• Proceedings of the KSRS Conference
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• v.2
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• pp.631-634
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• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.583-590
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• 2012

This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.121-130
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• 2011

This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.

• 한국지형공간정보학회:학술대회논문집
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• 2002.03a
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• pp.156-161
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• 2002

자연공원의 체계적인 관리를 위해서는 효율적인 자료수집과 처리, 그리고 합리적인 분석과정이 필요하며, 이러한 관점에서 지형공간정보체계와 위성원격탐사를 이용하는 공원관리 및 관광안내시스템의 개발이 요구되는 시점이다. 본 연구에서는 금오산 도립공원구역을 사례연구지역으로 GSIS(Geo-Spatial Information System)기법을 도입하여 수치지형도, 주제도, 위성영상 등으로부터 도형자료 및 비도형자료를 수집 처리하였다. DEM 생성을 통하여 얻어진 경사도, 사면방향, 지형단면, 지질 분석 등 주제별 지형분석을 행하였다. Landsat TM 위성자료로부터 토지피복분류와 NDVI 식생활력도를 추출하였고, 이 자료들로부터 GSIS 데이터베이스를 구축하였다. 또한 대상지역을 포함하는 Im 해상도의 IKONOS 위성자료를 처리하여 영상지도를 작성하고 DEM과 중합하여 3D 시각화를 구현하였다. 위성영상지도 및 3차원 경관도상에 주요 등산로 벡터자료를 중첩하여 표현하고, 5개 루트의 주요 등산로를 따라 3D 경관 및 문화재, 관리시설 등을 포함하는 동영상 파일을 제작하였다. 본 연구의 결과는 개발과 보존의 중도를 취하는 자연공원의 적정 토지이용을 위한 사전평가 자료 및 Web 기반 관광안내시스템을 구축하기 위한 기본데이터로 활용될 수 있을 것이다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1464-1466
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• 2003

classification of the satellite images provides information about land cover and/or land use. Quality of the classification result depends mainly on the spatial and spectral resolutions of the images. In this study, image fusion in terms of resolution merging, and band integration with multi-source of the satellite images; Landsat ETM+ and Ikonos were carried out to improve classification. Resolution merging and band integration could generate imagery of high resolution with more spectral bands. Precise image co-registration is required to remove geometric distortion between different sources of images. Combination of unsupervised and supervised classification of the fused imagery was implemented to improve classification. 3D display of the results was possible by combining DEM with the classification result so that interpretability could be improved.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.2 s.20
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• pp.39-47
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• 2002

For the purpose of data construction for the systematic management and sight-seeing guidance of the natural park, the Kumoh Mt. Province Park was selected as a pilot area. Digital topographic maps, thematic maps and satellite imagery covering the object area were processed and then landform analysis for elevation, slope, aspect and so on was conducted through DEM generation, and the landcover map and NDVI maP were extracted from Landsat TM data. The database was then constructed with these spatial data for GSIS. The image map was generated from IKONOS satellite data, which cover the pilot area data, with one meter resolution and also 3D visualization which was overlaid with main paths up a mountain were conducted. And the moving image files were produced along main paths up including main natural spectacular sights, cultural assets and management facilities. It is expected that the research result can be utilized as the fundamental data for re-assessing suitable land use and constructing Web-based guidance system.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Proceedings of the KSRS Conference
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• v.1
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• pp.426-429
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• 2006

Flood caused by Typhoon and severe rain during summer is the most destructive natural disasters in Korea. Almost every year flood has resulted in a big lost of national infrastructure and loss of civilian lives. It usually takes time and great efforts to estimate the flood-related damages. Government also has pursued proper standard and tool for using state-of-art technologies. High resolution satellite imagery is one of the most promising sources of ground truth information since it provides detailed and current ground information such as building, road, and bare ground. Once high resolution imagery is utilized, it can greatly reduce the amount of field work and cost for flood related damage assessment. The classification of high resolution image is pre-required step to be utilized for the damage assessment. The classified image combined with additional data such as DEM and DSM can help to estimate the flooded areas per each classified land use. This paper applied object-oriented classification scheme to interpret an image not based in a single pixel but in meaningful image objects and their mutual relations. When comparing it with other classification algorithms, object-oriented classification was very effective and accurate. In this paper, IKONOS image is used, but similar level of high resolution Korean KOMPSAT series can be investigated once they are available.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.749-757
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• 2008

Recently, flood damages have increased with heavy rainfall and typhoon influences, and it requires that visualization information to the flood inundation area of downstream in dam discharge. This study developed 3D GIS system that can visualize flood inundation area for Namgang Dam downstream. First, DEMs extracted from NGIS digital maps and IKONOS satellite images were optimized to mount in iWorld engine using TextureMaker and HeightMaker modules. And flood inundation area of downstream could be efficiently extracted with real-time flooding water level using Coordinate Operation System for Flood control In Multi-reservoir (COSFIM) and Flood Wave routing model (FLDWAV) in river cross section. This visualization information of flood inundation area can be used to examine flood weakness district needed in real time Dam operation and be applied to establish the rapid flood disaster countermeasures efficiently.

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.319-327
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• 2012

In this paper, we introduce a newly developed photogrammetric software for automatic generation of high quality geo-products and its performance assessment carried out using various satellite images. Our newly developed software provides the latest techniques of an optimized sensor modelling, ortho-image generation and automated Digital Elevation Model (DEM) generation for diverse remote sensing images. In particular, images from dual- and multi-sensor images can be integrated for 3D mapping. This can be a novel innovation toward a wider applicability of remote sensing data, since 3D mapping has been limited within only single-sensor so far. We used Kompsat-2, Ikonos, QuickBird, Spot-5 high resolution satellite images to test an accuracy of 3D points and ortho-image generated by the software. Outputs were assessed by comparing reliable reference data. From various sensor combinations 3D mapping were implemented and their accuracy was evaluated using independent check points. Model accuracy of 1~2 pixels or better was achieved regardless of sensor combination type. The high resolution ortho-image results are consistent with the reference map on a scale of 1:5,000 after being rectified by the software and an accuracy of 1~2 pixels could be achieved through quantitative assessment. The developed software offers efficient critical geo-processing modules of various remote sensing images and it is expected that the software can be widely used to meet the demand on the high-quality geo products.