• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

• Spatial Information Research
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• v.18 no.3
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• pp.33-40
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• 2010

Many cities have provided growth management measure for preventing urban sprawl and disordered development by rapid urbanization. Many Korean cities also, have been pressed by development issues as well as the Seoul Metropolitan Area. This study aims to predict urban growth and develop Urban Growth Management Model with Geographic Information System and quantitative method. Especially, this study provides reasonable management method by presenting prediction scenario considered institutional-oriented and demand-oriented. This study also, provides a scientific basis using GIS and quantitative analysis, and present decision making of planning and implementation process through simulation.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.261-272
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• 2012

In this study, climate variability was predicted by the Weather Research and Forecasting (WRF) model under two different scenarios (current trends scenario; SC1 and managed scenario; SC2) for future urban growth over the Seoul metropolitan area (SMA). We used the urban growth model, SLEUTH (Slope, Land-use, Excluded, Urban, Transportation, Hill-Shade) to predict the future urban growth in SMA. As a result, the difference of urban ratio between two scenarios was the maximum up to 2.2% during 50 years (2000~2050). Also, the results of SLEUTH like this were adjusted in the Weather Research and Forecasting (WRF) model to analysis the difference of the future climate for the future urbanization effect. By scenarios of urban growth, we knew that the significant differences of surface temperature with a maximum of about 4 K and PBL height with a maximum of about 200 m appeared locally in newly urbanized area. However, wind speeds are not sensitive for the future urban growth in SMA. These results show that we need to consider the future land-use changes or future urban extension in the study for the prediction of future climate changes.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5_2
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• pp.194-205
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• 2010

To predict urban growth according to changes in landcover, probability factors werecal culated and mapped. Topographic, geographic and social and political factors were used as prediction variables for constructing probability maps of urban growth. Urban growth-related factors included elevation, slope, aspect, distance from road,road ratio, distance from the main city, land cover, environmental rating and legislative rating. Accounting for these factors, probability maps of urban growth were constr uctedusing frequency ratio (FR) and logistic regression (LR) methods and the effectiveness of the results was verified by the relative operating characteristic (ROC). ROC values of the urban growth probability index (UGPI) maps by the FR and LR models were 0.937 and 0.940, respectively. The LR map had a slightly higher ROC value than the FR map, but the numerical difference was slight, with both models showing similar results. The FR model is the simplest tool for probability analysis of urban growth, providing a faster and easier calculation process than other available tools. Additionally, the results can be easily interpreted. In contrast, for the LR model, only a limited amount of input data can be processed by the statistical program and a separate conversion process for input and output data is necessary. In conclusion, although the FR model is the simplest way to analyze the probability of urban growth, the LR model is more appropriate because it allows for quantitative analysis.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.4
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• pp.367-379
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• 2010

Future climate changes over the Seoul metropolitan area (SMA) were predicted by the Weather Research and Forecasting (WRF) model using future land-use data from the urban growth model (SLEUTH) and forecast fields from ECHAM5/MPI-OM1 GCM (IPCC scenario A1B). Simulations from the SLEUTH model with GIS information (slope, urban, hill-shade, etc.) derived from the water management information system (WAMIS) and the intelligent transportation systems-standard nodes link (ITS-SNL) showed that considerable increase by 17.1% in the fraction of urban areas (FUA) was found within the SMA in 2020. To identify the effects of the urban growth on the temperature and wind variations in the future, WRF simulations by considering urban growth were performed for two seasons (summer and winter) in 2020s (2018~2022) and they were compared with those in the present (2003~2007). Comparisons of model results showed that significant changes in surface temperature (2-meter) were found in an area with high urban growth. On average in model domain, positive increases of $0.31^{\circ}C$ and $0.10^{\circ}C$ were predicted during summer and winter, respectively. These were higher than contributions forced by climate changes. The changes in surface temperature, however, were very small expect for some areas. This results suggested that surface temperature in metropolitan areas like the SMA can be significantly increased only by the urban growth during several decades.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.75-88
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• 2016

In this study, we used the CLUE-s model to predict the future land-use change based on the urban growth scenario in South Korea. The land-use maps of six classes (water, urban, rice paddy, upland crop, forest, and grass) for the year 2008 were obtained from the Ministry of Environment (MOE), and the land-use data for 5-year intervals between 1980 and 2010 were obtained from the Water Resources Management Information System (WAMIS), South Korea. For predicting the future land-use change, the MOE environmental conservation value assessment map (ECVAM) was considered for identifying the development-restricted areas, and various driving factors as location characteristics were prepared for the model. The predicted results were verified by comparing them with the land-use statistics of urban areas in each province for the year 2008. The prediction error rates were 9.47% in Gyeonggi, 9.96% in Gangwon, 10.63% in Chungbuk, 7.53% in Chungnam, 9.48% in Jeonbuk, 6.92% in Jeonnam, 2.50% in Gyeongbuk, and 8.09% in Gyeongnam. The sources of error might come from the gaps between the development of political decisions in reality with spatio-temporal variation and the mathematical model for urban growth rate in CLUE-s model for future scenarios. Based on the land-use scenario in 2008, the land-use predictions for the year 2100 showed that the urban area increased by 28.24%, and the rice paddy, upland crop, and forest areas decreased by 8.27, 6.72, and 1.66%, respectively, in South Korea.

• Journal of Environmental Impact Assessment
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• v.2 no.2
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• pp.1-11
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• 1993

Most developing countries are experiencing rapid urbanization and the associated growth of industry and services. Cities are currently absorbing two-thirds of the total population in the developing world. Korea has about 85 percent of urban dwellers. World population will shift from being predominantly rural to predominantly urban around the turn of the century. Although cities play a key role in development process and make more than a proportionate contribution to national economic growth, especially cities are also the main catalysts of economic growth in developing countries, they can also be unhealthy, inefficient, and inequitable places to live. Most developing countries are increasingly unable to provide basic environmental infrastructure and services, whether in the megacities or in secondary urban centers. Of particular concern is the strain on natural resources brought by the increasing number of people, cars, and factories. They are generating ever greater amounts of urban wastes and emissions. They also exceed the capacity of regulatory authorities to control them and of nature to assimilate them. The environmental consequences are translated into direct negative impacts on human health, the quality of life, the productivity of the city, and the surrounding ecosystems. Environmental degradation threatens the long tenn availability and quality of natural resources critical to economic growth. Cities, with their higher and growing per capita energy use for domestic, industrial, and transport purpose also contribute a disproportionate share of the emission leading to global warming and acid rain. An important priority is to develop strategic approaches for managing the urban environment. The design of appropriate and lasting strategic responses requires first an understanding of the underlying causes of urban environmental deterioration, it is necessary that longer tenn objectives should be set for urban area to avoid irreversible ecological damage and to ensure lasting economic development. As a means to the preventive policies against the adverse effect, environmental impact assessment (EIA) serve to identify a project's possible environmental consequences early enough to allow their being taken into consideration in the decision making process for urban planning. This paper describes some considerations of EIA for urban planning-scoping, assessment process, measurement and prediction of impacts, pollution controls and supervision, and system planning for environmental preservation.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.667-668
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• 2010

• 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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.247-248
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• 2015

Korea rapidly arranged urbanization and overpopulation with high growth of economy and all kinds of decrepit facilities are scattered all over the downtown. If there is a strong wind in fire, fire is rapidly increased by various fire spread factors. And Korea cannot build prediction model of urban fire combustion phenomena because there is no studies that physically explains the suitable flame phenomena for its real state. In this study, for development of Korean Urban fire Simulation on Attenuation of Radiant Heat Flux from Water Screen.