• Title/Summary/Keyword: Image Sensing

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Vegetation Water Status Monitoring around China and Mongolia Desert using Satellite Data (위성자료를 이용한 중국과 몽골 사막주변의 식생수분상태 모니터링)

  • Lee, Ga-Lam;Kim, Young-Seup;Han, Kyoung-Soo;Lee, Chang-Suk;Yeom, Jong-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.4
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    • pp.94-100
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    • 2008
  • Recently, global warming for climate system is a crucial issue over the world and it brings about severe climate change, abnormal temperature, a downpour, a drought, and so on. Especially, a drought over the earth surface accelerates desertification which has been advanced over the several years mainly originated from a climatic change. The objective of this study is to detect variation of vegetation water condition around China and Mongolia desert by using satellite data having advantage in observing surface biological system. In this study, we use SPOT/VEGETATION satellite image to calculate NDWI (Normalized Difference Water Index) around study area desert for monitoring of status of vegetation characteristics. The vegetation water status index from remotely sensing data is related to desertification since dry vegetation is apt to desertify. We can infer vegetation water status using NDWI acquired by NIR (Near infrared) and SWIR (Short wave infrared) bands from SPOT/VGT. The consequence is that NDWI decreased around desert from 1999 to 2006. The areas that NDWI was decreased are located in the northeast of Mongolian Gobi desert and the southeast of China Taklamakan desert.

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Geophysical study on the summit of the Dokdo volcano (독도화산체 정상부에 대한 지구물리학적 조사 연구)

  • Kim, Chang-Hwan;Jeong, Eui-Young;Park, Chan-Hong;Jou, Hyeong-Tae;Lee, Seung-Hoon;Kim, Ho
    • 한국지구물리탐사학회:학술대회논문집
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    • 2008.10a
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    • pp.207-212
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    • 2008
  • Bathymetry, side scan sonar, and magnetic survey data for the summit area of Dokdo obtained by Korea Ocean Research & Development Institute in 1999, 2004, and 2007 were analyzed to investigate the geophysical characteristics of the summit. Bathymetry and topographic data for the summit of Dokdo show uneven seabed and irregular undulations from costal line to -90 m in water depth, indicating the effects of partial erosions and taluses. The stepped slope in the bathymetry is supposed to be a coastal terrace suggesting repetition of transgressions and regressions in the Quaternary. The bathymetry and the side scan sonar data show a small crater, assumed to be formed by post volcanisms, at depth of $-100\;{\sim}\;-120\;m$ in the northeastern and the northwestern parts of the survey area. Except some areas with shallow sand sedimentary deposits, there are rocky seafloor and lack of sediments in the side scan sonar images of the survey area, dominantly. The analytic signal of the magnetic anomaly coincides with other geophysical results regarding to the location of the residual crater. The geophysical constraints of the summit of Dokdo propose that the islets and the rocky seabed elongated northeastward and northwestward from the islets might be the southern crater of the Dokdo volcano.

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Inflow Estimation into Chungju Reservoir Using RADAR Forecasted Precipitation Data and ANFIS (RADAR 강우예측자료와 ANFIS를 이용한 충주댐 유입량 예측)

  • Choi, Changwon;Yi, Jaeeung
    • Journal of Korea Water Resources Association
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    • v.46 no.8
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    • pp.857-871
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    • 2013
  • The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.

Research for Calibration and Correction of Multi-Spectral Aerial Photographing System(PKNU 3) (다중분광 항공촬영 시스템(PKNU 3) 검정 및 보정에 관한 연구)

  • Lee, Eun Kyung;Choi, Chul Uong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.4
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    • pp.143-154
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    • 2004
  • The researchers, who seek geological and environmental information, depend on the remote sensing and aerial photographic datum from various commercial satellites and aircraft. However, the adverse weather conditions and the expensive equipment can restrict that the researcher can collect their data anywhere and any time. To allow for better flexibility, we have developed a compact, a multi-spectral automatic Aerial photographic system(PKNU 2). This system's Multi-spectral camera can catch the visible(RGB) and infrared(NIR) bands($3032{\times}2008$ pixels) image. Visible and infrared bands images were obtained from each camera respectively and produced Color-infrared composite images to be analyzed in the purpose of the environment monitor but that was not very good data. Moreover, it has a demerit that the stereoscopic overlap area is not satisfied with 60% due to the 12s storage time of each data, while it was possible that PKNU 2 system photographed photos of great capacity. Therefore, we have been developing the advanced PKNU 2(PKNU 3) that consists of color-infrared spectral camera can photograph the visible and near infrared bands data using one sensor at once, thermal infrared camera, two of 40 G computers to store images, and MPEG board to compress and transfer data to the computer at the real time and can attach and detach itself to a helicopter. Verification and calibration of each sensor(REDLAKE MS 4000, Raytheon IRPro) were conducted before we took the aerial photographs for obtaining more valuable data. Corrections for the spectral characteristics and radial lens distortions of sensor were carried out.

