• Title/Summary/Keyword: 공간정확도

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Land Cover Classification Using Sematic Image Segmentation with Deep Learning (딥러닝 기반의 영상분할을 이용한 토지피복분류)

  • Lee, Seonghyeok;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.35 no.2
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    • pp.279-288
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    • 2019
  • We evaluated the land cover classification performance of SegNet, which features semantic segmentation of aerial imagery. We selected four semantic classes, i.e., urban, farmland, forest, and water areas, and created 2,000 datasets using aerial images and land cover maps. The datasets were divided at a 8:2 ratio into training (1,600) and validation datasets (400); we evaluated validation accuracy after tuning the hyperparameters. SegNet performance was optimal at a batch size of five with 100,000 iterations. When 200 test datasets were subjected to semantic segmentation using the trained SegNet model, the accuracies were farmland 87.89%, forest 87.18%, water 83.66%, and urban regions 82.67%; the overall accuracy was 85.48%. Thus, deep learning-based semantic segmentation can be used to classify land cover.

Image Retrieval scheme using Spatial Similarity and XML (공간유사도와 XML을 이용한 이미지 검색기법)

  • 이수철;황인준
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05d
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    • pp.1063-1068
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    • 2002
  • 공간 관계는 이미지나 멀티미디어 데이터를 검색하기 위한 시스템에서 오브젝트들을 표현하는데 중요한 요소이다. 본 논문에서는 기존의 검색 방식과 다르게 이미지에 있는 여러 오브젝트들간의 공간 관계와 각 오브젝트들이 가지고 있는 특징을 이용한 새로운 방식의 이미지 데이터 검색기법을 제안한다. 이것은 질의와 데이터베이스 내에 있는 이미지들간의 유사성을 효율적으로 계산하는데 유용하다. 또한 각 오브젝트의 공간정보와 특징들에 대한 정보들이 XML형태로 주석 처리되어 있기 때문에 이전 검색 기법보다 정확도가 높다. 마지막으로 제안한 검색기법을 이용한 이미지 검색 시스템을 구현하여, 실제 데이터를 검색함으로써 성능을 평가하였다.

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중파 안테나를 이용한 R-Mode 공간파 저감 방안에 관한 연구

  • 정해상;전중성;국승기
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2021.11a
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    • pp.8-9
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    • 2021
  • 중파대역의 전파는 지표면을 따라 전파되는 지표파와 전리층에 반사되어 전파되는 공간파가 있다. 중파 R-Mode는 TOA추정을 통해 위치를 결정한다. 전리층에 반사되는 공간파를 수신할 경우 TOA 오차는 커질 수밖에 없다. 측위 정확도 향상을 위해 안테나 기반 중파 R-Mode의 수신성능을 향상하는

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Implementation of Facility Movement Recognition Accuracy Analysis and Utilization Service using Drone Image (드론 영상 활용 시설물 이동 인식 정확도 분석 및 활용 서비스 구현)

  • Kim, Gwang-Seok;Oh, Ah-Ra;Choi, Yun-Soo
    • Journal of the Korean Institute of Gas
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    • v.25 no.5
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    • pp.88-96
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    • 2021
  • Advanced Internet of Things (IoT) technology is being used in various ways for the safety of the energy industry. At the center of safety measures, drones play various roles on behalf of humans. Drones are playing a role in reaching places that are difficult to reach due to large-scale facilities and space restrictions that are difficult for humans to inspect. In this study, the accuracy and completeness of movement of dangerous facilities were tested using drone images, and it was confirmed that the movement recognition accuracy was 100%, the average data analysis accuracy was 95.8699%, and the average completeness was 100%. Based on the experimental results, a future-oriented facility risk analysis system combined with ICT technology was implemented and presented. Additional experiments with diversified conditions are required in the future, and ICT convergence analysis system implementation is required.

