• 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.

• Journal of the Korean Geographical Society
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• v.50 no.6
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• pp.607-619
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• 2015

It is important to detect trails accurately for finding a proper management. We examined the applicability of KOMPSAT imagery to detect trails and found that it could be an efficient alternative to track trails correctly. We selected K2 and K3 imagery with different spatial resolution. Then, we processed each imagery to get NDVI, SAVI, and SC data. And then, we identified trails by object-based analysis and network analysis. Finally, we evaluated the potential trails with F-measurement and Jaccard coefficient which are based on correctness and completeness. The results show that the applicability is quite different in each case. Among them, especially the SC data with K3 shows the most highest value; correctness of detecting legal trails is 0.44 and completeness of that is 0.54. F-measurement and Jaccard coefficient are 0.49 and 0.32. In general, although there is a limit in detecting trails by using only KOMPSAT imagery, the usefulness of KOMPSAT imagery can be a higher considering its cost efficiency and availability of acquiring periodic data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.405-411
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• 2011

In this study we tried to compare and analyze KOMPSAT-2 NOVI and vegetation coverage(VC) which is investigated by fieldwork. To standardize KOMPSAT-2 NOVI, we adjusted NOVI using reference data which is atmospheric corrected MODIS NDVI. Each vegetation coverage point data was surveyed in field using portable GPS and compared with NDVI of satellite imagery. As a results, there was high level of correlation in vegetation coverage and NOVI.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.170-181
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• 2015

A research on extracting croplands located nearby coastal areas using the spatial information data sets is the important task for managing the agricultural products in coastal areas. This research aims to extract the various croplands(croplands on mountains and croplands on plain areas) located nearby coastal areas using the KOMPSAT-2 imagery, the high-resolution satellite imagery, and the airborne topographic LiDAR(Light Detection And Ranging) data acquired in coastal areas of Uljin, Korea. Firstly, the NDVI(Normalized Difference Vegetation Index) imagery is generated from the KOMPSAT-2 imagery, and the vegetation areas are extracted from the NDVI imagery by using the appropriate threshold. Then, the DSM(Digital Surface Model) and DEM(Digital Elevation Model) are generated from the LiDAR data by using interpolation method, and the CHM(Canopy Height Model) is generated using the differences of the pixel values of the DSM and DEM. Then the plain areas are extracted from the CHM by using the appropriate threshold. The low slope areas are also extracted from the slope map generated using the pixel values of the DEM. Finally, the areas of intersection of the vegetation areas, the plain areas and the low slope areas are extracted with the areas higher than the threshold and they are defined as the croplands located nearby coastal areas. The statistical results show that 85% of the croplands on plain areas and 15% of the croplands on mountains located nearby coastal areas are extracted by using the proposed methodology.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.37-45
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• 2014

This paper reports the geolocation accuracy of KOMPSAT-3 imagery. KOMPSAT-3 was launched successfully on May 18, 2012 and has been released last March. In this paper, we have checked the geolocation accuracy of initial sensor model, precise sensor model and stereo-and multi-image model using four KOMPSAT-3 images covering the same area. The KOMPSAT-3 images without GCPs provided the geolocation accuracy of about 30m and the geocorrected KOMPSAT-3 images provided the geolocation accuracy of about 1m or less. KOMPSAT-3 stereo- and multi-images models yield threedimensional points with sub-meter accuracy in horizontal and vertical direction. Overall, KOMPSAT-3 showed much improved performance in terms of the geolocation accuracy over KOMPSAT-2. KOMPSAT-3 is expected to be able to replace foreign satellite data with sub-meter accuracy level for achieving accurate geometric information.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.68-80
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• 2015

To increase the utilization of the KOrea Multi-Purpose SATellite(KOMPSAT) series imagery being developed pursuant to the national space development program, high quality images with enhanced locational accuracy should be created through standardized post-processing processes. In the present study, using the Value-Added Processing System(VAPS) constructed for the post-processing of KOMPSAT imagery, location correction experiments were conducted using KOMPSAT-2 and -3 imagery from domestic and overseas regions. First, 50 pieces from each of KOMPSAT-2 imagery were selected from South Korean and North Korean regions, and modeling was conducted using GCP Chips. According to the results, the Root Mean Square Errors(RMSE) for South Korea and North Korea were 1.59 pixels and 2.04 pixels, respectively, and the locational accuracy of ortho mosaic imagery using check points were 1.33m(RMSE) and 1.90m(RMSE), respectively. Meanwhile, in the case of overseas regions for which GCP could not be easily obtained, the improvement of locational accuracy could be identified through image corrections using Open Street Map(OSM). The VAPS and reference materials used in the present study are expected to be very useful in constructing a precise image DB for entire global regions.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.486-488
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• 2007

The Grid Reference System, which was firstly used in SPOT series, has been successfully adapted in KOMPSAT-1 and KOMPSAT-2 program, which identifies the geographical location to make image collection plans and manage the database of satellite images. Each Grid Reference System for KOMPSAT-1 and KOMPSAT-2 was designed based on system parameters related to each KOMPSAT-1 and KOMPSAT-2 and this fact leads to the need for the design of the Grid Reference System for KOMPSAT-3 (KGRS-3, hereafter), which reflects system parameters for KOMPSAT-3. The (K, J) coordinate system has been defined as the Grid Reference System for KOMPSAT-3 using heritages from KOMPSAT-1 and KOMPSAT-2 programs. The numbering of K begins with the prime meridian of K = 1 with running eastward on earth increasingly, and the numbering of J uses a value of J = 1000 at all points on the equator and begin with running northward increasingly. The Grid Reference System for KOMPSAT-3 is to be implemented in Ground Segment of KOMPSAT-3 system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.177-182
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• 2004

This study presents the application of aerial photographs and KOMPSAT-1 Electro-Optical Camera(EOC) imagery in detecting the change of an urban area that has been rapidly growing. For the study, we used multi-time images which were acquired by two different sensors. For all of the images, the coordinate reference system and scale were first made identical through the 1st and 2nd geometric corrections and then image resampling were carried out to spatial resolution of 7m to detect changes under the same conditions. The Image Differencing was employed as a change detection technique. It was confirmed to be able to detect the changes of terrestrial surface like building, structure and road features from aerial photos and KOMPSAT EOC images with single band. The changes could be detected to some extent with the images acquired from different kinds of sensors as well as the same kinds of sensors.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.21-27
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• 2013

Recently, It is increasing that importance of systematic management by carbon sinks in forest resources. Especially, in terms of social, Forest resources in urban areas are important role as well as carbon sinks, and improvement of the natural environment of the city. In this study, through ANOVA analysis that a total of nine different vegetation index from rearranged NIR band of images to Forest tree species classified in urban areas using high-resolution aerial images and satellite images of KOMPSAT-2. And various vegetation indices such as NDVI are divided a species by forest units through statistical analysis. Also, separated species are compared to forest type map by the Forest Service. As a result, it is built as basis for vegetation management in urban areas.