• Journal of Environmental Science International
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• v.19 no.1
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• pp.115-124
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• 2010

Urban watershed can be found in the visible changes in technology, the most realistic satellite images is to use the data. Satellite image data on the indicators for progress on the nature of the change of land use is consistent and repetitive information, regular observation makes possible the detailed analysis of space-time. These remote sensing techniques and the type of course and, by using the time series history, the past, the dynamic model and the randomized prediction methodology for the conversion process if the city and river basin cooperation of the space changes effectively will be able to extrapolate. For each of the main changes in river flow, depending on the area of urbanization as determined according to reproduce the duration of the relationship between the urbanization of the area and runoff can be represented as a linear polynomial expression was, if a linear expression in the two fast slew rate of 0.858 to 0.861 showed up, and fast slew rate of 0.934 to 0.974 for the polynomial are reported. Change of land use changes in the watershed of the flow is one of the most affecting elements. Therefore, changes in land use of the correct classification of rivers is a more accurate calculation of the amount of the floodgate. In particular, using the Landsat images through the image of the land use category, land use past data and calculated using the Markov Chain model and predict the future land use plan in the water control project will be used for large likely.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.2
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• pp.67-83
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• 2002

The coupled model (SMART) of dynamic meteorology model and particle dispersion model was developed. The numerical experiment on the relationship between change of land use and diffusion behavior in complex terrain was carried out using this model. It tried to investigate the change of particle diffusion behavior and local weather under the condition in which land-land breeze and sea breeze and mountain breeze intermingled. The numerical experiment results are as follows; 1) The more complicated local circulation field of the interaction of sea breeze, mountain breeze and Land -land breeze is formed. Then, the region circulation in which the urbanization is specific by location of the region is strengthened and is weakened. 2) Though in the region with dominant sea breeze, Land-land breeze does not appear directly, the progress of the sea wind to the inland is affected. 3) In the prediction of the air diffusion, emission high quality and accurate information of the emission site are important. That is to say, the dispersion predicting result which emission high quality and small error of the site perfectly vary for Land - land breeze in the effect may be brought about.

• Journal of the Korean housing association
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• v.15 no.4
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• pp.45-54
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• 2004

This study systematized synthetically to use internet GIS and real estate appraisal method in computing system for the real estate decision. First, indicated the method of using GIS and databases to appraise the real estate by using the cost approach. Second, used the artificial neural network to predict the change of land prices and the artificial neural network convinced us that it indicates easily the result of land prices without complicated processes. Third, examined land prices using the artificial neural network but there is limits for the land price prediction because of difficult data gathering. also, this study may heighten information levels of the real estate field according to 21th century information level if use actively a internet, information users who should pay much moneys in existent real estate decisions may can approach easily.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.105-114
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• 2007

This study is to predict the spatial expansion of urban areas by applying CA(Cellular Automata)-Markov technique considering MCE(multi-criteria evaluation) and MOLA(multi-objective land allocation) of factor analysis. For the 10 administration districts$(3677.3km^2)$ including the whole Anseong-cheon watershed, the past six temporal land use data(1973, 1981, 1985, 1990, 1994, 2000) from Landsat satellite images were prepared. During this period, the urban area increased $233.71km^2$. Using the 36 indices composed of topological characteristics, population and land use change, the final factor map of MOLA was produced through 5 maps of MCE. Using 1990 and 1994 land use data, the 2000 predicted urban area of CA-Markov with factor map showed 0.06% improvement of absolute error comparing with that of CA-Markov without factor map. By the CA-Markov technique considering factor map, the 2030 and 2060 urban area increased $58.94km^2(0.78%)\;and\;60.14km^2(0.81%)$ respectively comparing with 2000 urban area$(313.19km^2)$. The 2030 and 2060 paddy area decreased $93.28km^2(2.54%)\;and\;93.65km^2(2.55%)$ respectively comparing with 2000 paddy area$(1383.23km^2)$.

• Korean Journal of Environment and Ecology
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• v.25 no.4
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• pp.590-600
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• 2011

The research was carried out for prediction of the potential habitats of warm-temperate evergreen broad-leaved trees under the current climate(1961~1990) and three climate change scenario(2081~2100) (CCCMA-A2, CSIRO-A2 and HADCM3-A2) using classification tree(CT) model. Presence/absence records of warm-temperate evergreen broad-leaved trees were extracted from actual distribution data as response variables, and four climatic variables (warmth index, WI; minimum temperature of the coldest month, TMC; summer precipitation, PRS; and winter precipitation, PRW) were used as predictor variables. Potential habitats(PH) was predicted 28,230$km^2$ under the current climate and 77,140~89,285$km^2$ under the three climate change scenarios. The PH masked by land use(PHLU) was predicted 8,274$km^2$ and the proportion of PHLU within PH was 29.3% under the current climate. The PH masked by land use(PHLU) was predicted 35,177~45,170$km^2$ and increased 26.9~36.9% under the three climate change scenarios. The expansion of warm-temperate evergreen broad-leaved trees by climate change progressed habitat fragmentation by restriction of land use. The habitats increase of warm-temperate evergreen broad-leaved trees had been expected competitive with warm-temperate deciduous broadleaf forest and suggested the expand and northward shift of warm-temperate evergreen broad-leaved forest zone.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.833-845
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• 2021

Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

• Journal of Korean Society on Water Environment
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• v.30 no.4
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• pp.418-428
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• 2014

The purpose of this study is to predict the spatio-temporal changes in land uses and to evaluate land-based pollutant loads in the future under Total Water Pollution Load Management System using CLUE-S model. For these ends, sensitive parameters of conversion elasticities in CLUE-S model were calibrated and these calibrated parameters of conversion elasticities, level II land cover map of year 2009, and 7 driving factors of land use changes were used in predicting future land uses in 2002 with two scenarios(Scenario 1: non area restriction, Scenario 2: area restriction). This projected land use map of 2020 was used to estimate land-based pollutant loads. It was expected that urban areas will increase in 2020 from both scenarios 1 and 2. In Scenario 1, urban areas are expected to increase within greenbelt areas and deforest would be expected. Under Scenario 2, these phenomena were not expected. Also the results of estimation of BOD and TP pollutant loads, the BOD difference between scenarios 1 and 2 was 719 kg/day in urban areas and TP difference was 17.60 kg/day in urban areas. As shown in this study, it was found that the CLUE-S model can be useful in future pollutant load estimations because of its capability of projecting future land uses considering various socio-economic driving factors and area-restriction factors, compared with conventionally used land use prediction model.

• 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.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.125-135
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• 2013

Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.