• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.257-267
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• 2011

This paper examines the spatial and temporal variability in the shoreline boundary caused by artificial structures in Songdo Beach of South Korea. Quickbird Images of 2003, 2005, 2007, and 2010 extracted from Google Earth were used to identify changing trends of shoreline boundary. The most significant changes were observed in area where groins were extensively established, inducing the sand beach much narrower than before in almost 75% of the area($15070.72m^2$ in 2003 to $3877.46m^2$ in 2010). The Google Earth made it possible to identify area-wide patterns of shoreline change subject to many different type of artificial structures, which cannot be acquired by traditional field sampling. Groin heights, lengths and profiles can be modified during maintenance operations if the Google Earth monitoring indicates that the initial layout is not operating properly as a physical barrier to control sediment transport. It is anticipated that this research could be used as a valuable reference to confirm the outputs from past field researches for coastal processes to respond to storms in more visual and quantitative manner.

• Journal of the Korean association of regional geographers
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• v.15 no.3
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• pp.421-433
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• 2009

The impervious ratio was frequently employed as a fundamental attribute will be used as a proxy of the total environmental burden in the urban area since it may contribute as much or more on a cumulative basis to the overall environmental condition. This research proposes a comparative evaluation framework in a more objective and Quantitative way for an impervious ratio in the university campus, using the Google Earth. Two university campuses (Kyungpook National University: KNU, Hong Kong University: HKUJ were selected as survey objectives in order to evaluate the potential of Google Earth in monitoring impervious conditions in the campus. The 61cm resolution of Quickbird data combined with digital map realistically identified the major type of impervious surface such as road, building and parking lots in the study area by large scale spatial precision. The impervious zones with persistently high road density and parking space were specifically identified over the KNU campus while the HKC campus was intensively covered by tree, resulting in almost twice (31%). as compared to KNU (18.4%), The methods of characterizing impervious surface used in this study are easily replicable using data that are primarily publicly available, and therefore the collection of impervious coverage data via Google Earth is, therefore, proposed as a practical alternative.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.227-239
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• 2014

This study aims to evaluate performance of various image fusion methods based on the spectral responses of high-resolution optical satellite sensors such as KOMPSAT-2, QuickBird and WorldView-2. The image fusion methods used in this study are GIHS, GIHSA, GS1 and AIHS. A quality evaluation of each image fusion method was performed with both quantitative and visual analysis. The quantitative analysis was carried out using spectral angle mapper index (SAM), relative global dimensional error (spectral ERGAS) and image quality index (Q4). The results indicates that the GIHSA method is slightly better than other methods for KOMPSAT-2 images. On the other hand, the GS1 method is suitable for Quickbird and WorldView-2 images.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.55-61
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• 2005

Digital Elevation Model (DEM) generation from remotely sensed imagery is crucial for a variety of mapping applications such as ortho-photo generation, city modeling. High resolution imaging satellites such as SPOT-5, IKONOS, QUICK-BIRD, ORBVIEW constitute an excellent source for efficient and economic generation of DEM data. However, prerequisite knowledge in the areas of sensor modeling, epipolar resampling, and image matching is required to generate DEM from these high resolution satellite imagery. From the above requirements, epipolar resampling emerges as the most important factors. Research attempts in this area are still in high demand and short supply. Another cause that adds to the complication of the problem is that most studies of DEM generation from IKONOS scenes have been based on rational function model. In this paper, we proposed a new methodology for DEM generation from satellite scenes using parallel projection model which is sensor independent, makes it possible for sensor modeling and epipolar resampling by only few control points. The performance and feasibility of the developed methodology is evaluated through real dataset captured by IKONOS.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.238-242
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• 2007

Today's commercial high resolution satellite imagery such as that provided by IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Digital maps supply the most generally used GIS data probiding topography, road, and building information. Currently, the building information provided by digital maps is incompletely constructed for GIS applications due to planar position error and warped shape. We focus on extracting of the accurate building information including position, shape, and height to update the building information of the digital maps and GIS database. In this paper, we propose a new method of 3D building information extraction with a single high resolution satellite image and digital map. Co-registration between the QuickBird image and the 1:1,000 digital maps was carried out automatically using the RPC adjustment model and the building layer of the digital map was projected onto the image. The building roof boundaries were detected using the building layer from the digital map based on the satellite azimuth. The building shape could be modified using a snake algorithm. Then we measured the building height and traced the building bottom automatically using triangular vector structure (TVS) hypothesis. In order to evaluate the proposed method, we estimated accuracy of the extracted building information using LiDAR DSM.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.89-100
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• 2010

The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.

• Korean Journal of Environmental Agriculture
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• v.28 no.1
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• pp.1-8
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• 2009

This study was aimed at assess environmental conservation functions by analyzing the change of land use areas in agricultural fields between 1999 and 2006, and comparing land surface temperature distribution between 1994 and 2006 in Yongin city. Land use maps of Yongin city were obtained from soil maps for 1999, Quickbird satellite images(less than 1 m) and parcel map for 2006. The land use area for Yongin city was in the order of forest > paddy field > upland > residence & building in 1999, and forest > residence & building > paddy field > upland in 2006. Decrease of paddy and upland fields reduced 34% and 41% of the capability of agricultural multifunctionality as to environment including flood control, groundwater recharge, and air cooling. Land surface temperature(LST) was derived from Landsat TM thermal infrared band acquired in September of 1994 and 2006 and classified into three grades. The results impplied that green vegetation in agricultural field and forest play an important role to reduce land surface temperature in warm season.