• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.252-262
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• 2020

In Remote Sensing, a machine learning based SVM model is typically utilized for land cover classification. And study using neural network models is also being carried out continuously. But study using high-resolution imagery of KOMPSAT is insufficient. Therefore, the purpose of this study is to assess the accuracy of land cover classification by neural network models using high-resolution KOMPSAT-3 satellite imagery. After acquiring satellite imagery of coastal areas near Gyeongju City, training data were produced. And land cover was classified with the SVM, ANN and DNN models for the three items of water, vegetation and land. Then, the accuracy of the classification results was quantitatively assessed through error matrix: the result using DNN model showed the best with 92.0% accuracy. It is necessary to supplement the training data through future multi-temporal satellite imagery, and to carry out classifications for various items.

• Proceedings of the KSRS Conference
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• v.1
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.357-366
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• 2006

A traditional image analysis or classification method using satellite imagery is mostly based on the spectral information. However, the spatial information is more important according as the resolution is higher and spatial patterns are more complex. In this study, we attempted to compare and analyze the variogram properties of actual high resolution imageries mainly in the urban area. Through the several experiments, we have understood that the variogram is various according to a sensor type, spatial resolution, a location, a feature type, time, season and so on and shows the information related to a feature size. With simple modeling, we confirmed that the unique variogram types were shown unlike the classical variogram in case of small subsets. Based on the grasped variogram characteristics, we made a level index map for determining urban complexity or land-use classification. These results will become more and more important and be widely applied to the various fields of high-resolution imagery such as KOMPSAT-2 and KOMPSAT-3 which is scheduled to be launched.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.4
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• pp.405-414
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• 2000

A new generation of commercial satellites like IKONOS, SPOT-5 and OrbView-3,4 will have improved features, especially an higher geometric resolution with a better dynamic radiometric range. In addition high precision orbital position and attitude data will be provided by the on-board GPS receivers, IMU(Inertial Measurement Units) and star trackers. This additional information allows for reducing the number of ground control points. Furthermore this information enables direct georeferencing of imagery without ground control points. In our work mathematical models for calculating the satellite orbital parameters of SPOT-3 and KOMPSAT-1 were developed and can be easily extended to process images from other high resolution imaging systems as they become available.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.282-296
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• 2012

This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.3-11
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• 2009

This study aims at proposing that high resolution satellite images could be used to form an urban management plan by calculating the amount of green areas and detecting land use changes in each zoning region within urban planning jurisdiction of Jinju in Gyeongsangnam-do selected as a case study area, analysing imagery of IKONOS and KOMPSAT-2 that are high resolution satellite images. In conclusion, application possibilities of high resolution satellite images as assessment data of urban management administration that help to assess changes in each zoning region are indicated after developing modules based on ArcGIS for calculation and detection of green areas and land use changes and then analysing land use changes and spatial distribution of green areas by using those modules.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.563-569
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• 2021

With the launch of Compact Advanced Satellite 500 series of various characteristics and the operation of KOMPSAT-3/3A, uses of high-resolution satellite images have been continuously increased. Especially, in order to provide satellite images in the form of ARD (Analysis Ready Data), various pre-processing such as geometric correction and radiometric correction have been developed. For pre-processing of high spatial satellite imagery, auxiliary information, such as solar zenith, solar azimuth and offnadir angle, should be required. However, most of the high-resolution satellite images provide the solar zenith and nadir angle for the entire image as a single variable. In this paper, the solar zenith and offnadir angle corresponding to each pixel of the image were calculated using RFM (Rational Function Model) and auxiliary information of the image, and the quality of extracted information were evaluated. In particular, for the utilization of pixel-based solar zenith and offnadir angle, pixel-based auxiliary data were applied in calculating the top of atmospheric reflectance, and comparative evaluation with a single constant-based top of atmospheric reflectance was performed. In the experiments using various satellite imagery, the pixel-based solar zenith and offnadir angle information showed a similar tendency to the auxiliary information of satellite sensor, and it was confirmed that the distortion was reduced in the calculated reflectance in the top of atmospheric reflectance.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2027-2034
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• 2021

Using multi-temporal KOMPSAT-3/3A high-resolution satellite images, the Normalized Difference Vegetation Index (NDVI) for the area around the Fukushima daiichi nuclear power plant was determined, and the pattern of vegetation changes was analyzed. To calculate the NDVI, surface reflectance from the KOMPSAT-3/3A satellite image was used. Satellite images from four years were used, and the zones where the images overlap was designated as the area of interest (AOI) for the study, and by setting a profile passing through highly vegetated area as a data analysis method, the changes by year were examined. In addition, random points were extracted within the AOI and displayed as a box plot to quantitatively indicate change of NDVI distribution pattern. The main results of this study showed that the NDVI in 2014 was low within AOI in the vicinity of the nuclear power plant, but vegetated area continued to expand until 2021. These results were also confirmed in the change monitoring results shown in a profile or box plot. In disaster areas where access is restricted, such as the Fukushima nuclear power plant area, where it is difficult to collect field data, obtaining land cover classification products with high accuracy using satellite images is challenging, so it is appropriate to analyze them using primary outputs such as vegetation indices obtained from high-resolution satellite imagery. It is necessary to establish an international cooperation system for jointly utilizing satellite images. Meanwhile, to periodically monitor environmental changes in neighboring countries that may affect the Korean peninsula, it is necessary to establish utilization models and systems using high-resolution satellite images.

• Journal of Space Technology and Applications
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• v.1 no.3
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• pp.337-355
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• 2021

This paper is made to suggest a future strategy for the Korean High Resolution Wide Swath Synthetic Aperture Radar (HRWS SAR) satellite development by surveying the current trends for the SAR satellite technologies. From the survey, the latest SAR technology trends are revealed of using Digital Beam-Forming (DBF), SCan-On-Receive (SCORE), Displaced Phase Center Antenna (DPCA), interferometry, and polarimetry for exploiting the SAR imagery. Based on the latest SAR technology trends and the foreign HRWS SAR development cases, the strategy for the future HRWS Korean SAR satellite development is suggested to develop the DPCA and SCORE technologies by using the KOrea Multi-Purpose SATellite-6 (KOMPSAT-6) which is going to launch in a few years, and consequently to develop the HRWS SAR satellites which can monitor the whole Earth at weekly intervals.