• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.495-502
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• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.129-134
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• 2000

To utilize the survey method using the geodetic satellite GPS, we tried to analysis the GPS/Leveling and the geopotential model of the 26 GPS observation points including 23 BM and 3 triangulation points with approximately 16-km interval selected from the Andong geographic map with a scale of 1:250,000. The average deviations of the geopotential model calculated from the results of analysis to the GPS/Leveling and the previously developed geopotential models(EGM96, OSU91A, and KGEOID), are 0.493 m, 0.277 m, and 0.195 m, respectively and RMS errors are $\pm$0.299 m, $\pm$0.152 m, and $\pm$ 0.133 m. The general trend of geoid undulations, however, shows an increasing pattern to the NW-SE direction. It has been also reported that the geoid undulation related with topographic-highs and geoid-highs although very poor relationship is shown in this area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.9-17
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• 2007

In this study, Digital Elevation Models (DEMs) were constructed from color images, grayscale images and each bands (Red, Green, Blue) of color image, and the accuracies of each DEMs were evaluated, And then, correlation coefficients between left and right images of each stereopairs were analyzed. The DEM can be constructed conventionally from the digital map and stereopair images using image matching. The image matching requires stereo satellite images or aerial photographs. In case of rotor aerial photographs, these are to be scanned in 3 bands (Red, Green, Blue). For this study, 5 types of images were acquired; color, grayscale, RED band, GREEN band, and BLUE band image. DEMs were constructed from 5 types of stereopair images and evaluated using elevation points of digital maps. In order to analyze the cause of various accuracies of each DEMs, the similarity between left and right images of each stereopairs were analyzed. Consequently, the accuracy of the DEM constructed from RED band images of color aerial photograph were proved best.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.4
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• pp.405-415
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• 2011

The objective of this study was to compare greenhouse gas emissions from road transportation by calculation methods (Tier 1, Teir 2, and Tier 3). Tier 1 based on 2006 IPCC guidelines default emission factor and amount of fuel consumption. The Tier 2 approach is the same as Tier 1 except that country-specific carbon contents of the fuel sold in road transport are used. Tier 2 based on emission factor of guidelines for local government greenhouse gas inventories (Korea Environment Corporation), the fuel consumption per one vehicle, and the registered motor vehicles. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories (National Institute of Environmental Research) and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT) for each vehicle subcategory and possible road type. VKT was estimated by using GIS road map and traffic volume of the section. The GHG average emission rate by the Tier 1 was 728,857 $tonCO_2eq$/yr, while Tier 2 and Tier 3 were 864,757 $tonCO_2eq$/yr and 661,710 $tonCO_2eq$/yr, respectively. Tier 3 was underestimated by 10.1 and 20.7 percent for the GHG emission observed by Tier 1 and Tier 2, respectively. Based on this study, we conclude that Tier 2 is reasonable GHG emissions than Tier 1 or Tier 3. But, further study is still needed to accurate GHG emission from Tier 3 method by expanding the traffic survey area and developing the model of local road traffic.

• Journal of Korean Society of Rural Planning
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• v.16 no.2
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• pp.47-55
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• 2010

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.617-625
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• 2014

The Rational Function Model has been used as a replacement sensor model in most commercial photogrammetric systems due to its capability of maintaining the accuracy of the physical sensor models. Although satellite images with rational polynomial coefficients have been used to determine three-dimensional position, it has limitations in the accuracy for large scale topographic mapping. In this study, high resolution stereo satellite images, QuickBird-2, were used to investigate how much the three-dimensional position accuracy was affected by the No. of ground control points, polynomial order, and distribution of GCPs. As the results, we can confirm that these experiments satisfy the accuracy requirements for horizontal and height position of 1:25,000 map scale.

