• Title/Summary/Keyword: map accuracy

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A Study on Object Based Image Analysis Methods for Land Use and Land Cover Classification in Agricultural Areas (변화지역 탐지를 위한 시계열 KOMPSAT-2 다중분광 영상의 MAD 기반 상대복사 보정에 관한 연구)

  • Yeon, Jong-Min;Kim, Hyun-Ok;Yoon, Bo-Yeol
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.3
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    • pp.66-80
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    • 2012
  • It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

Fully Automated Generation of Cloud-free Imagery Using Landsat-8 (Landsat-8을 이용한 자동화된 구름 제거 영상 생성)

  • Kim, Byeong Hee;Kim, Yong;Han, You Kyung;Choi, Won Seok;Kim, Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.2
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    • pp.133-142
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    • 2014
  • Landsat is one of the popular satellites for observing land surface that is used in various areas including monitoring, detecting and classifying changes in land surface. However, shades, which cloud itself and its shadow, interrupted often clear observation and analysis of ground surface. For this reason, the process of removing shades and restoring original ground surfaces are critical for geospatial users. This study is planned to recommend a methodology for more accurate and clear images of Landsat-8 sensor, which provided two additional bands of costal/aerosol and cirrus. In fact, those bands are known as functioned effectively in detecting and restoring shades. Otsu's thresholding technique to detect clouds, we replaced those detective shades by using experimental and reference images. In accurate assessment, the overall accuracy and kappa coefficients were about 85% and 0.7128, respectively. This indicates that the proposed technique is effective for recovering the original land surface.

Automatic Extraction of Training Dataset Using Expectation Maximization Algorithm - for Automatic Supervised Classification of Road Networks (기대최대화 알고리즘을 활용한 도로노면 training 자료 자동추출에 관한 연구 - 감독분류를 통한 도로 네트워크의 자동추출을 위하여)

  • Han, You-Kyung;Choi, Jae-Wan;Lee, Jae-Bin;Yu, Ki-Yun;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.2
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    • pp.289-297
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    • 2009
  • In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

Orthophoto and DEM Generation Using Low Specification UAV Images from Different Altitudes (고도가 다른 저사양 UAV 영상을 이용한 정사영상 및 DEM 제작)

  • Lee, Ki Rim;Lee, Won Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.5
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    • pp.535-544
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    • 2016
  • Even though existing methods for orthophoto production using expensive aircraft are effective in large areas, they are drawbacks when dealing with renew quickly according to geographic features. But, as UAV(Unmanned Aerial Vehicle) technology has advanced rapidly, and also by loading sensors such as GPS and IMU, they are evaluates that these UAV and sensor technology can substitute expensive traditional aerial photogrammetry. Orthophoto production by using UAV has advantages that spatial information of small area can be updated quickly. But in the case of existing researches, images of same altitude are used in orthophoto generation, they are drawbacks about repetition of data and renewal of data. In this study, we targeted about small slope area, and by using low-end UAV, generated orthophoto and DEM(Digital Elevation Model) through different altitudinal images. The RMSE of the check points is σh = 0.023m on a horizontal plane and σv = 0.049m on a vertical plane. This maximum value and mean RMSE are in accordance with the working rule agreement for the aerial photogrammetry of the National Geographic Information Institute(NGII) on a 1/500 scale digital map. This paper suggests that generate orthophoto of high accuracy using a different altitude images. Reducing the repetition of data through images of different altitude and provide the informations about the spatial information quickly.

A Comparative Study on Power Tool Manufacturers' Products Spec. and Design Development Features - By the Case Study on BOSCH, BLACK&DECKER and KEYANG Electrics- (전동공구 회사의 제품사양별 디자인개발특성 비교연구 -보슈(BOSCH), 블랙앤데커(BLACK&DECKER), 계양전기 사례를 중심으로 -)

  • 채승진
    • Archives of design research
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    • v.17 no.1
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    • pp.383-392
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    • 2004
  • The power tools is the product using working power generated by electric motor. Many companies are manufacturing numerous devices. Main features of tools are included various assembled products, small, light and solid and durable enough to match several standards. Fundamental requirements for the product is excellent performance and convenience for use. The quality of them depends on the equipped motor'(s) capability, accuracy of gear and endurance against worn-out. By adapting the state-of-the-art parts, they could be used in the place from home to heavy industry broadly. They can be classified electronic drills, grinders, saws and sanders families for the household appliances. For industrial tools, bore drill, grinder, polisher, and driver drill are classified as special and high priced group. This study presents the strategy of power tool development of BOSCH, BLACK&DECKER and KEYANG. Their products were analyzed in terms of product line and product mix concept. Then they are examined by design elements, such as color, shape and material for housing. As an analysis method, the image scale parameter and criteria were applied to each company's product.

