• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.517-529
• /
• 2009

Many satellite image fusion techniques have been developed in order to produce a high resolution multispectral (MS) image by combining a high resolution panchromatic (PAN) image and a low resolution MS image. Heretofore, most high resolution image fusion techniques have used IKONOS and QuickBird images. Recently, GeoEye-1, offering the highest resolution of any commercial imaging system, was launched. In this study, we have experimented with GeoEye-1 images in order to evaluate which fusion algorithms are suitable for these images. This paper presents compares and evaluates the efficiency of five image fusion techniques, the $\grave{a}$ trous algorithm based additive wavelet transformation (AWT) fusion techniques, the Principal Component analysis (PCA) fusion technique, Gram-Schmidt (GS) spectral sharpening, Pansharp, and the Smoothing Filter based Intensity Modulation (SFIM) fusion technique, for the fusion of a GeoEye-1 image. The results of the experiment show that the AWT fusion techniques maintain more spatial detail of the PAN image and spectral information of the MS image than other image fusion techniques. Also, the Pansharp technique maintains information of the original PAN and MS images as well as the AWT fusion technique.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.2
• /
• pp.47-53
• /
• 2012

Recently many developed countries have used satellite images for classifying cropland areas to reduce time and efforts put into field survey. Korea also has used satellite images for the same purpose since KOMPSAT-2 was successfully launched and operated in 2006, but still far way to go in order to achieve the required accuracy from the products. This study evaluated the accuracy of the calculated croplands by using the objected classification method with various satellite images including ASTER, Spot-5, Rapid eye, Quickbird-2, Geo eye-1. Also, their usability and effectiveness for the cropland survey were verified by comparing with field survey data. As results. Geo eye-1 and Rapid eye showed higher accuracy to calculate the paddy field areas while Geo eye-1 and Quickbird-2 showed higher accuracy to calculate the upland field areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.2
• /
• pp.107-116
• /
• 2012

We investigated the accuracy in three dimensional geo-positioning derived by four high resolution satellite images acquired by two different sensors using the vendor-provided rational polynomial coefficients(RPC) based block adjustment in this research. We used two in-track stereo pairs of GeoEye-1 and WorldView-2 satellite and DGPS surveying data. In this experiment, we analyzed accuracies of RPC block adjustment models of two kinds of homogeneous stereo pairs, four kinds of heterogeneous stereo pairs, three 3 triplet image pairs, and one quadruplet image pair separately. The result shows that the accuracies of the models are nearly same. The accuracy without any GCPs reaches about CEP(90) 2.3m and LEP(90) 2.5m and the accuracy with single GCP is about CEP(90) 0.3m and LEP(90) 0.5m.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.4
• /
• pp.101-108
• /
• 2011

Construction of the Jangbogo antarctic station was planned, and it requires detailed information on topography of the area around the station. The purpose of this research is to generate the topographic map to construct the Jangbogo antarctic station using the satellite image. To do this, surveying and pre-test of equipment were conducted. In addition, for sensor modeling of the GeoEye-1 satellite image, RPC-bias correction was done, and it showed that at least two control points are required. In generating the map, a 1/2,500 scale was deemed suitable in consideration of resolution of the image and the fact that supplementary topographic surveying would be impossible. In order to provide detailed information on the topography around the Jangbogo station, the digital elevation model based on image matching was created, and compared with GPS-RTK data, accuracy of vertical location about 0.6m was exhibited.

• 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.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1407-1422
• /
• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Journal of Korean Physical Therapy Science
• /
• v.11 no.3
• /
• pp.14-27
• /
• 2004

