• Title/Summary/Keyword: Aerial survey

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A Study on the Monitoring Method of Landslide Damage Area Using UAV (UAV를 이용한 산사태 피해지역 모니터링 방법에 관한 연구)

  • Kim, Sung-Bo
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.6_2
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    • pp.1043-1050
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    • 2020
  • In this study, a study was presented on the monitoring technique of landslide area using UAV. In the case of disaster investigation using drone mapping, it can be used at various disaster sites. The mission can be carried out at various disaster sites, including surveys of damage to mountainous areas caused by landslides, building collapses surveys of flood damage, typhoons, earthquakes. The damage investigation plan using drone mapping is expected to be highly utilized at disaster sites where investigators cannot access it like in mountainous areas and where it is difficult to conduct direct damage investigations at the site. Drone mapping technology has many advantages in terms of disaster follow-up, such as recovery. Compared to the existing survey system, which was mainly carried out manually, the investigation time can be drastically reduced, and it can also respond to disaster sites that are difficult to carry out or are difficult to access directly. In addition, it is possible to establish and guide spatial data at the disaster site based on accurate mapping data from the time of the disaster, which has considerable strength in managing the situation of the disaster site, selecting priority areas for recovery, and establishing recovery plans. As such, drone mapping is a technology that can be used in a wide range of sites along with natural disasters and social disasters. If a damage investigation system is established through this, it is believed that it will contribute significantly to the rapid establishment of recovery plans along with the investigation of disaster response time and extent of damage recovery.

Development of Extraction Technique for Irrigated Area and Canal Network Using High Resolution Images (고해상도 영상을 이용한 농업용수 수혜면적 및 용배수로 추출 기법 개발)

  • Yoon, Dong-Hyun;Nam, Won-Ho;Lee, Hee-Jin;Jeon, Min-Gi;Lee, Sang-Il;Kim, Han-Joong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.4
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    • pp.23-32
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    • 2021
  • For agricultural water management, it is essential to establish the digital infrastructure data such as agricultural watershed, irrigated area and canal network in rural areas. Approximately 70,000 irrigation facilities in agricultural watershed, including reservoirs, pumping and draining stations, weirs, and tube wells have been installed in South Korea to enable the efficient management of agricultural water. The total length of irrigation and drainage canal network, important components of agricultural water supply, is 184,000 km. Major problem faced by irrigation facilities management is that these facilities are spread over an irrigated area at a low density and are difficult to access. In addition, the management of irrigation facilities suffers from missing or errors of spatial information and acquisition of limited range of data through direct survey. Therefore, it is necessary to establish and redefine accurate identification of irrigated areas and canal network using up-to-date high resolution images. In this study, previous existing data such as RIMS (Rural Infrastructure Management System), smart farm map, and land cover map were used to redefine irrigated area and canal network based on appropriate image data using satellite imagery, aerial imagery, and drone imagery. The results of the building the digital infrastructure in rural areas are expected to be utilized for efficient water allocation and planning, such as identifying areas of water shortage and monitoring spatiotemporal distribution of water supply by irrigated areas and irrigation canal network.

Application of advanced spectral-ratio radon background correction in the UAV-borne gamma-ray spectrometry

  • Jigen Xia;Baolin Song;Yi Gu;Zhiqiang Li;Jie Xu;Liangquan Ge;Qingxian Zhang;Guoqiang Zeng;Qiushi Liu;Xiaofeng Yang
    • Nuclear Engineering and Technology
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    • v.55 no.8
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    • pp.2927-2934
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    • 2023
  • The influence of the atmospheric radon background on the airborne gamma spectrum can seriously affect researchers' judgement of ground radiation information. However, due to load and endurance, unmanned aerial vehicle (UAV)-borne gamma-ray spectrometry is difficulty installing upward-looking detectors to monitor atmospheric radon background. In this paper, an advanced spectral-ratio method was used to correct the atmospheric radon background for a UAV-borne gamma-ray spectrometry in Inner Mongolia, China. By correcting atmospheric radon background, the ratio of the average count rate of U window in the anomalous radon zone (S5) to that in other survey zone decreased from 1.91 to 1.03, and the average uranium content in S5 decreased from 4.65 mg/kg to 3.37 mg/kg. The results show that the advanced spectral-ratio method efficiently eliminated the influence of the atmospheric radon background on the UAV-borne gamma-ray spectrometry to accurately obtain ground radiation information in uranium exploration. It can also be used for uranium tailings monitoring, and environmental radiation background surveys.