Impact Analysis of Deep Learning Super-resolution Technology for Improving the Accuracy of Ship Detection Based on Optical Satellite Imagery (광학 위성 영상 기반 선박탐지의 정확도 개선을 위한 딥러닝 초해상화 기술의 영향 분석)

  • Park, Seongwook;Kim, Yeongho;Kim, Minsik
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.559-570
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    • 2022
  • When a satellite image has low spatial resolution, it is difficult to detect small objects. In this research, we aim to check the effect of super resolution on object detection. Super resolution is a software method that increases the resolution of an image. Unpaired super resolution network is used to improve Sentinel-2's spatial resolution from 10 m to 3.2 m. Faster-RCNN, RetinaNet, FCOS, and S2ANet were used to detect vessels in the Sentinel-2 images. We experimented the change in vessel detection performance when super resolution is applied. As a result, the Average Precision (AP) improved by at least 12.3% and up to 33.3% in the ship detection models trained with the super-resolution image. False positive and false negative cases also decreased. This implies that super resolution can be an important pre-processing step in object detection, and it is expected to greatly contribute to improving the accuracy of other image-based deep learning technologies along with object detection.

Development of radar rainfall estimation technique considering the elevation effect for hydropower dam operation (발전용 댐 운영을 위한 고도영향을 고려한 레이더 정량적 강우 추정 기술 개발)

  • Yoon, Seong Sim;Shin, Hongjoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.69-69
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    • 2020
  • 수자원 확보 및 홍수 대응을 위해서는 정확한 강우정보를 바탕으로 한 효율적인 댐 운영이 필요하다. 그러나 댐이 위치한 지역은 산지지역으로 강우관측소 밀도의 지역적인 편차로 인해 지상 관측 강우자료 활용 시 강우 정보의 정확도 확보에 한계가 있다. 또한, 강우의 시·공간적 변동성 심화로 기존의 강우계만으로는 정확한 강우량 추정이 어려워 이를 홍수기 댐 운영의 기초정보로 활용 시 합리적 댐 운영에 한계가 있다. 댐 운영 시 강우 관측정보는 댐 유입량 산정을 위한 강우-유출해석 모형의 입력 자료로 활용되기 때문에 강우량 자료의 정확도 확보가 무엇보다 중요하나, 현재 댐 운영에 필요한 강우 관측정보로는 지상우량계 자료가 주로 활용되고 있어 이를 보완하고자 일반적으로 강우의 공간분포를 관측할 수 있는 고해상도 레이더 강우 정보가 활용되고 있다. 본 연구에서는 전력생산(발전) 및 용수공급, 홍수조절 기능을 고려하여 운영되고 있는 한국수력원자력(주)의 수력발전용댐(팔당, 의암, 춘천, 화천, 청평, 도암, 괴산, 섬진강, 보성강댐)에 활용할 수 있도록 환경부 합성레이더 자료를 바탕으로 레이더 강우정보를 산출하고, 레이더 강우의 정확도 향상을 위해 고도영향을 고려한 레이더 강우 보정기술을 개발하고자 한다. 적용한 기법은 강우장의 공간적 구조는 레이더 자료로 획득하고, 강우량은 강우계 관측정보를 합성하는 조건부합성기법을 기본으로 하며, 고도 영향을 고려할 수 있도록 강우분포장 생성 시 주변수를 강우로, 이차변수를 고도로 정의한 표준화된 정규공동크리깅을 활용한 기법이다. 본 연구를 통해 산출된 레이더 강우를 댐 유입 측면에서 기존의 보정기법과 비교하여 정확도를 검토하고, 댐 운영에 활용할 수 있도록 유역평균강우량 정보를 산출하고자 한다.

