• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.703-715
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• 2011

Forests have been considered one of the most important ecosystems on the earth, affecting the lives and environment. The sustainable forest management requires accurate and timely information of forest and tree parameters. Appropriately interpreted remotely sensed imagery can provide quantitative data for deriving forest information temporally and spatially. Especially, analysis of individual tree detection and crown delineation is significant issue, because individual trees are basic units for forest management. Individual trees in aerial imagery have reflectance characteristics according to tree species, crown shape and hierarchical status. This study suggested a method that identified individual trees and delineated crown boundaries through adopting gradient method algorithm to amplified greenness data using red and green band of aerial imagery. The amplification of specific band value improved possibility of detecting individual trees, and gradient method algorithm was performed to apply to identify individual tree tops. Additionally, tree crown boundaries were explored using spectral intensity pattern created by geometric characteristic of tree crown shape. Finally, accuracy of result derived from this method was evaluated by comparing with the reference data about individual tree location, number and crown boundary acquired by visual interpretation. The accuracy ($\hat{K}$) of suggested method to identify individual trees was 0.89 and adequate window size for delineating crown boundaries was $19{\times}19$ window size (maximum crown size: 9.4m) with accuracy ($\hat{K}$) at 0.80.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.2 s.2
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• pp.83-96
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• 1993

The orthophto map is seen as the form of picture with the uniform reduced scale as the current terrain map. Thus it provides a reasonable feeling of scene and is easy to be interpreted. Furthermore, digital orthophoto is currently used as the basic terrain information data of the Geo-Spatial Information System(GSIS). Therefore, the orhtophoto map has high potential use as a future terrain map. This paper studies the method of producing orthophoto map by using the digital satellite imagery data taken from SPOT satellite of France. The production of orthophoto map requires the process of generating orthophoto imagery with digital elevation model, which process is called digital differential rectification. As the final accuracy of orthophoto map depends on that of digital elevation model, the precise and efficient production method of digital elevation model should be preceded. This study investigated the method of producing digital elevation model directly from SPOT satellite imagery and generated ortho-image by resampling the original SPOT imagery through digital differential rectification. Finally, Simple orthophoto map was made by overlaying the ortho-image and the contour map from digital elevation model.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.83-94
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• 2003

All the urban planning process require land use informations, which should be obtained after through intensive investigation and accurate analysis about the past and current situations and conditions of a city. Until now, the generation of land use informations from remotely sensed imagery has had many limitation because of its spatial resolution. It is now expected that the availability of high resolution satellite imagery whose spatial resolution less than 10m will reduce these limitations. For the purpose of urban growth monitoring we must first establish a urban land use classification nomenclature. In this study, we would like to establish a land use nomenclature for land use classification using remotely sensed data, especially using KOMPSAT EOC imagery.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.5-6
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• 2008

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.35-43
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• 2013

Georeferenced SLI(Street-Level Imagery) services such as Google Streetview, which contain abundant information about the real world, can increase its applicability substantially through conflation with other spatial datasets. For this purpose, we propose a method to improve a correspondence of building region to combine building information more accurately. First, the spatial inconsistency between SLI and vector map is removed by alignment based on road intersections. Then, visible building regions are searched from the spatial inconsistency-removed vector map, and the optimal corresponding building areas are determined in the SLI scene using the visible regions as seed information. The experimental results demonstrated that our method had improved the accuracy of building region correspondence by about 8%. Therefore, our method can be utilized effectively for enhancement of conflation service based on the SLI.

• Ocean and Polar Research
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• v.35 no.4
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• pp.395-405
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• 2013

The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.197-201
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• 2002

The high prices of satellite images prevent researchers from studying remote sensing and most non-professional people doesn't have the simple and easy solutions for the manipulation of satellite images. "Integrated Management of Satellite Imagery Information" project which will be promoted by ETRI (Electronics and Telecommunications Research Institute) will provide the solutions for the above mentioned problems. We will introduce the archiving center in this study. This includes the data construction, storage, management and distribution. We first review the background for this archiving center and introduce the interior and foreign institutes which archive and distribute satellite images. We review our H/W system and S/W system briefly. Finally, the further service of our project will be suggested. Since we will distribute the satellite images (Landsat, SPOT, JERS, Corona, Kompast-1) and will receive Landsat7 ETM+ in 2003 you, this will help the professional work dealing with the satellite image and attract the non-professional people for simple and easy manipulation solutions of satellite image.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.351-358
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• 2017

A new method to decompose the footprints of marine atmosphere boundary layer (MABL) on Synthetic Aperture Radar (SAR) imagery into characteristic spatial scales is proposed. Using two-dimensional Empirical Mode Decomposition (EMD) we obtain three Intrinsic Mode Functions (IMFs), which mainly present longitudinal rolls, three-dimensional cells and atmospheric gravity waves (AGW). The rolls and cells have spatial scales between 3.0 km and 3.8 km and between 5.3 km and 7.1 km, respectively. Based on previous observations and mixed-layer similarity theory, we estimated MABL's depths that vary from 0.95 km to 1.2 km over the rolls and from 3.0 km to 3.8 km over the cells. The AGW has maximum spectrum at 14.3 km wavelength. The method developed in this work can be used to decompose other satellite imageries into individual features through characteristic spatial scales.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.439-448
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• 2022

MV (Moving Vehicle) detection using satellite imagery is important for traffic monitoring and provides a wide range of observations. Specifically, MV detection methods utilizing the time lag in single-pass optical satellite images have been studied for detecting MVs from a single set of images. Because of limitations in detecting MVs outside of roads, most previous studies required road information to limit the moving object to cars on the road. However, it is difficult to obtain road information from inaccessible areas. Therefore, this study proposed a new method for detecting MVs regardless of their locations from single-pass optical satellite images without using additional data. WV-3 (Worldview-3) satellite images were used, and a spatial correlation coefficient map was proposed to detect spatial displacement which denotes MVs across two WV-3 MS images. Finally, evaluation was performed through quantitative metrics and visual inspection. The evaluation results revealed that the proposed method can detect MV movements from the single-pass satellite images. On the contrary, misdetected or undetected MVs due to radiometric differences between the images could be identified by visual inspection. The performance of the proposed method can be improved by minimizing radiometric variations and adding conditions that are robust to radiometric differences between the images.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.295-304
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• 2011

In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.