• 제목/요약/키워드: 위성기반

검색결과 2,274건 처리시간 0.03초

A Study on Building Object Change Detection using Spatial Information - Building DB based on Road Name Address - (기구축 공간정보를 활용한 건물객체 변화 탐지 연구 - 도로명주소건물DB 중심으로 -)

  • Lee, Insu;Yeon, Sunghyun;Jeong, Hohyun
    • Journal of Cadastre & Land InformatiX
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    • 제52권1호
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    • pp.105-118
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    • 2022
  • The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

Field Tests for Accuracy of GNSS-RTK Surveys by ISO 17123-8 Standard (ISO 17123-8 표준에 의한 GNSS-RTK 수신기 정확도 평가)

  • Lee, Hungkyu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • 제40권4호
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    • pp.333-342
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    • 2022
  • This paper has theoretically and practically reviewed the ISO (International Standard Organization) 17123-8 standard not only to raise the appropriateness for introducing performance criteria of GNSS (Global Navigation Satellite Systems) surveying equipment based on RTK (Real-Time Kinematic) accuracy but also to derive its proper test procedure by introducing the international standard. Field experiments have been performed to appreciate the GNSS-RTK accuracy of five selected receivers via the full testing procedure of the ISO standard, which statistically compares the so-called experimental standard deviations with themselves and with the reference accuracy. A series of statistical tests have revealed that the RTK accuracy of the same class receivers is not identical, whereas that of the different classes can be equivalent. Such a result evidences the urgency of adopting an RTK accuracy-based specification of the GNSS equipment to the performance standard, currently referenced to the static observation technique only. It is believed that this transition helps the maximization of a new generation of cost-effective receivers to legal surveying applications. Finally, this study proposes the ISO full test, comparing an experimental standard deviation with its referenced value, for a potential field verification procedure of the new performance standard.

Comparison of Two Methodsto Estimate Urban Sensible Heat Flux by Using Satellite Images (위성 영상을 활용한 두 가지 현열 플럭스 추정 방법 간의 비교)

  • Kim, Sang-Hyuck;Lee, Dong-Kun
    • Journal of Environmental Impact Assessment
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    • 제31권1호
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    • pp.63-74
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    • 2022
  • In orderto understand the urban thermal conditions, many studies have been conducted to estimate the thermal fluxes. Currently sensible heat fluxes are estimated through various methods, but studies about comparing the differences between each method are very insufficient. Therefore, this study try to estimate the sensible heat flux of the same area by two representative estimation methods and compare their results to confirm the significance and limitation between methods. As a result of the study, the heat balance methods has a great advantage in terms of resolution but it can not consider the anthropogenic heat flux, so sensible heat flux can be underestimated in urban areas. When estimating based on physical equation, anthropogenic heat flux can be considered and the error is relatively small, it has a limitations in time and space resolutons. The two methods showed the largest difference in industiral areas where anthropogenic heat fluxes are high, with an average of 135 W/m2 and a maximum of 400 W/m2. On the other hand, the green and water have a very small difference with and average of 20 W/m2. The results between two methods show significant differences in urban areas, it is necessary to select a suitable method for each research purpose.

Construction of Sea-Floor Topographic Survey System Based on Echosounder and GNSS (Echosounder와 GNSS 기반 해저지형측량시스템의 구축)

  • Jin-Duk LEE;Yong-Jin CHOI;Jae-Bin LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • 제26권1호
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    • pp.56-68
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    • 2023
  • A system that extracts seabed topographic information by simultaneously and continuously observing the horizontal position and water depth in the sea by combining a single beam echosounder and GNSS was constructed. By applying the developed system to actual measurements of small-scale sea areas, the effectiveness of bathymetry and sea-floor topographic data acquisition using GNSS and echosounder was examined. By using the developed outdoor program DS-NAV and indoor program DS-CAD and applying the tide level data at the time of actual measurement of the target sea area, it was possible to derive bathymetry results based on the datum level i.e. approximate lowest low water level(A.L.L.W). By using the developed outdoor program DS-NAV and indoor program DS-CAD and applying the tide level data at the time of actual measurement of the target sea area, it was possible to derive the results of bathymetric survey based on the datum level. From database built through the actual measurement. it was possible to create 3D model of the sea-floor topography and extract cross-sections. The results of this study are expected to be economically useful for extracting seabed topographical information from small sea areas or in dredging sites for offshore construction.

