• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.5
• /
• pp.475-483
• /
• 2008

The purpose of this study is to figure out the research trend of surveying in Korea through the analyses of research field and the published year of surveying related papers in journals and theses of master and Ph. D. The papers and theses published since 1957 were collected and analyzed to find out the major research topics and trends with time. The analyses of research trends in terms of time showed certain correlation between research areas, for example, remote sensing is highly correlated with GIS (98%), GPS correlated with GIS(95%). Through the regression analysis, it was found that the trends of the most fields were well-fitted with a third-order polynomial except the field of Geodesy. Furthermore, it was predicted that the number of studies in general surveying, photogrammetry, remote sensing and land information will be increasing while those in GPS, GIS, digital map and Geodesy will be decreasing.

• Food Science and Preservation
• /
• v.10 no.3
• /
• pp.308-313
• /
• 2003

In the present study, we investigated the optimum recipe of the pumpkin drink using old pumpkin extract. Response surface methodology (RSM) was applied to optimize and monitor the drink recipe with pumpkin extract. The polynomial equation for color, flavor, taste, mouth feel, overall palatability, pH, brix and viscometer showed 0.7682, 0.9046, 0.9364, 0.9110, 0.8456, 0.9264, 0.7135 and 0.9906 of R$^2$, respectively and flavor, taste, mouth feel, overall palatability, pH and viscometer showed 5～10％ of significance level. The optimum ranges of recipe on organoleptic properties of pumpkin pouch drink were estimated on 86.5～87.5％ of the old pumpkin extract, 0.36～0.42％ of xanthan gum and 9％ of vinegar.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.739-744
• /
• 2002

Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

• Korean Journal of Remote Sensing
• /
• v.40 no.4
• /
• pp.387-396
• /
• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.5
• /
• pp.505-513
• /
• 2014

The RapidEye can acquire the 6.5m spatial resolution satellite imagery with the high temporal resolution on each day, based on its constellation of five satellites. The image products are available in two processing levels of Basic 1B and Ortho 3A. The Basic 1B image have radiometric and sensor corrections and include RPCs (Rational Polynomial Coefficients) data. In Korea, the geometric accuracy of RapidEye imagery can be improved, based on the scaled national digital maps that had been built. In this paper, we present the fully automated procedures to georegister the 1B data using 1:25,000 digital maps. Those layers of map are selected if the layers appear well in the RapidEye image, and then the selected layers are RPCs-projected into the RapidEye 1B space for generating vector images. The automated edge-based matching between the vector image and RapidEye improves the accuracy of RPCs. The experimental results showed the accuracy improvement from 2.8 to 0.8 pixels in RMSE when compared to the maps.

• Progress in Medical Physics
• /
• v.17 no.4
• /
• pp.212-223
• /
• 2006

Positional accuracy of the on-board imager (OBI) isocenter with gantry rotation was presented in this paper. Three different type of automatic evaluation methods of discrepancies between therapeutic and OBI isocenter using digital image processing techniques as well as a procedure stated in the customer acceptance procedure (CAP) were applied to check OBI isocenter migration trends. Two kinds of kV x-ray image set obtained at OBI source angle of $0^{\circ},\;90^{\circ},\;180^{\circ},\;270^{\circ}$ and every $10^{\circ}$ and raw projection data for cone-beam CT reconstruction were used for each evaluation method. Efficiencies of the methods were also estimated. If a user needs to obtain an isocenter variation map with full gantry rotation, a method taking OBI image for every $10^{\circ}$ and fitting with 5th order polynomial was appropriate. However for a mere quality assurance (QA) purpose of OBI isocenter accuracy, it was adequate to use only four OBI Images taken at the OBI source angle of $0^{\circ},\;90^{\circ},\;180^{\circ}\;and\;270^{\circ}$. Maximal discrepancy was 0.44 mm which was observed between the OBI source angle of $90^{\circ}\;and\;180^{\circ}$ OBI isocenter accuracy was maintained below 0.5 mm for a year. Proposed QA program may be helpful to Implement a reasonable routine QA of the OBI isocenter accuracy without great efforts.

• Journal of Mushroom
• /
• v.16 no.1
• /
• pp.22-30
• /
• 2018

This study was performed to determine optimal extraction conditions of fermented Polygonum multiflorum root by Lentinula edodes (JMI10079) Pegler mycelials using response surface methodology. The independent factors were extraction temperature (X1: $40-100^{\circ}C$), extraction time (X2: 2-10 hrs.), and the ratio of water to sample (X3: 33-100 mg/mL). Their effects were assessed on dependent variables of the extract properties, which included soluble solid contents (Y1), $^{\circ}Brix$ of sample extract (Y2), total polyphenol content (Y3), total flavonoid content (Y4), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical cation scavenging activity (Y5) and 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (Y6). The experimental data obtained were fit to a second-order polynomial equation. The optimal extraction conditions for fermented P. multiflorum root were: X1: $91.22^{\circ}C$, X2: 7.72 hrs, and X3: 39.71 mg/mL.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.4_1
• /
• pp.299-309
• /
• 2014

This paper evaluated the possibility for 1/5,000 digital topographic mapping by using PLEIADES images of 0.5m GSD(Ground Sampling Distance) resolution that has recently launched. Those results of check points by applying the initial RPC(Rational Polynomial Coefficient) of PLEIADES images came out as; RMSE of those were $X={\pm}1.806m$, $Y={\pm}2.132m$, $Z={\pm}1.973m$. Also, if we corrected geometric correction using 16 GCP(Ground Control Point)s, the results of RMSE became $X={\pm}0.104m$, $Y={\pm}0.171m$, $Z={\pm}0.036m$, and t he RMSE of check points were $X={\pm}0.357m$, $Y={\pm}0.239m$, $Z={\pm}0.188m$; which of those results indicated the accuracy of standard adjustment complied in error tolerances of the 1/5,000 scale. Additionally, we converted coordinates of points, obtained by TerraSAR. for comparing with measurements from GPS(Global Positioning System) surveying. The RMSE of comparing converted and GPS points were $X={\pm}0.818m$, $Y={\pm}0.200m$, $Z={\pm}0.265m$, which confirmed the possibility for 1/5,000 digital topographic mapping with PLEIADES images and GCPs. As method of obtaining GCPs in unaccessible area, however, the outcome evaluation of GCPs extracted from TerraSAR images was not acceptable for 1/5,000 digital topographic mapping. Therefore, we considered that further researches are needed on applicability of GCPs extracted from TerraSAR images for future alternative method.