This study approaches the effects of Balance Training on excercise performance and the prevention from the injuries caused by excercise. The subjects of the Balance Training program are female exercise beginners and the research period covers 8 weeks from January 10 to March 7, 2003. The research objects are 19 female golf beginners in 30s to 40s, who live in Seoul or Seongnam in Gyeonggi province and have played golf less than 6 months. The programs of the Balance Training and exercise performance were conducted to an 11 experimental group among the 19 research objects at the same time, and only the exercise performance program was applied to an 8 control group for 8 weeks. Before and after 8 weeks' application of the research programs to each group, the research subjects were examined, especially the components of their bodies, the balance and the performance capability were measured both before and after the test. The frequency of injuries by exercise was measured after the test, and the difference of the frequency was compared with the frequency before exercise. First, the experimental group, in a measurement of balance, showed that SN, MB, SAr and SAg of static balance decreased in a situation of MEO, MEC, GEO, GEC, TBEO, TBO, FHEO, FEO(p <0.05), but the control group increased. Second, the analysis on the change of exercise performance indicated better improvement in distance, ball speed, and accuracy of the experimental group than the control group(p<0.05). Third, the experience of injuries showed that there were 2 injuries in the experimental group and 11 injuries in the control group. The injured parts were 2 cases in the hands and fingers of the experimental group, and 1 case in the shoulder, 4 in the elbows, 4 in the hands and fingers and 2 in the lumber of the control group. From the above-mentioned results, it is recognized that the Balance Training program improved the exercise performance of female golf beginners and had good effects on the prevention from injuries. Accordingly, if this program is applied to sports-beginners, it will contribute to the improvement of the public health.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.56 no.3
• /
• pp.55-64
• /
• 2014

While utilizing high resolution satellite image for land use classification has been popularized, object-oriented classification has been adapted as an affordable classification method rather than conventional statistical classification. The aim of this study is to extract the paddy field area using object-oriented classification with time series NDVI from high-resolution satellite images, and the RapidEye satellite images of Jaeryung-gun in North Korea were used. For the implementation of object-oriented classification, creating objects by setting of scale and color factors was conducted, then 3 different land use categories including paddy field, forest and water bodies were extracted from the objects applying the variation of time-series NDVI. The unclassified objects which were not involved into the previous extraction classified into 6 categories using unsupervised classification by clustering analysis. Finally, the unsuitable paddy field area were assorted from the topographic factors such as elevation and slope. As the results, about 33.6 % of the total area (32313.1 ha) were classified to the paddy field (10847.9 ha) and 851.0 ha was classified to the unsuitable paddy field based on the topographic factors. The user accuracy of paddy field classification was calculated to 83.3 %, and among those, about 60.0 % of total paddy fields were classified from the time-series NDVI before the unsupervised classification. Other land covers were classified as to upland(5255.2 ha), forest (10961.0 ha), residential area and bare land (3309.6 ha), and lake and river (1784.4 ha) from this object-oriented classification.

• Korean Journal of Remote Sensing
• /
• v.28 no.2
• /
• pp.181-189
• /
• 2012

Recently, interest in potential for estimating water quality using high resolution satellite images is increasing. However, low SNR(Signal to Noise Ratio) over inland water and radiometric errors such as non-linearity of brightness value of high resolution satellite images often lead to accuracy degradation in water quality estimation. Therefore radiometric correction should be carried out to estimate water quality for high resolution satellite images. For KOMPSAT-2 images parameters for brightness value-radiance conversion are not available and precise radiometric correction is difficult. To exploit KOMPSAT-2 images for water quality monitoring, it is necessary to investigate non-linearity of brightness value and noise over inland water. In this paper, we performed brightness value comparison between KOMPSAT-2 images and IKONOS/GeoEye-1, which are known to show the linearity. We used the images obtained over the same area and on the same date for comparison. As a result, we showed that although KOMPSAT-2 images are more noisy;the trend of brightness value and pattern of noise are almost similar to reference images. The results showed that appropriate target area to minimize the impact of noise was $5{\times}5$. Non-linearity of brightness value between KOMPSAT-2 and reference images was not observed. Therefore we could conclude that KOMPSAT-2 may be used for estimation of water quality parameters such as concentration of chlorophyll.

• Journal of the Korean GEO-environmental Society
• /
• v.2 no.1
• /
• pp.67-79
• /
• 2001

The objective of this study is to determine the engineering properties of micro fine hybrid silicate grout materials that were developed recently. In this study, MSG-N type was mainly used as grout materials, and the chemical components, grain size distribution, mineral characteristics were analyzed. Moreover, the properties of active silica and ordinary portland cement acting as coagulating agent were analyzed and compared with each other. To determine the engineering properties, the bleeding test, viscosity test, coagulation test, examination with naked eye, photographing by using SEM, uniaxial compression test and in-situ application test for reclaimed ground were carried out. A series of test results showed that the strength of micro fine hybrid silicate grout materials was about twice that of ordinary sodium silicate grout materials, and alkali leakage decreased dramatically when MSG method was utilized. Especially, based on the evaluation of the application of the MSG method to field, this method would be very effective in reducing coefficient of permeability due to its excelent permeability.