A study on the analysis of current status of Seonakdong River algae using hyperspectral imaging (초분광영상을 이용한 서낙동강 조류 발생현황 분석에 관한 연구)

  • Kim, Jongmin;Gwon, Yeonghwa;Park, Yelim;Kim, Dongsu;Kwon, Jae Hyun;Kim, Young Do
    • Journal of Korea Water Resources Association
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    • 제55권4호
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    • pp.301-308
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    • 2022
  • Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

DVB-S2-based T4 class common data link performance improvement plan for UAV system application (무인기 체계 적용을 위한 DVB-S2 기반 T4급 공용데이터링크 성능 개선방안)

  • Bae, Jongtae;Baek, Seongho;Oh, Jimyung;Lee, Sangpill;Song, Choongho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제26권12호
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    • pp.1846-1854
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    • 2022
  • The sophistication and diversification of mission equipment for surveillance and reconnaissance is leading to a demand for large-capacity public data links. Overseas, a T4 class(274Mbps) common data link was applied to the Global hwak, a high-altitude unmanned aerial vehicle, and various research and development are being conducted in Korea. In this paper, we propose a structure in which pilot is additionally applied to improve SNR performance while minimizing data transmission rate loss in the DVB-S2 frame structure, which is a european satellite broadcasting standard, for high-capacity transmission of T4 class or higher in the common data link. For the performance evaluation of the proposed structure, the performance of the DVB-S2 was compared and analyzed by simulating the UAV data link channel environment. As a result of simulation, 0.15% of transmission rate loss occurred at T4 class transmission rate compared to DVB-S2 in the proposed structure, but improved SNR reception performance of 0.2~0.3dB was confirmed in the UAV channel environment.

A study on discharge estimation for the event using a deep learning algorithm (딥러닝 알고리즘을 이용한 강우 발생시의 유량 추정에 관한 연구)

  • Song, Chul Min
    • Proceedings of the Korea Water Resources Association Conference
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.246-246
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    • 2021
  • 본 연구는 강우 발생시 유량을 추정하는 것에 목적이 있다. 이를 위해 본 연구는 선행연구의 모형 개발방법론에서 벗어나 딥러닝 알고리즘 중 하나인 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 유량을 추정하였다. 합성곱 신경망은 일반적으로 분류 문제 (classification)을 해결하기 위한 목적으로 개발되었기 때문에 불특정 연속변수인 유량을 모의하기에는 적합하지 않다. 이를 위해 본 연구에서는 합성곱 신경망의 완전 연결층 (Fully connected layer)를 개선하여 연속변수를 모의할 수 있도록 개선하였다. 대부분 합성곱 신경망은 RGB (red, green, blue) 사진 (photograph)을 이용하여 해당 사진이 나타내는 것을 예측하는 목적으로 사용하지만, 본 연구의 경우 일반 RGB 사진을 이용하여 유출량을 예측하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이를 위해 본 연구에서는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는 수문학적 이미지는 입력자료로 활용했다. 합성곱 신경망의 구조는 Convolution Layer와 Pulling Layer가 5회 반복하는 구조로 설정하고, 이후 Flatten Layer, 2개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 다시 1개의 Dense Layer가 이어지는 구조로 설계하였다. 마지막 Dense Layer의 활성화 함수는 분류모형에 이용되는 softmax 또는 sigmoid 함수를 대신하여 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 이와 함께 각 층의 활성화 함수는 정규화 선형함수 (ReLu)를 이용하였으며, 모형의 학습 평가 및 검정을 판단하기 위해 MSE 및 MAE를 사용했다. 또한, 모형평가는 NSE와 RMSE를 이용하였다. 그 결과, 모형의 학습 평가에 대한 MSE는 11.629.8 m3/s에서 118.6 m3/s로, MAE는 25.4 m3/s에서 4.7 m3/s로 감소하였으며, 모형의 검정에 대한 MSE는 1,997.9 m3/s에서 527.9 m3/s로, MAE는 21.5 m3/s에서 9.4 m3/s로 감소한 것으로 나타났다. 또한, 모형평가를 위한 NSE는 0.7, RMSE는 27.0 m3/s로 나타나, 본 연구의 모형은 양호(moderate)한 것으로 판단하였다. 이에, 본 연구를 통해 제시된 방법론에 기반을 두어 CNN 모형 구조의 확장과 수문학적 이미지의 개선 또는 새로운 이미지 개발 등을 추진할 경우 모형의 예측 성능이 향상될 수 있는 여지가 있으며, 원격탐사 분야나, 위성 영상을 이용한 전 지구적 또는 광역 단위의 실시간 유량 모의 분야 등으로의 응용이 가능할 것으로 기대된다.