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LANDSAT remotely sensed data's Classification accuracy improvement Using Standardized Principal Components Analysis (표준화 주성분 분석(Standardized PCA)을 이용한 LANDSAT 위성자료 분류 (Classification)의 정확도 향상)

  • 장훈;윤완석
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.151-156
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    • 2003
  • 본 연구에서는 2000년 LANDSAT ETM+ 수도권 영상을 이용하여 도시지역 10개소, 식생지역 10개소를 선정해서 각각에 대해 표준화 주성분 분석을 적용하여 두 지역간의 고유벡터 매트릭스를 비교ㆍ분석해보았다. 도시 지역과 식생 지역각각에 대해 총 6개의 주성분이 생성되었으며 PC-2와 고유벡터 부호가 변한 밴드(band2, band7)를 RGB로 조합하여 수원지역을 대상으로 분류(Classification)한 결과의 정확도를 분광서명 분별 분석(Signature Separability Analysis)통해 얻은 밴드조합(band1, band3, band5) 영상의 분류결과와 비교해 보았다. 수원지역 2000년 IKONOS 영상의 다중분광 밴드(4×4m)와 전정색 밴드(1x1m)를 융합한 영상이 분류 정확도를 판단하는 기준으로 사용되었다. 비교결과 분류 전체 정확도는 각각 87.7%, 77.29% Khat 지수는 0.83, 0.68로 나타나 PC-2, 밴드2, 밴드7을 이용했을 때 분류 정확도를 높일 수 있다는 결과를 얻었다.

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A Study on Precision of 3D Spatial Model of a Highly Dense Urban Area based on Drone Images (드론영상 기반 고밀 도심지의 3차원 공간모형의 정밀도에 관한 연구)

  • Choi, Yeon Woo;Yoon, Hye Won;Choo, Mi Jin;Yoon, Dong Keun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.2
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    • pp.69-77
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    • 2022
  • The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

An Analysis of Vertical Position Accuracy for the Three-Dimensional Spatial Data Object Utilizing the Public Information (공공데이터를 활용한 3차원 공간정보 객체의 수직위치 정확도 분석)

  • Kim, Jeong Taek;Yi, Su Hyun;Kim, Jong Il;Bae, Sang Won
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.3
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    • pp.137-143
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    • 2014
  • Recently, as new paradigm for government operation called government 3.0, government is actively operating policy opening and sharing public data. In addition, the Ministry of Land are operating an open platform integrated map service (the VWorld) which provides a variety of video contents such as the country's national spatial information, traffic information and three-dimensional building for the public. According to W3C Foundation's Open Data Status Report(2013), our country has the evaluated results that the part of the government's policy support and planning is good while the part of the data management is vulnerable. So our country needs the quality improvement for the data management. In addition, a digital aerial photograph image data is required to be up-to-date for the three-dimensional spatial object data. In this paper, we present the method for enhancement of the accuracy of vertical position and for maintainment of up-to-date vertical position. Our methods evaluate the data quality and analyze the cause of error of measurement utilizing the national standard quality assessment method. The result of research shows that the accuracy of vertical position is improved if the height of the building captain is adjusted by the quality assessment values and a three-dimensional model has up-to-date data if reconstruction and extension information of construction register is utilized.

A Study on the Improvement of UAV based 3D Point Cloud Spatial Object Location Accuracy using Road Information (도로정보를 활용한 UAV 기반 3D 포인트 클라우드 공간객체의 위치정확도 향상 방안)

  • Lee, Jaehee;Kang, Jihun;Lee, Sewon
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.705-714
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    • 2019
  • Precision positioning is necessary for various use of high-resolution UAV images. Basically, GCP is used for this purpose, but in case of emergency situations or difficulty in selecting GCPs, the data shall be obtained without GCPs. This study proposed a method of improving positional accuracy for x, y coordinate of UAV based 3 dimensional point cloud data generated without GCPs. Road vector file by the public data (Open Data Portal) was used as reference data for improving location accuracy. The geometric correction of the 2 dimensional ortho-mosaic image was first performed and the transform matrix produced in this process was adopted to apply to the 3 dimensional point cloud data. The straight distance difference of 34.54 m before the correction was reduced to 1.21 m after the correction. By confirming that it is possible to improve the location accuracy of UAV images acquired without GCPs, it is expected to expand the scope of use of 3 dimensional spatial objects generated from point cloud by enabling connection and compatibility with other spatial information data.