• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.6
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• pp.826-831
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• 2016

he land use, land-use change, and forestry (LULUCF) is one of the greenhouse gas inventory sectors that cover emission and removals of greenhouse gases resulting from land use such as agricultural activities and land use change. Particularly, LULUCF-Cropland sector consists of carbon stock changes in soil, $N_2O$ emissions from disturbance associated with land use conversion to cropland, and $CO_2$ emission from agricultural lime application. In this paper, we conducted the study to calculate the greenhouse gases emission of LULUCF-Cropland sector in South Korea from 1990 to 2014. The emission by carbon stock changes, conversion to cropland and lime application in 2014 was 4424, 32, and 125 Gg $CO_2$-eq, respectively. Total emission from the LULUCF-Cropland sector in 2014 was 4,582 Gg $CO_2$-eq, increased by 508% since 1990 and decreased by 0.7% compared to the previous year. Total emission from this sector showed that the largest sink was the soil carbon and its increase trend in total emission in recent years was largely due to loss of cropland area.

• 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.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.315-325
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• 2023

This study analyzed the disturbance process of river wetlands based on modern and contemporary maps and aerial photographs, and analyzed land cover and NDVI changes in the hydro-ecological impact zone around the Wangjin District. A stable sandbar was formed near Wangjinnaru and was naturally connected to the agricultural land within inland, but after the sandbar and river wetland were destroyed due to heavy floods, embankment construction, land readjustment, and comprehensive river management, artificial replaced wetlands and ecological parks were created, and sandbars in the form of river island were restored again. The change in land cover in the hydro-ecological impact zone showed that rice paddies and fields in agricultural areas decreased from 36.3% in 2013 to 22.9% in 2022, with the largest change in area to 814,476m². It was confirmed that the land cover was undergoing vegetation over time. Since the vegetation condition is good, a healthy food chain is formed in the waterfront ecosystem, which can be expected to be biodiversity-positive. Summarizing seasonal changes in the vegetation index, the overall change in the vegetation index was the largest in spring (March), followed by summer (June), and the change in autumn (September) was the smallest except for water. By land use, the overall vegetation index (NDVI) increased, including 39.1% improvement in alternative wetlands, 38.2% improvement in load, 44.3% improvement in ecological parks, 35.6% improvement in agricultural areas, and -8.1% decrease in water.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• Journal of the Korean GEO-environmental Society
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• v.13 no.7
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• pp.39-47
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• 2012

Six land use data for a total of twenty five years were reviewed from 1975 to 2000 by dividing the period by 5-year unit; the land use variation was schematized; the watershed hydrological parameters were extracted by the representative rainfall years(maximum, average, driest year) by analyzing the recent thirty years'(from 1980 to 2010) climate data of the study region with SWAT model to investigate the effect of the precipitation change on the characteristics of groundwater recharge. In addition Markov Chain model was used to estimate the future land use; the predicted land use was applied to study the effect of the land use variation on the characteristics of groundwater recharge. For the research of this, long-term characteristics of groundwater recharge were estimated for the study region; the obtained results can be described as follows. The study region was divided into typical three area using SWAT model; yearly land use conditions were applied to the meteorological data of 1975 to 2010 and analyzed, producing the average rate of groundwater recharge of 30% for the applied period. This number is way lower than that of the earlier studies on the groundwater recharge for Jeju Island, which is 40-50%. Thirty percent (30%) is low considering the geological characteristics of Jeju, water-permeable vesicular strata, the reason of which must be the type of development is non-permeable paving.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.402-411
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• 2014

This study suggests the method of green infrastructure (GI) application which helps proper distribution of structural GI and non-structural GI by using land characteristics assessment and performs the case study. Land assessment standard consists of land cover type, fragmentation degree, proximity degree to residential districts, and cluster degree of fragmented areas which represents the quality of green network. The result of assessment proposes the land suitability to preserve or develop and it can be utilized to choose the type of the green infrastructures.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.87-95
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• 2012

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about $21{\sim}25^{\circ}C$ and maximum LST is observed over industrial area of about $28{\sim}32^{\circ}C$. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.53-62
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• 2013

Land-use/cover changes not only amplify or alleviate influence of climate changes but also they are representative factors to affect environmental change along with climate changes. Thus, the use of land-use/cover changes scenario, consistent climate change scenario is very important to evaluate reliable influences by climate change. The purpose for this study is to predict and analyze the future urban growth considering social and economic scenario from RCP scenario suggested by the 5th evaluation report of IPCC. This study sets land-use/cover changes scenario based on storyline from RCP 4.5 and 8.5 scenario. Urban growth rate for each scenario is calculated by urban area per person and GDP for the last 25 years and regression formula based on double logarithmic model. In addition, the urban demand is predicted by the future population and GDP suggested by the government. This predicted demand is spatially distributed by the urban growth probability map made by logistic regression. As a result, the accuracy of urban growth probability map is appeared to be 89.3~90.3% high and the prediction accuracy for RCP 4.5 showed higher value than that of RCP 8.5. Urban areas from 2020 to 2050 showed consistent growth while the rate of increasing urban areas for RCP 8.5 scenario showed higher value than that of RCP 4.5 scenario. Increase of urban areas is predicted by the fact that famlands are damaged. Especially RCP 8.5 scenario indicated more increase not only farmland but also forest than RCP 4.5 scenario. In addition, the decrease of farmland and forest showed higher level from metropolitan cities than province cities. The results of this study is believed to be used for basic data to clarify complex two-way effects quantitatively for future climate change, land-use/cover changes.

• Korean Journal of Environment and Ecology
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• v.19 no.4
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• pp.375-384
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• 2005

This study was conducted selecting 44 places with a block unit subject to urban area in Gangnam-gu, to analyze a temperature change according to land use and green structure. In this study, it was used the broad-wide urban temperature, supported by Landset TM and ETM+ satellite image 6scene(1999${\~}$2002). The result of the research, the land use pattern has slightly influence on a temperature change of urban area. The result from correlation analysis between temperature and the factors affected by land cover type, such as building-to-land ratio(A correlation coefficient is 0.368${\~}$0.709) have positive correlation and green area ratio(a correlation coefficient is -0.551${\~}$-0.860) have negative correlation. The result from correlation analysis between temperature and green capacity of the land, crown projection area ratio, each factor have negative correlation with temperature, as showing that a correlation coefficient of green capacity of the land is -0.577(June 2006)${\~}$-0.882(June 1999) and crown projection area ratio's is -0.549(June 2001)${\~}$-0.817(June 1999). The result of the regression analysis for establishing urban area temperature change prediction model showed that green capacity of the land of the explanation variable was accepted.