• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.56-70
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• 2017

In this study, multi-image information for the central Taewha River basin was used to develop and analyze a distribution map of non-point pollution sources. The data were collected using a hyper-sensor (image), aerial photography, and a field spectro-radiometer. An image correction process was performed for each image to develop an ortho-image. In addition, the spectra from the field spectro-radiometer measurements were analyzed for each classification to create land cover and distribution maps of non-point pollutant sources. In the western region of the Taewha River basin, where most of the forest and agricultural land is distributed, the distribution map showed generated loads for BOD($kg/km^2{\times}day$) of 1.0 - 2.3, for TN($kg/km^2{\times}day$) of 0.06 - 9.44, and for TP($kg/km^2{\times}day$) of 0.03 - 0.24, which were low load distributions. In the eastern region where urbanization is in progress, the BOD, TN, and TP were 85.9, 13.69, and 2.76, respectively and these showed relatively high load distributions when the land use was classified by plot.

• Journal of the Korean earth science society
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• v.18 no.6
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• pp.515-521
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• 1997

To investigate the nature of the waste materials in the Nanjido Landfill, we have conducted multivariate statistical analysis of geophysical data set comprised of magnetic, gravity, LandSat TM thermal band and surface depression measurement data. Because these data sets show different responses to the depth, we have transformed the observed total field magnetic data and gravity data to the residual reduced-to-pole(RTP) magnetic anomalies and the three dimensional density anomalies, respectively, and utilized the informations about the upper shallow part of the landfills only in the following process. For the statistical analysis at the points of depression measurement, the magnetic, density and LandSat data values at these points are determined by interpolation process. Since the multivarite statistical analysis technique utilizes a clustering algorithm for classification of data set and we have measured the dissimilarity between objects by using Euclidean distance, standardization was applied prior to distance calculation in order to eliminate any scaling effects due to different measurement unit of each data set. The hierarchial grouping technique was used to construct the dendrogram. The optimum number of statistical groups(clusters), which are classified on the basis of geophysical and geotechnical characteristics, appeared to be six on the resulting dendrogram. The result of this study suggests that the dimension and nature of the multicomponent waste landfills can be identified by application of the multivarite statistical analysis technique to integrated geophysical data sets.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1581-1589
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• 2013

The aim of this study is to suggest a methodology for calculating the peak-hour ratio of passengers at urban railway stations by reflecting the characteristics of passenger demand patterns and the land use inventory of stations. To achieve this, urban railway stations in Seoul are divided into three groups by using factor analysis and cluster analysis. For each station group, we calculate five and four variables related to the passenger demand patterns and the land use inventory of stations, respectively, as well as the peak-hour ratios of passengers. Among these nine variables, average daily passengers and the location quotient (LQ) index for business services are selected as the classification criteria for station groups based on statistical tests. Using the two variables, a group allocation process is suggested to estimate the peak-hour ratio of passengers for a newly-constructed station. Evaluation results based on thirteen stations show that the proposed methodology produces lower errors than the currently-used guideline does. The results of this study contribute to establishing efficiently construction and operation plans for newly-constructed stations.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.81-99
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• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.352-363
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• 1999

It has been rare to obtain reliable information related to the size of forest land in North Korea. Several sources of forest statistics, ranging from the first map of forest distribution in Korean Peninsula produced in 1910 to official data reported by the North Korea Government in 1997, were gathered and analyzed to define the characteristics of forest cover changes over years. In addition, Landsat satellite data obtained from 1973 to 1993 were processed for the two study areas of the provinces of Pyungyang and Heasan, where the topography and land use pattern are significantly different each other. Using three sets of multitemporal Landsat imagery, land cover ma-ps were produced by computer classification. Although forest statistics reported before 1990 are somewhat inconsistent, they mere gradually decreasing over years. The estimates of 1991 satellite data and the recent statistics reported in 1998 shows very steep decline in forest lands as compared to the ones before 1990. The abrupt decrease of forest lands after 1990 was also found on the detailed analysis of Landsat data for the two study areas of Pyungyang and Heasan. The rapid decline of forest lands may have something to do with the poor economic situation of the country and the continuing natural disasters of severe flooding and drought. Unstocked forest, which was not classified into forest land, was a very distinct and pervasive land cover type that can be easily observed on satellite imagery. Since unstocked forest land in North Korea may be a critical factor for degrading environmental quality as well as for the continuing natural disasters, further analysis is necessary to define the exact extent and the physical characteristics of the cover type.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• Korean Journal of Environmental Agriculture
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• v.27 no.2
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• pp.120-132
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• 2008

Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze topography using DEM(digital elevation model) and classify landuse & landcover into 10 classes-paddy field, dry field, forest, bare land, grass & bush, water body, reclaimed land, salt farm, residence & building, and others-using Landsat TM images in North Korea. Elevation was greater than 1,000 meters in the eastern part of North Korea around Ranggang-do where Kaemagowon was located. Pyeongnam and Hwangnam in the western part of North Korea were low in elevation. Topography of North Korea showed typical 'east-high and west-low' landform characteristics. Landcover classification of North Korea using spectral reflectance of multi-temporal Landsat TM images was performed and the statistics of each landcover by administrative district, slope, and agroclimatic zone were calculated in terms of area. Forest areas accounted for 69.6 percent of the whole area while the areas of dry fields and paddy fields were 15.7 percent and 4.2 percent, respectively. Bare land and water body occupied 6.6 percent and 1.6 percent, respectively. Residence & building reached less than 1 percent of the country. Paddy field areas concentrated in the A slope ranged from 0 to 2 percent(greater than 80 percent). The dry field areas were shown in the A slope the most, followed by D, E, C, B, and F slopes. According to the statistics by agroclimatic zone, paddy and dry fields were mainly distributed in the North plain region(N-6) and North western coastal region(N-7). Forest areas were evenly distributed all over the agroclimatic regions. Periodic landcover analysis of North Korea based on remote sensing technique using satellite imagery can produce spatial and temporal statistics information for future landuse management and planning of North Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.61-69
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• 2015

This study was performed to provide fundamental data to establish the new soil pollution standards and the soil contamination management plans in a rational manner. The distribution characteristics of new soil contaminants such as barium (Ba) and chromium (Cr) in soils (n=140) were investigated in relation to land-use classification and geological features. Also, the sequential extraction test was conducted to evaluate fate and mobility of new soil contaminants. The soil samples taken from 140 sites were analyzed to survey distribution levels of selected new soil contaminants. The average concentration and range for hazardous metals (Ba, Cr) were Ba 128.946 (26.757~489.587) mg/kg, Cr 30.121 (2.579~132.783) mg/kg. Based on land use classification, the highest Ba concentration was found in factory soils, followed by dry field and park soils, while Cr concentration was highest in rice paddy soils, followed by dry field and factory soils. Within 10 geological units investigated the highest Ba and Cr concentrations were observed in the soils from Okcheon group and metamorphic rocks, respectively. The BCR (European Community Bureau of Reference) sequential extraction was conducted to identify chemical distributional existence of 2 elements of soils from each geological unit. Ba in soils is mainly assumed to exists as reducible form (such as BaSO₄, BaCO₃) and Cr in soils mainly is assumed to exist as residual form (such as Cr₂O₃, Cr_xFe_1-x(OH)₃(x < 1)).