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Detection of Plastic Greenhouses by Using Deep Learning Model for Aerial Orthoimages (딥러닝 모델을 이용한 항공정사영상의 비닐하우스 탐지)

  • Byunghyun Yoon;Seonkyeong Seong;Jaewan Choi
    • Korean Journal of Remote Sensing
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    • 제39권2호
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    • pp.183-192
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    • 2023
  • The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.

Analysis of the Impact of Surface Reflectance Error Retrieved from 6SV for KOMPSAT-3A according to MODIS AOD Expected Error (MODIS AOD 기대 오차에 따른 6SV 기반 KOMPSAT-3A 채널별 지표반사도 오차 영향 분석)

  • Daeseong Jung;Suyoung Sim;Jongho Woo;Nayeon Kim;Sungwoo Park;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • 제39권6_1호
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    • pp.1517-1522
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    • 2023
  • This study evaluates the impact of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) expected error (EE) on the accuracy of surface reflectance (SR) derived from the KOMPSAT-3A satellite, utilizing the Second Simulation of the Satellite Signal in the Solar Spectrum Vector radiative transfer model. By considering a range of ground-based AOD and the resultant MODIS AOD EE, the research identifies significant influences on SR accuracy, particularly under high solar zenith angles(SZA) and shorter wavelengths. The study's simulations reveal that SR errors increase with shorter wavelengths and higher SZAs, highlighting the necessity for further research to improve atmospheric correction algorithms by incorporating wavelength and SZA considerations. Additionally, the study provides foundational data for better understanding the use of AOD data from other satellites in atmospheric correction processes and contributes to advancing atmospheric correction technologies.

On-orbit Thermal Characteristic for Multilayered High Damping Yoke Structure Based on Superelastic Shape Memory Alloy for Passive Vibration Control of Solar Panels (태양전지판의 수동형 제진을 위한 초탄성 형상기억합금 기반 적층형 고댐핑 요크 구조의 궤도상 열적 특성 분석)

  • Min-Young Son;Jae-Hyeon Park;Bong-Geon Chae;Sung-Woo Park;Hyun-Ung Oh
    • Journal of Aerospace System Engineering
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    • 제18권1호
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    • pp.1-10
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    • 2024
  • In a previous study, a structure of a superplastic yoke consisting of a thin FR4 layer laminated with viscoelastic tape on both sides of a shape memory alloy (SMA) was proposed to reduce residual vibration generated by a deployable solar panel during high motion of a satellite. Damping properties of viscoelastic tapes will change with temperature, which can directly affect vibration reduction performance of the yoke. To check damping performance of the yoke at different temperatures, free damping tests were performed under various temperature conditions to identify the temperature range where the damping performance was maximized. Based on above temperature test results, this paper predicts temperature of the yoke through orbital thermal analysis so that the yoke can have effective damping performance even if it is exposed to an orbital thermal environment. In addition, the thermal design method was described so that the yoke could have optimal vibration reduction performance.