• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Spatial Information Research
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• v.8 no.2
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• pp.275-288
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• 2000

The purpose of this study is to analyze relationship between the NDVI change pattern and landcover change pattern in the City of Sungnam during 1985 and 1996. The results of this study are as follows; (1) NDVI of the level 6 and 7 is decreased and the level 5 is increased in the area where Forst area changed to the other land cover during 1985 and 1996. (2) In the area where Agricultural-Pasture changed to forest, NDVI level became higher certainly during that time. But in the area where there has been changed from Agricultural-Pasture to Urban or built-up, Agricultural-Pasture to Barren land, the level of NDVI is decreased. (3) In the Urban or built-up to other land, or built-up the level of NDVI is increased. (4) In the area where Barren land changed to other land cover, the level of NDVI is increased.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.305-314
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• 2017

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.15-27
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• 2022

Climate change is considered a severe global problem closely related to carbon storage. However, recent urbanization and land-use changes reduce carbon stocks in terrestrial ecosystems. Recently, the role of protected areas has been emphasized as a countermeasure to the climate change, and protected areas allow the area to continue to serve as a carbon sink due to legal restrictions. This study attempted to expand the scope of these protected areas to an evaluation-based environmental spatial information theme map. In this study, the area of each grade was compared, and the distribution of land cover for each grade was analyzed using the Ecological and Nature Map, Environmental Conservation Value Assessment Map and Urban Ecological Map of Sejong Special Self-Governing City. Based on this, the average carbon storage for each grade was derived using the InVEST Carbon model. As a result of the analysis, the high-grade area of the environmental spatial information generally showed a wide area of the natural area represented by the forest area, and accordingly, the carbon storage amount was evaluated to be high. However, there are differences in the purpose of production, evaluation items, and evaluation methods between each environmental spatial information, there are differences in area, land cover, and carbon storage. Through this study, environmental spatial information based on the evaluation map can be used for land use management in the carbon aspect, and it is expected that a management plan for each grade suitable for the characteristics of each environmental spatial information is required.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.79-91
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• 2023

This study surveyed the actual status of reclamation areas in South Pyongan Province, North Korea, using satellite images and literature to survey the creation date, area, and length of the embankment of the reclamation areas. The reclamation areas in South Pyongan Province were created in three stages, with the first stage completed in the late 1970s or early 1980s, the second stage in the late 1980s or early 1990s, and the third stage in the 2000s. The total area of the reclamation areas is 105,570 hectares. The land cover of the reclamation areas is as follows: agriculture (50.5%), saltern (29.5%), water bodies (13.6%), foreshore (12.4%), grasslands (3.0%), bare land (0.4%), facility (0.1%), and forests (0.1%). The study also found that the NDVI values of the reclamation areas vary depending on the location. The NDVI values of the Gwiseong and Namyang reclamation areas are low, while the NDVI values of the Samcheonpo and Jigdongbaedali reclamation areas are high. The study found that the NDVI values of the reclamation areas are correlated with the land cover of the reclamation areas. The study's findings can be used to understand the development direction and regional characteristics of the reclamation areas in South Pyongan Province. The study's findings can also be used to develop policies and plans for the sustainable development and utilization of the reclamation areas in South Pyongan Province.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.382-385
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• 2008

MODIS images have a great advantage of high temporal resolution to monitor land cover changes in a large area. The moderate and low spatial resolution satellite images are incomparably economic than high resolution satellite images. As diverse satellite images are provided recently, strategies using satellite images are necessary for continuous, effective and long-term land monitoring. This research purposed to use MODIS images to monitor land cover in Korean peninsula for long-term and continuous change detection. To maximize the advantages of high temporal resolution, the change detection was based on the MODIS temporal profiles of the surface reflectance for one year. In this study as the reflectance patterns of year 2005 were compared with the reflectance patterns of year 2007, the changed pixels could be detected during two years. To set up the threshold value for the decision of change, ASTER images with the higher spatial resolution, 15m, were used for this study. The test area covered the suburban area of metropolitan city, Seoul, where the landcover changes have been frequently happened.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.102-106
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• 2005

As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.35-43
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• 2008

The purpose of this study is to evaluate the hydrological impact due to temporal land cover change by gradual urbanization of upstream watershed of Pyeongtaek gauging station of Anseong-cheon. WMS HEC-1 was adopted, and OEM with 200 m resolution and hydrologic soil group from 1:50,000 scale soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. The watershed showed a trend that forest & paddy areas decreased and urban/residential area gradually increased during the four selected years. The model was calibrated at 2 locations (Pyeonglaek and Gongdo) by comparing observed with simulated discharge results for 5 summer storm events from 1998 to 2001. The watershed average CN values varied from 61.7 to 62.3 for the 4 selected years. To identify the impact of streamflow by temporal area change of a target land use, a simple evaluation method that the CN values of areas except the target land use are unified as one representative CN value was suggested. By applying the method, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• Journal of Environmental Science International
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• v.28 no.2
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• pp.259-266
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• 2019

Two main sources of data, meteorological data and land surface characteristics, are essential to effectively run a distributed rainfall-runoff model. The specification and averaging of the land surface characteristics in a suitable way is crucial to obtaining accurate runoff output. Recent advances in remote sensing techniques are often being used to derive better representations of these land surface characteristics. Due to the mismatch in scale between digital land cover maps and numerical grid sizes, issues related to upscaling or downscaling occur regularly. A specific method is typically selected to average and represent the land surface characteristics. This paper examines the amount of flooding by applying the FLO-2D routing model, where vegetation heterogeneity is manipulated using the Manning's roughness coefficient. Three different upscaling methods, arithmetic, dominant, and aggregation, were tested. To investigate further, the rainfall-runoff model with FLO-2D was facilitated in Yongdam catchment and heavy rainfall events during wet season were selected. The results show aggregation method provides better results, in terms of the amount of peak flow and the relative time taken to achieve it. These rwsults suggest that the aggregation method, which is a reasonably realistic description of area-averaged vegetation nature and characteristics, is more likely to occur in reality.