• Journal of Wetlands Research
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• v.13 no.1
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• pp.95-104
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• 2011

This study was implemented to select the suitable site for Palustrine Wetland at habitat restoration for Oriental stork, red species and top-level predator in ecosystem. The evaluation items was fitted by review the antecedent studies on the suitable site selection model and evaluation items of wetland. The study sites were setted in $5,884,800m^2$ area including Yesan-gun Dae-ree, in which Oriental stork' park will be located, through DEM(Digital Elevation Model) watershed analysis. The thematic map by valuation items with secure of water resource, soil, topography, distance between roads, houses, etc., land using, wildlife corridor, and type of water resource was prepared using GIS program. The sites with high evaluation score were selected as suitable creation sites for wetland through overlapping those maps. Total 8 sites with over 18 point were selected. The characteristics of selected sites show that the soil are consisted of clay, the connectivity is valued high with surface water, the slope are gentle, and the connectivity is good with surroundings ecosystem. The result of water quality analysis, which was implement to survey available water resources and develop the solution of problem of water environment, showed that water quality at Salmok reservoir and Bogang reservoir is generally good, but the water quality at stagnant water body rising out from groundwater is not good. This study has limit to select the suitable sites of wetland only by analyzing physiotherapy environment in study area. Hereafter, the study is need to examine closely enhancement effects of biological diversity through investigation of biotic environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.379-387
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• 2006

The real world is spatially modelled conceptually either as discrete objects or earth surface. The generated data models are then usually represented as vector and raster respectively. Although there are limited cases where only one data model is sufficient to solve the spatial problem at hand, it is now generally accepted that GIS should be able to handle various types of data model. Recent advances in spatial technology introduced even more variety of heterogeneous data models and the need is ever growing to handle and manage efficiently these large variety of spatial data. The OGC (Open GIS Consortium), an international organization pursuing standardization in the geospatial industry. recently introduced the GMLJP2 (Geographic Mark-Up Language JP2) format which enables store and handle heterogeneous spatial data. The GMLJP2 format, which is based on the JP2 format which is an abbreviation for JPEG2000 wavelet image compression format, takes advantage of the versatility of the GML capabilities to add extra data on top of the compressed image. This study takes a close look into the GMLJP2 format to analyse and exploit its potential to handle and mange hetergeneous spatial data. Aerial image, digital map and LIDAR data were successfully transformed end archived into a single GMLJP2 file. A simple viewing program was made to view the heterogeneous spatial data from this single file.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.94-101
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• 2008

Warming trends during winter seasons in East Asian regions are expected to accelerate in the future according to the climate projection by the Inter-governmental Panel on Climate Change (IPCC). Warmer winters may affect short-term cold hardiness of deciduous fruit trees, and yet phenological observations are scant compared to long-term climate records in the regions. Dormancy depth, which can be estimated by daily temperature, is expected to serve as a reasonable proxy for physiological tolerance of flowering buds to low temperature in winter. In order to delineate the geographical pattern of short-term cold hardiness in grapevines, a selected dormancy depth model was parameterized for "Campbell Early", the major cultivar in South Korea. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HDDTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations and a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and site elevation). To generate relevant datasets for climatological normal years in the future, we combined a 25km-resolution, 2011-2100 temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 scenario) with the 1971-2000 HD-DTM. The dormancy depth model was run with the gridded datasets to estimate geographical pattern of change in the cold-hardiness period (the number of days between endo- and forced dormancy release) across South Korea for the normal years (1971-2000, 2011-2040, 2041-2070, and 2071-2100). Results showed that the cold-hardiness zone with 60 days or longer cold-tolerant period would diminish from 58% of the total land area of South Korea in 1971-2000 to 40% in 2011-2040, 14% in 2041-2070, and less than 3% in 2071-2100. This method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of Korean Neurosurgical Society
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• v.30 no.2
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• pp.131-136
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• 2001

