• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.3-10
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• 2010

In this study, the orbit-based sensor modeling is applied to the digital plotting and the accuracy of digital plotting is analyzed. The KOMPSAT-2 satellite image with orbit-attitude model is used for the analysis. The precise sensor modeling with various combination of parameters is performed for the stereo satellite image. In addition, we analyze the error range of ground control points by applying the result of stereo modeling to digital survey system. According to the result, it is possible to produce digital map using stereo image with a small number of GCPs when the orbit-based sensor modeling for KOMPSAT-2 is applied. This means that it is suitable for the generation of digital map on a scale of 1/5,000 to 1/25,000 considering the resolution of KOMPSAT-2 image.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.133-143
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• 2009

This paper describes differences of performance when the orbit attitude model is applied to the respective images obtained from two different types of satellite. The one is Spot that rotates its pointing mirror and the other is Kompsat-2 that rotates its whole body when they obtain imagery for target. Our research scope is limited to the orbit-attitude model only as its good performance was proved in prior investigation. Model performances between two images were compared with sensor model accuracy and 3D coordinates calculation. The results show performances of the orbit-attitude model for each image type were different. For Spot imagery, the model required attitude angle to be included as adjustment parameters. For Kompsat-2 imagery, the model required high-order parameter for adjustment. This implies that satellite sensor model may be applied differently in accordance with platform's attitude control scheme and accuracy. Understanding of this information can be a base for improvement and development of model and application for new satellite images.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.51-58
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• 2011

Accurate DEM(Digital Elevation Model) generation using satellite images is an active research topic. This paper focuses on generation of a DEM with multiple Kompsat-2 images. For DEM generation, we applied an orbit-attitude sensor model and a RPM sensor model to stereo and multiple Kompsat-2 images respectively. For matching, we used an object-space based matching method. Through the result of this experiment, we could confirm that the sensor model from multiple images is more accurate than the model from stereo images. Also DEM from multiple images gave much better performance than DEM from stereo images.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.39-54
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• 2012

The objective of this study is to propose efficient data fusion techniques feasible to the KOMPSAT-2 satellite images. The most widely used image fusion techniques, which are the high-pass filter (HPF), the intensity-hue-saturation-based (modified IHS), the pan-sharpened, and the wavelet-based methods, was applied to four KOMPSAT - 2 satellite images having different regional and seasonal characteristics. Each fusion result was compared and analyzed in spatial and spectral features, respectively. Quality evaluation of image fusion techniques was performed in both quantitative and visual analysis. The quantitative analysis methods used for this study were the relative global dimensional error (spatial and spectral ERGAS), the spectral angle mapper index (SAM), and the image quality index (Q4). The results of quantitative and visual analysis indicate that the pan-sharpened method among the fusion methods used for this study relatively has the suitable balance between spectral and spatial information. In the case of the modified IHS method, the spatial information is well preserved, while the spectral information is distorted. And also the HPF and wavelet methods do not preserve the spectral information but the spatial information.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.49-54
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• 2011

Recently Korean government announced the vision for low-carbon green growth. Quantifying of the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. In the city planning the carbon storage estimation has become an important factor. In this paper, KOMPSAT-2 satellite imagery was used to develop a method to predict the urban forest carbon storage from the Normalized Difference Vegetation Index (NDVI) computed from a time sequence image data. The total carbon storage change by trees in the 6 administrative zonings of Jinju was estimated using the image data in 2007 and 2009. Therefore the paper presents a method based on the satellite images, which can estimate the spread of urban tree and carbon storage variation using KOMPSAT-2.

• Aerospace Engineering and Technology
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• v.1 no.2
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• pp.141-148
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• 2002

The purpose of this study is to enhance geo-location accuracy of the image data acquired by the Electro-Optical Camera(EOC) onboard KOMPSAT-1. EOC image data were analyzed to verify geo-location error. It was found that the major contribution was the time mark inaccuracy and attitude knowledge error. This study shows that the geo-location accuracy can be enhanced by modifying the time and attitude data of the ancillary data.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1537-1549
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• 2020

The ground sample distance of KOMPSAT-3 is 0.7 m for panchromatic band, 2.8 m for multi-spectral band, and the swath width of KOMPSAT-3 is 16 km. Therefore, an image of an area wider than the swath width (16 km) cannot be acquired with a single scanning. Thus, after scanning multiple areas in units of swath width, the acquired images should be made into one image. At this time, the necessary algorithm is called image mosaicking or image stitching, and is used for cartography. Mosaic algorithm generally consists of the following 4 steps: (1) Feature extraction and matching, (2) Radiometric balancing, (3) Seamline estimation, and (4) Image blending. In this paper, we have studied an effective seamline estimation method for satellite images. As a result, we can estimate the seamline more accurately than the existing method, and the heterogeneity of the mosaiced images was minimized.