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Automatic Extraction of Roof Components from LiDAR Data Based on Octree Segmentation (LiDAR 데이터를 이용한 옥트리 분할 기반의 지붕요소 자동추출)

  • Song, Nak-Hyeon;Cho, Hong-Beom;Cho, Woo-Sug;Shin, Sung-Woong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.4
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    • pp.327-336
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    • 2007
  • The 3D building modeling is one of crucial components in building 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes by stereoplotter compiler, which indeed take great amount of time and efforts. In addition, some automatic methods that were proposed in research papers and experimental trials have limitations of describing the details of buildings with lack of geometric accuracy. It is essential in automatic fashion that the boundary and shape of buildings should be drawn effortlessly by a sophisticated algorithm. In recent years, airborne LiDAR data representing earth surface in 3D has been utilized in many different fields. However, it is still in technical difficulties for clean and correct boundary extraction without human intervention. The usage of airborne LiDAR data will be much feasible to reconstruct the roof tops of buildings whose boundary lines could be taken out from existing digital maps. The paper proposed a method to reconstruct the roof tops of buildings using airborne LiDAR data with building boundary lines from digital map. The primary process is to perform octree-based segmentation to airborne LiDAR data recursively in 3D space till there are no more airborne LiDAR points to be segmented. Once the octree-based segmentation has been completed, each segmented patch is thereafter merged based on geometric spatial characteristics. The experimental results showed that the proposed method were capable of extracting various building roof components such as plane, gable, polyhedric and curved surface.

Strategies of Updating Road Framework Data by a Vehicle-based Kinematic Survey (차량이동측량에 의한 도로 기본지리정보 갱신방안에 관한 연구)

  • Yoon, ha-Su;Lee, Jin-Soo;Seo, Chang-Wan;Choi, Yun-Soo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.4
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    • pp.355-363
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    • 2007
  • The purpose of this study is to maximize the use of framework data by a method for updating road framework data using a economical, rapid, and accurate Vehicle-based kinematic survey to get the latest road data among "transportation framework data" which was built in 2003. We collected data using a Vehicle-based kinematic survey with DGPS (Differential Global Positioning System) in Daejeon and Pyeongtaek city and verified the accuracy of line and point features between surveying and previous results. The result showed that Daejeon city which is located near GPS CORS (Continuously Operating Reference Station)s and receive a signal well had lower errors than 1/5,000 digital base map, and Pyeongtaek city which is located far from the stations and receive a signal badly had errors beyond the limits. The study showed that postprocessing method or Total Station surveying should be used where signals cannot be detected well after analyzing a receiving rate from GPS CORSs, the stations of other organizations should be shared, and further studies are needed.

Extraction of Water Depth in Coastal Area Using EO-1 Hyperion Imagery (EO-1 Hyperion 영상을 이용한 연안해역의 수심 추출)

  • Seo, Dong-Ju;Kim, Jin-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.716-723
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    • 2008
  • With rapid development of science and technology and recent widening of mankind's range of activities, development of coastal waters and the environment have emerged as global issues. In relation to this, to allow more extensive analyses, the use of satellite images has been on the increase. This study aims at utilizing hyperspectral satellite images in determining the depth of coastal waters more efficiently. For this purpose, a partial image of the research subject was first extracted from an EO-1 Hyperion satellite image, and atmospheric and geometric corrections were made. Minimum noise fraction (MNF) transformation was then performed to compress the bands, and the band most suitable for analyzing the characteristics of the water body was selected. Within the chosen band, the diffuse attenuation coefficient Kd was determined. By deciding the end-member of pixels with pure spectral properties and conducting mapping based on the linear spectral unmixing method, the depth of water at the coastal area in question was ultimately determined. The research findings showed the calculated depth of water differed by an average of 1.2 m from that given on the digital sea map; the errors grew larger when the water to be measured was deeper. If accuracy in atmospheric correction, end-member determination, and Kd calculation is enhanced in the future, it will likely be possible to determine water depths more economically and efficiently.

Fire Severity Mapping Using a Single Post-Fire Landsat 7 ETM+ Imagery (단일 시기의 Landsat 7 ETM+ 영상을 이용한 산불피해지도 작성)

  • 원강영;임정호
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.85-97
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    • 2001
  • The KT(Kauth-Thomas) and IHS(Intensity-Hue-Saturation) transformation techniques were introduced and compared to investigate fire-scarred areas with single post-fire Landsat 7 ETM+ image. This study consists of two parts. First, using only geometrically corrected imagery, it was examined whether or not the different level of fire-damaged areas could be detected by simple slicing method within the image enhanced by the IHS transform. As a result, since the spectral distribution of each class on each IHS component was overlaid, the simple slicing method did not seem appropriate for the delineation of the areas of the different level of fire severity. Second, the image rectified by both radiometrically and topographically was enhanced by the KT transformation and the IHS transformation, respectively. Then, the images were classified by the maximum likelihood method. The cross-validation was performed for the compensation of relatively small set of ground truth data. The results showed that KT transformation produced better accuracy than IHS transformation. In addition, the KT feature spaces and the spectral distribution of IHS components were analyzed on the graph. This study has shown that, as for the detection of the different level of fire severity, the KT transformation reflects the ground physical conditions better than the IHS transformation.

Evaluation of Utilization of Satellite Remote Sensing Data for Drought Monitoring (가뭄 모니터링을 위한 인공위성 원격탐사자료의 활용 가능성 평가)

  • Won, Jeongeun;Son, Youn-Suk;Lee, Sangho;Kang, Limseok;Kim, Sangdan
    • Korean Journal of Remote Sensing
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    • v.37 no.6_2
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    • pp.1803-1818
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    • 2021
  • As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.