Object : The clinical uses of screws are increasing with broader applications in spinal disorders. When screws are inserted repeatedly to achieve optimal position, tips of screw pitch may become damaged during insertion even though there are significant differences in the moduli of elasticity between bone and titanium. The effect of repeated screw insertion on pullout resistance was investigated. Methods : Three different titanium screws(cortical lateral mass screw, cancellous lateral mass screw and cervical vertebral body screw) were inserted into the synthetic cancellous material and then extracted axially at a rate of 2.4mm/min using Instron(Model TT-D, Canton, MA). Each set of screws was inserted and pulled out three times. There were six screws in each group. The insertional torque was measured with a torque wrench during insertion. Pullout strength was recorded with a digital oscilloscope. Results : The mean pullout force measurements for the cortical lateral mass screws($185.66N{\pm}42.60$, $167.10N{\pm}27.01$ and $162.52 N{\pm}23.83$ for first, second and third pullout respectively : p=0.03) and the cervical vertebral body screws($386.0N{\pm}24.1$, $360.2N{\pm}17.5$ and $330.9N{\pm}16.7$ : p=0.0024) showed consecutive decrease in pullout resistance after each pullout, whereas the cancellous lateral mass screws did not($194.00N{\pm}36.47$, $219.24N{\pm}26.58$ and 199.49N(36.63 : p=0.24). The SEM after insertion and pullout three times showed a blunting in the tip of the screw pitch and a smearing of the screw surface. Conclusions : Repetitive screw insertion and pullout resulted in the decrease of pullout resistance in certain screws possibly caused by blunting the screw tip. This means screw tips suffer deformations during either repeated insertion or pullout. Thus, the screws that have been inserted should not be used for the final construct.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.104-115
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• 2014

A levee is defined as an man-made structure protecting the areas from temporary flooding. This paper suggests a methodology for establishing the levee GIS database using the airborne topographic LiDAR(Light Detection and Ranging) data taken in the Nakdong river basins and the WAMIS(WAter Management Information System) information. First, the National Levee Database(NLD) established by the USACE(United States Army Corps Engineers) and the levee information tables established by the WAMIS are compared and analyzed. For extracting the levee information from the LiDAR data, the DSM(Digital Surface Model) is generated from the LiDAR point clouds by using the interpolation method. Then, the slope map is generated by calculating the maximum rates of elevation difference between each pixel of the DSM and its neighboring pixels. The slope classification method is employed to extract the levee component polygons such as the levee crown polygons and the levee slope polygons from the slope map. Then, the levee information database is established by integrating the attributes extracted from the identified levee crown and slope polygons with the information provided by the WAMIS. Finally, this paper discusses the advantages and limitations of the levee GIS database established by only using the LiDAR data and suggests a future work for improving the quality of the database.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.261-269
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• 2006

There is a need to restore the terrain back its natural environment after mining development. It is necessary to compare the original and developing surfaces for post-management and to analyze the terrain change to develop a process for efficient restoration plan. This study analyzes and compares change to the terrain by annual mining development using GIS. Contours digitized with CAD based on photogrammetry are classified into annual data and created by Triangulated Irregular Network (TIN). By producing profiles and cross sections using TIN, many stations are distinguished. As a result of the terrain changes caused by mining development from 2000 to 2003 by operating elevation values each cell converted to raster from TIN, $11,094,460m^3$ are cut and $5,127,968m^3$ are filled up to 46% of cut volume, and annual surface changes of cut and fill area to mining are analyzed to visual and quantitative data. This study is used for the restoration plan and additional mining. And it is expected that this annual change, caused by mining development, can be used to return the terrain close to its original condition for finished mining area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.551-560
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• 2014

Compare to other industrial sites, the civil construction work not only takes longer time but also has made of complicated processes, such as the integrated management, process control, and quality control until the completion. However, it is hard to take control the construction sites, since numerous issues are always emerged. The study purposes on providing the dataset to synthetically manage and monitor the civil construction site, main design, drawings, process, construction cost, and others at real-time by using the low altitude close-range aerial images, based on UAV, and the GPS surveying method for treating the three-dimensional spatial information quickly and accurately. As a result, we could provide the latest information for the quick decision-making following from planning to completion of the construction, and objective site evaluation by the high-resolution three-dimensional spatial information and drawings. Also, the present map, longitudinal map, and cross sectional view are developed to provide various datasets rapidly, such as earthwork volume table, specifications, and transition of ground level.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1179-1194
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• 2020

This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R² (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R² = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.