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Multi-Buffer Zone Analysis of Geo-Based Integrated Thematic Mappable Information by Using GIS (GIS를 이용한 지질자료 기반 통합 주제정보의 다중 버퍼 영역분석)

  • 이기원;박노욱;권병두
    • Spatial Information Research
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    • v.7 no.2
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    • pp.159-173
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    • 1999
  • GIS has been regarded as one of important tools or methodologies for various geoscience applications. Recently, spatial data integration schemes for site-specific or field-specific thematic mapping are newly developed and utilized. However, these kinds of approaches are somewhat insufficient quantitative assessment of integrated layers towards known targets in-detailed . Moreover, GIS analysis scheme is rarely extended to scientific approaches. In this study, simple approach of Multi-Buffer Zone Analysis , related to GIS analystical aspect, is addressed and an actual application for predicting or favorable mapping of mineral occurrences, one of GIS-based geoscientific approaches, is performed, As for geo-processing in GIS itself, this scheme can be regarded as extension or adaptiation of cell-based buffering or proximity analysis to geoscientific data interpretation. This study is based on rationale that surface geological pattern around primitives such as a point, a line, or a polygon in GIS, representing significant geological features, can be efficiently utilized to delineate complex geological behaviors or events, especially handling multiple dta sets originated from multiple sources such as airborne geophysical/radiometric exploration, field survey, and even a classified image of remote sensing. Conclusively, this methodology associated wit GIS is though to be helpful to analyze the spatial pattern of multiple data, pointing given sources, and is expected to effectively utilize for exploratory analysis of cell-based resultant layer integrated with complex or different data sources.

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Analyzing Characteristics of Forest Damage within the Geum-buk Mountain Range (금북정맥의 산림훼손 특성 분석)

  • Jang, Gab-Sue;Jeon, Seong-Woo;Kim, Sang-Soo
    • Journal of the Korean Institute of Landscape Architecture
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    • v.36 no.5
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    • pp.55-63
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    • 2008
  • The characteristics of forest damage in the Geum-buk Mountains were analyzed by using satellite images and a field survey for landscape conservation purposes. A survey scope was fixed using DEM, and areas of damage in the mountain range were analyzed via ArcMap v. 9.2 using SPOT 5 images, a high resolution satellite image. All damaged areas were reviewed and corrected in a field survey. As a result, 75 roads were found to completely fragment forest patches. Of those roads, 26 have the width under 3m, which means that the fragmentation of the forest by these roads may have a minor effect on forest habitat and its ecosystems, while other roads such as two-lane roads may have broader detrimental influences on the ecosystem. Two thousand eighty-three sections of accounted for a total area of about 5,760.7ha. Orchard areas including chestnut tree plantations were ranked as the largest in the damaged area within the Geum-buk Mountains, followed by public facility areas and grassland areas. This means that man-made land usage has progressed in the area regardless of slope and elevation.

Localization of Unmanned Ground Vehicle based on Matching of Ortho-edge Images of 3D Range Data and DSM (3차원 거리정보와 DSM의 정사윤곽선 영상 정합을 이용한 무인이동로봇의 위치인식)

  • Park, Soon-Yong;Choi, Sung-In
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.43-54
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    • 2012
  • This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

Road Extraction from Images Using Semantic Segmentation Algorithm (영상 기반 Semantic Segmentation 알고리즘을 이용한 도로 추출)

  • Oh, Haeng Yeol;Jeon, Seung Bae;Kim, Geon;Jeong, Myeong-Hun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.3
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    • pp.239-247
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    • 2022
  • Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

A study on the development of a Blue-green algae cell count estimation formula in Nakdong River downstream using hyperspectral sensors (초분광센서를 활용한 낙동강 하류부 남조류세포수 추정식 개발에 관한 연구)

  • Kim, Gwang Soo;Choi, Jae Yun;Nam, Su Han;Kim, Young Dod;Kwon, Jae Hyun
    • Journal of Korea Water Resources Association
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    • v.56 no.6
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    • pp.373-380
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    • 2023
  • Due to abnormal climate phenomena and climate change in Korea, overgrowth of algae in rivers and reservoirs occurs frequently. Algae in rivers are classified into green algae, blue-green algae, diatom, and other types, and some species of blue-green algae cause problems due to odor and the discharge of toxic substances. In Korea, an algae alert system is in place, and it is issued based on the number of harmful blue-green algae cells. Thus, measuring harmful blue-green algal blooms is very important, and currently, the analysis method of algae involves taking field samples and determining the cell count of green algae, blue-green algae, and diatoms through algal microscopy, which takes a lot of time. Recently, the analysis of algae concentration through Phycocyanin, an alternative indicator for the number of harmful algae cells, has been conducted through remote sensing. However, research on the analysis of the number of blue-green algae cells is currently insufficient. In this study, we water samples for algal analyses were collected from river and counted the number of blue-green algae cells using algae microscopy. We also obtained the Phycocyanin concentration using an optical sensor and acquired algae spectra through a hyperspectral sensor. Based on this, we calculated the equation for estimating blue-green algae cell counts and estimated the number of blue-green algae cells.

Analysis of Drought Damage around Tonlé Sap which is Largest Lake in Southeast Asia (동남아시아 최대 호수인 톤레사프호 주변 가뭄피해 분석)

  • Lee, Jong Sin;Um, Dae Yong
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.5
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    • pp.961-969
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    • 2017
  • Today, the world is experiencing a variety of natural disasters due to the extreme weather. Drought that occurred throughout Southeast Asia from February to May 2016 is also a form of abnormal climate. As a result of this drought, five countries, including Cambodia, Thailand, Vietnam, Laos and Myanmar, faced food shortages, food shortages, as well as rice yields for export. In this study, remote sensing technique was applied to the vicinity of Tonlé Sap, the largest lake in Southeast Asia, to quantitatively analyze the damage caused by drought. As a result, the change of land cover caused a drastic decrease in the water system (132.582㎢) and greenery (706.937㎢) in February 2016, and the reduced water system and greenery changed to dry land and paddy field. It was also found that the temperature rise of 6℃ ~ 8 ℃ compared to the previous year due to the drought from February to April 2016 due to the change of the surface temperature. And it was found that the function of the lake was deteriorated in April due to continuous drought.