• Tunnel and Underground Space
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• v.18 no.4
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• pp.252-262
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• 2008

In the uniaxial compressive test of a single specimen of transversely isotropic rock, its 5 independent elastic constants can not be defined since maximum 4 independent strain measurements are available theoretically. In order to solve this problem, one equation proposed by Saint Venant in 19C and confirmed by Lekhnitskii through the test experiences has been used for long time. Accordign to authors' experiences, however, this equation turned out to give erroneous elastic constants in some cases. Three new equations are suggested and their compatibilities are discussed in this paper. As the results of the analyses of the models, Lekhnitskii's suggested equation is effective for the specimen with the high dip angle whereas it results in the large erred output for that with dip angle less than $25{\sim}30$. It was found that the effectivenesses of three suggested equations and their compatibilities are subject to the dip angle and not to the amounts of elastic constants. Guide map to the selection of the compatible one of those suggested equations is presented as a result of the study.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.58-67
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• 2000

Todays enterprise networks are composed of multiple types of interconnected networks.Enterprise Networks interoperability between these technologies is needed. To enable interworking, it is necessary to be able to map between the relevant object models and to build on this to provide a mechanism to handle protocol conversion on the domain boundaries.In this paper, we describe a gateway between management application in the CORBA domain and agent in the SNMP domain and various integration methods. The main function of the gateway is to dynamically convert the method invocations on object reference in CORBA domain to SNMP messages for MIB entries at remote agents, We also present translation methods from SNMP MIB to CORBA IDL using Direct translation and Abstract translation. JIDM algorithm has no notion of containment and inheritance relationships between object classes and is difficult to understanding between management attribute and SNMP Action attribute. Abstract translation over come these problems.New superclasses define for common attributes and define explicit CORBA method for SNMP Action.It is a methodology for obtaining the CORBA-compliant management agents from already existing SNMP agents.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.1-12
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• 2002

Landslide prediction modeling has been regarded as one of the important environmental applications in GIS. While, landslide stability in a certain area as collateral process for prediction modeling can be characterized by DEM-based hydrological features such as flow-direction, flow-accumulation, flow-length, wetness index, and so forth. In this study, Slope-Area plot methodology followed by stability index mapping with these hydrological variables is firstly performed for stability analysis with actual landslide occurrences at Boeun area, Korea, and then Landslide prediction modeling based on likelihood ratio model for landslide potential mapping is carried out; in addition, KOMPSAT EOC imagery is used to detect the locations and scalped scale of Landslide occurrences. These two tasks are independently processed for preparation of unbiased criteria, and then results of those are qualitatively compared. As results of this case study, land stability analysis based on DEM-based hydrological variables directly reflects terrain characteristics; however, the results in the form of land stability map by landslide prediction model are not fully matched with those of hydrologic landslide analysis due to the heuristic scheme based on location of existed landslide occurrences within prediction approach, especially zones of not-investigated occurrences. Therefore, it is expected that the resets on the space-robustness of landslide prediction models in conjunction with DEM-based landslide stability analysis can be effectively utilized to search out unrevealed or hidden landslide occurrences.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.161-169
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• 2007

A study was conducted in the Hong Kong with the aim of deriving an algorithm for the retrieval of suspended sediment (SS) and sea surface salinity (SSS) concentrations from Aqua/MODIS level 1B reflectance data with 250m and 500m spatial resolutions. 'In-situ' measurements of SS and SSS were also compared with coincident MODIS spectral reflectance measurements over the ocean surface. This is the first study of SSS modeling in Southeast Asia using earth observation satellite images. Three analysis techniques such as multiple regression, linear regression, and principal component analysis (PCA) were performed on the MODIS data and the 'in-situ' measurement datasets of the SS and SSS. Correlation coefficients by each analysis method shows that the best correlation results are multiple regression from the 500m spatial resolution MODIS images, $R^2$= 0.82 for SS and $R^2$ = 0.81 for SSS. The Root Mean Square Error (RMSE) between satellite and 'in-situ' data are 0.92mg/L for SS and 1.63psu for SSS, respectively. These suggest that 500m spatial resolution MODIS data are suitable for water quality modeling in the study area. Furthermore, the application of these models to MODIS images of the Hong Kong and Pearl River Delta (PRO) Region are able to accurately reproduce the spatial distribution map of the high turbidity with realistic SS concentrations.