008 and 2011-2013 in Chungcheongbuk-do, respectively. In order to produce land use/cover change matrix which plays an important role as an activity data for estimating GreenHouse Gas inventory, permanent plots were classified into six land use/cover categories. Additionally, matrixes for assessing the changes in age class and dominant tree species can provide more detailed information. For forest stand variables(tree density, basal area, growing stock, mean diameter at breath height, and mean height), their growth and change were assessed. The periodic annual growth ratios for tree density and basal area were slightly declined whereas that of growing stock was estimated to be about 3.7%. The uncertainty of changes in forest stand variables is less than 5%, except for tree density (RSE: 58%). The variation of tree density is relatively high compared to the other variables.

• 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.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.495-504
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• 2005

The objective of this study is to estimate the impacts of land cover change on the runoff behavior using Hydrologic Simulation Program-Fortran (HSPF) model and Landsat images. Land cover maps were prepared using three every ten years from 1980 to 2000 of the upper watershed ($258\;km^2$) of Gyeongan stream. Hydrologic parameters of HSPF were calibrated using observed data (1999 - 2000) and validated using observed data (2001, 2003) at Gyeongan gauge station. The simulation results showed that runoff volume and peak rate increased as $15.0\;km^2$ forest areas decreased and $19.3\;km^2$ urban areas increased for 20 years land use changes. The runoff volume showed a higher rate of increase in wet year (2003, 1709.4 mm) than in dry year (2001, 871.2 mm). The peak runoff increased $13.3\;\%$ in normal year (2000, 1257.3 mm) because the year has the highest rain intensity (241.3 mm/hr) among the test years. The runoff volume of a dry season and a wet season (May - September) in normal year 2000 increased $4.4\;\%$ and decreased $8.1\;\%$, respectively.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.117-126
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• 2018

This study aims to evaluate the usability of polarimetric SAR measurements for discriminating water-covered area from other land cover types and to propose polarimetric parameters showing the better response to the flood. Flood-related changes in the polarimetric parameters were studied using the L-band PALSAR-2 quad-pol mode data acquired before and after the severe flood events occurred in Joso city, Japan. The experimental results showed that, among various polarimetric parameters, the HH-polarization intensity, the Shannon entropy, and the surfaces scattering component of model-based decomposition were found to be useful to discriminate water-covered areas from other land cover types. Particularly, an unsupervised change detection with the Shannon entropy provides the best result for an automated mapping of flood extents.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.266-268
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• 2003

This is based on the AGENT-LUC model framework. Luangprabang Province has the largest percentage of shifting cultivation area in Laos PDR. The model simulates the spatial and temporal patterns of the shifting cultivation in the study area, using a GIS database while the total area of shifting cultivation is controlled by supply and demand balance of food. The model simulation period is from 1990 to 1999, at a spatial resolution of 500m. The results are evaluated using statistical data and remote sensing images. Through the validation, it is concluded that the trends simulated agrees to that of statistical data and the spatial and temporal patterns are also replicated satisfactorily.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.26-41
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• 2012

It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 1999.03a
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• pp.24-25
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• 1999

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.133-140
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• 2007

In this study we did the monitor the change of a urban land coverage to forecast and to deal with various city problems according to urban development. The amount of change of a land coverage used the landsat satellite image and was calculated by analyzing the situation and the distribution aspect of land cover of the road circumstance by time series. We interpreted two images which are taken picture different time and calculated the amount of the area change through integration of the spatial analysis technique of remote sensing and GIS for this study. We could create the development model of the urban area by continuous analysis of satellite and geographic data.