• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.516-518
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• 2003

This study discusses an effort to build a model to link normalized difference vegetation indices (NDVI) and socio-economic indicators derived from village survey (1990, 1993, 1996, and 2000) statistical data in Bekasi, West Java, Indonesia. Socio-economics indicators of sub-district level, in this study the number of agricultural households (AH), are aggregated from village level data. NDVI from Landsat-TM resolution data (1989 and 1997) are computed to detect land use/land cover (LULC) dynamics in the sub-district areas. Attention is mainly paid on the examination of agricultural land cover changing in the sub-district level. NDVI measurements might be used to predict AH dynamics as showed by computed linear regression models.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.293-296
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• 2002

The purpose of this study is to evaluate the hydrological impact due to temporal land cover change urbanization of Anseong-cheon watershed $(585.09km^2)$. WMS (Watershed Modeling System) HEC-1 was adopted, and burned DEM with $200{\times}200m$ resolution and soil map reclassified by hydrologic soil groups were prepared. Land cover for 1985, 1990, 1995 and 2000 were classified by maximum likelihood method, using Landsat MSS and TM imageries. Calibration and verification of HEC-1 were conducted using 4 storm events. Peak flow at Pyeong taek station increased $25.9m^3/sec$ during the past 15 years due to paddy and forest decrease. Streamflow impact by just paddy area decrease and forest area decrease were also analysed keeping watershed CN values unchanged of the given year, respectively.

• Journal of the Korean Geographical Society
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• v.50 no.3
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• pp.277-287
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• 2015

This paper addresses limitations of land-change modeling application in the context of REDD (Reducing Emissions from Deforestation and forest Degradation). REDD is an international conservation policy that aims to protect forests via carbon credit generation and trading. In REDD, carbon credits are generated only if there is measurable quantied carbon sequestration activities that are additional to business-as-usual (BAU). A "reference level" is defined as simulated baseline carbon emissions for the future under a BAU scenario, and predictive land-change modeling plays an important role in constructing reference levels. It is tested in this research how predictive accuracies of two land-change models, namely Geographic Emission Benchmark (GEB) and GEOMOD, vary with respect to different spatial scales: Xishuangbanna prefecture and Yunnan province. The accuracies are measured by Figure of Merit. In this Chinese case study, it turns out that GEB's better performance is mainly due to quantity (e.g., how many hectares of forest will be converted to agricultural land?) rather than spatial allocation (e.g., where will the conversion happen?). As both quantity and allocation are crucial in REDD reference level setting it appears to be fundamental to systematically analyze accuracies of quantity and allocation independently in pursuit of accurate reference levels.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.458-471
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• 2013

This paper addresses the limitation of a map comparison metric entitled Figure of Merit through employing a simple land change model. The metric was originally designed to overcome limitations of other existing statistics, such as Kappa, when assessing predictive accuracy of land change models. A series of comparisons between null and predicted outcomes at multiple resolutions as well as a multi-resolution Figure of Merit analysis techniques of validation are compared for spatially segregated calibration and validation datasets. The Figure of Merit at the null resolution in this paper was 57%, although future research must be done to determine if this was simply a coincidence. A Figure of Merit greater than 50% would seem to represent a "Resolution of Merit" in that the Figure of Merit at that resolution becomes greater than the error. Thus, these two metrics should be used in tandem to assess predictive accuracy of a land change model.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.49-66
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• 2024

Extreme rainfall will become intense due to climate change, increasing inundation risk to agricultural land. Hydrological and hydraulic simulations for the entire watershed were conducted to analyze the impact of climate change. Rainfall data was collected based on past weather observation and SSP (Shared Socio-economic Pathway)5-8.5 climate change scenarios. Simulation for flood volume, reservoir operation, river level, and inundation of agricultural land was conducted through K-HAS (KRC Hydraulics & Hydrology Analysis System) and HEC-RAS (Hydrologic Engineering Center - River Analysis System). Various scenarios were selected, encompassing different periods of rainfall data, including the observed period (1973-2022), near-term future (2021-2050), mid-term future (2051-2080), and long-term future (2081-2100), in addition to probabilistic precipitation events with return periods of 20 years and 100 years. The inundation area of the Aho-Buin district was visualized through GIS (Geographic Information System) based on the results of the flooding analysis. The probabilistic precipitation of climate change scenarios was calculated higher than that of past observations, which affected the increase in reservoir inflow, river level, inundation time, and inundation area. The inundation area and inundation time were higher in the 100-year frequency. Inundation risk was high in the order of long-term future, near-term future, mid-term future, and observed period. It was also shown that the Aho and Buin districts were vulnerable to inundation. These results are expected to be used as fundamental data for assessing the risk of flooding for agricultural land and downstream watersheds under climate change, guiding drainage improvement projects, and making flood risk maps.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.162-165
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• 2004

The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.211-217
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• 2006

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with urban expansion. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery. Old satellite Imagery is useful data to extract urban information. CORONA is a photo satellite reconnaissance program used from 1960 to 1972 and its imagery was declassified and has been available to the public since 1995. Since CORONA images are collected with panoramic cameras, several types of geometric distortions are involved. In this study we proposed mathematical modeling method which use modified collinearity equations. After the geometric modeling, we mosaicked images. We can successfully extract urban boundaries using GLCM method and visual interpretation in CORONA (1972) and SPOT (1995) imagery and detect urban changes in Seoul quantitatively.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.3-8
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• 1998

Using GIS and socio-economical data the relationship between human activities and global environmental change Is Analysed from the view point of food productivity and CO2 emission. Under the assumption that the population problem, the food problem and global warming due to energy consumption can be stabilized through managing land use, impacts of human activities such as consumption of food, energy and timber on global environment changes, and global population capacity are Analysed using developed system dynamics model in the research. In the model the world is divided into two groups: OECD countries and the others. Used global land use data set Is land cover map derived from satellite data, and potential distribution of arable land is estimated by the method of Clamor and Solomon which takes into consideration spatial distribution of climate data such as precipitation and evapotranspiration. In addition, impacts of CO2 emission from human activities on food production through global warming are included in the model as a feedback. The results of the analysis for BaU scenario and Toronto Conference scenario are similar to the results of existing models. From the result of this study, the human habitability in 2020 is 8 billion people, and CO2 emission in 2020 based on BaU Scenario and on Toronto Scenario is 1.7 and 1.2 times more than the 1986's respectively. Improving spatial resolution of the model by using global data to distribute the environmental variables and sauce-economical indices is left for further studies.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.123-141
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• 2017

This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.4
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• pp.395-403
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• 2000

It is so sensitive that the matter of compensation for private possessions caused in the course of public construction planning is very important. Especially, more logical planning is necessary when the dam be constructed, because it is mainly controlled by the surface of water, and if that planning is made public, artificial change is occurred in land use in that area for the purpose of rising the compensation. In this study, the plan for the application of aerial photo based ortho image was drew up for solving these problems and for the rational, rapid compensation. Ortho image was made by aerial photo, used as reading material for the change in land use. The modeling of drainage basin, came under the planning surface of water, and the 3D simulation were performed for the scene analysis, the change understanding in land use for a lot number in a certain period by overlapping the digital image, the digital land registration map, and the digital topography map as well as the analysis of the admitted land followed by the height of reservoir water.