• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.61-68
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• 2016

Digital aerial images have been commonly used in a large scale map production owing to their excellent geometry, and high spatial and radiometric resolution in recent years. However, a quality verification process for acquired images should be preceded in order to secure the high precision and reliability of produced results. Several experimental studies to verify digital imaging systems have been vigorously researched by constructing permanent test field in abroad. On the other hand, it is urgently necessary to suggest a practical scheme for an image quality verification, because this related study and experiment are still in its early stage at home. Hence, this study aims to present an easy method to measure the spatial resolution of the image in a visual way using a portable Siemens star. The images used in the study were obtained with three different cameras, two frame array sensors of DMC, UltraCamXp and a linear array sensor of ADS80. The Siemens star target appeared in every image is extracted and then the spatial resolution of image is compared with theoretical GSD(Ground Sample Distance) by a visual method. In addition, the change of spatial resolution depending on the location of the Siemens star from image center and flight direction and cross-flight direction is also compared and analyzed. As study results, while the theoretical GSDs of images taken with each camera are about 6~9cm, the visual resolutions are 1.2~1.3 times as great as the theoretical ones.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.51-59
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• 2016

Global consumption of fossil fuels continues to increase. As developing countries use fossil fuel as much as the existing fossil fuel using countries, the total amount of fossil fuel consumed has risen. The finite fossil energy depletion insecurity have become serious. In addition, fossil energy is caused by environmental pollution, economic and social problems remain in assignments that need to be addressed. Although solar power is clean and has many benefits, there are several problems in the process of installing a solar power plant. To solve these problems, floating photovoltaic plants has emerged as an alternative. This floating photovoltaic plants location analysis has not been made yet. In this study, the conditions of the floating photovoltaic plants location is analyzed with the Analytic Hierarchy Process using the terrain and climate factors. The score is assigned to the attribute information of each factor by the classification table. After multiplied by the weight the result is analyzed by visualization of the score. As the result, the score of the northen part of Gyeongsangbuk-do province is higher than the southern part of Gyeongsangbuk-do province. Especially Andongho lake in Andong City and the reservoir in Yeongyang-Gun are extracted as the optimal location. The score of the river boundary is low not the center of the river stream. It is expected that this study would be a more accurate floating solar power plant location analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.35-41
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• 2016

GNSS/Geoid positioning technology allows orthometric height determination using both the geoidal height calculated from geoid model and the ellipsoidal height achieved by GNSS survey. In this study, Network-RTK surveying was performed through the Benchmarks in the study area to analyze the possibility of height positioning of the Network-RTK. And the orthometric heights were calculated by applying the Korean national geoid model KNGeoid13 according to the condition of with site calibration and without site calibration and the results were compared. Simplex algorithm was adopted for liner programming in this study and the heights of all Benchmarks were calculated in both case of applying site calibration and does not applying site calibration. The results were compared to Benchmark official height of the National Geographic Information Institute. The results showed that the average value of the height difference was 0.060m, and the standard deviation was 0.072m in Network-RTK without site calibration and the average value of the height difference was 0.040m, and the standard deviation was 0.047m in Network-RTK with the application of the site calibration. With linearization method to obtain the optimal solution for observations it showed that the height determination within 0.033m was available in GNSS Network-RTK positioning.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.213-220
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• 2009

In order to predict the risk of freeze injury for 'Changhowon Hwangdo' peach trees, we used the dormancy depth (i.e., the daily chill unit accumulation during the overwintering period) as a proxy for the short-term, physiological tolerance to freezing temperatures. A Chill-days model was employed and its parameters such as base temperature and chilling requirement were optimized for peach trees based on the 12 observational experiments during the 2008-2009 winter. The model predicted the flowering dates much closer to the observations than other models without considering dormancy depth, showing the strength of employing dormancy depth into consideration. To derive empirical equations for calculating the probabilistic freeze risk, the dormancy depth was then combined with the browning ratio and the budburst ratio of frozen peach fruit branches. Given the exact date and the predicted minimum temperature, the equations calculate the probability of freeze damages such as a failure in budburst or tissue browning. This method of employing dormancy depth in addition to freezing temperature would be useful in locating in advance the risky areas of freezing injury for peach trees production under the projected climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.206-212
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• 2009

We investigated the patterns of freeze injury in dormant 'Changhowon Hwangdo' peach fruit by observing the extent of browning and germination of the branches that were treated with freezing temperature sets simulating the process of natural freezing incidences in orchards. Under the treatment of freezing temperature of $-15^{\circ}C$, the browning ratios were 15% for flower bud and less than 3% for both leaf bud and cambium. Under the $-20^{\circ}C$ treatment, the browning ratios were 40% for both flower and leaf buds and 1% for cambium. The browning ratios were 86%, 68% and 40% respectively for flower bud, leaf bud, and cambium under the $-25^{\circ}C$ treatment. All the samples showed 100% browning ratio under the $-30^{\circ}C$ treatment. The budburst ratios of leaf buds were 85%, 66%, 32%, and 0% under the -15, -20, -25 and $-30^{\circ}C$ treatments, respectively. The branches of peach fruit treated with the same freezing temperature showed different responses depending on the sampling date. In January the browning ratio was low and the budburst ratio was high whereas in February the opposite was the case, showing vulnerability of peach trees to low temperature after endo-dormancy release.

• 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.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.327-336
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• 2007

The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.