Comparative Analysis of DTM Generation Method for Stream Area Using UAV-Based LiDAR and SfM (여름철 UAV 기반 LiDAR, SfM을 이용한 하천 DTM 생성 기법 비교 분석)

  • Gou, Jaejun;Lee, Hyeokjin;Park, Jinseok;Jang, Seongju;Lee, Jonghyuk;Kim, Dongwoo;Song, Inhong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.66 no.3
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    • pp.1-14
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    • 2024
  • Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

Detection of Pine Wilt Disease tree Using High Resolution Aerial Photographs - A Case Study of Kangwon National University Research Forest - (시계열 고해상도 항공영상을 이용한 소나무재선충병 감염목 탐지 - 강원대학교 학술림 일원을 대상으로 -)

  • PARK, Jeong-Mook;CHOI, In-Gyu;LEE, Jung-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.2
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    • pp.36-49
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    • 2019
  • The objectives of this study were to extract "Field Survey Based Infection Tree of Pine Wilt Disease(FSB_ITPWD)" and "Object Classification Based Infection Tree of Pine Wilt Disease(OCB_ITPWD)" from the Research Forest at Kangwon National University, and evaluate the spatial distribution characteristics and occurrence intensity of wood infested by pine wood nematode. It was found that the OCB optimum weights (OCB) were 11 for Scale, 0.1 for Shape, 0.9 for Color, 0.9 for Compactness, and 0.1 for Smoothness. The overall classification accuracy was approximately 94%, and the Kappa coefficient was 0.85, which was very high. OCB_ITPWD area is approximately 2.4ha, which is approximately 0.05% of the total area. When the stand structure, distribution characteristics, and topographic and geographic factors of OCB_ITPWD and those of FSB_ITPWD were compared, age class IV was the most abundant age class in FSB_ITPWD (approximately 55%) and OCB_ITPWD (approximately 44%) - the latter was 11% lower than the former. The diameter at breast heigh (DBH at 1.2m from the ground) results showed that (below 14cm) and (below 28cm) DBH trees were the majority (approximately 93%) in OCB_ITPWD, while medium and (more then 30cm) DBH trees were the majority (approximately 87%) in FSB_ITPWD, indicating different DBH distribution. On the other hand, the elevation distribution rate of OCB_ITPWD was mostly between 401 and 500m (approximately 30%), while that of FSB_ITPWD was mostly between 301 and 400m (approximately 45%). Additionally, the accessibility from the forest road was the highest at "100m or less" for both OCB_ITPWD (24%) and FSB_ITPWD (31%), indicating that more trees were infected when a stand was closer to a forest road with higher accessibility. OCB_ITPWD hotspots were 31 and 32 compartments, and it was highly distributed in areas with a higher age class and a higher DBH class.

Estimation of Chlorophyll Contents in Pear Tree Using Unmanned AerialVehicle-Based-Hyperspectral Imagery (무인기 기반 초분광영상을 이용한 배나무 엽록소 함량 추정)

  • Ye Seong Kang;Ki Su Park;Eun Li Kim;Jong Chan Jeong;Chan Seok Ryu;Jung Gun Cho
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.669-681
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    • 2023
  • Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R2)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm2, relative error (RE)≤17.9% and validation of R2≥0.56, RMSE≤1.41 ㎍/cm2, RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R2=0.80, RMSE=0.94 ㎍/cm2, RE=13.9%, and validation showed R2=0.57, RMSE=1.40 ㎍/cm2, RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

Region Growing Method for Calculating Unmeasured Rate of Aerial LiDAR Data (항공라이다의 결측률 산출을 위한 영역확장 기법)

  • Han, Soung-Man;Kim, Ji-Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.29-38
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    • 2010
  • The airborne LiDAR which was introduced in the early 2000's provides the point data. The new methods for the verification of LiDAR materials with high accuracy which is different from the existing airborne survey are needed. In accordance with the rules of airborne laser survey which were enacted in 2009, the verifications by three methods of Unmeasured Rate and point accuracy, point density have been executed, and Unmeasured Rate is to evaluate the rate for the presence of points within uniform grids except non-reflective areas such as watershed areas. For the calculation of Unmeasured Rate, non-reflective areas should be removed by all means, and in case of normal LiDAR materials, as there are scant points for watershed areas, watershed areas should be divided by additional spatial information. So, in this study, the watershed areas were extracted using domain extension technique from the high resolution CIR images of 0.3m grade. In addition, in order to compare the accuracy of Unmeasured Rate calculated, the comparative analysis of the Unmeasured Rate calculated by digital maps has been done. In conclusion, we found that 1I1e accuracy of Unmeasured Rate extracted by domain extension technique is similar to the value extracted by digitizing technique.

UAV Photogrammetry Accuracy Analysis at Marine Using Arbitrary Reference Points (임의의 기준점을 이용한 해상에서의 UAV 사진측량 정확도 분석)

  • Oh, Jae Hyun;Kim, Byung Woo;Hwang, Dae Young;Hong, Soon Heon
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.4
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    • pp.39-45
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    • 2016
  • In this study, with arbitrary reference points on the water, photogrammetry accuracy analysis was conducted using unmanned aerial vehicle(UAV). A small reservoir is a research area, and twenty buoys were used as arbitrary reference points. Errors of location coordinate were identified with control of amounts of used reference points. cases are categorized by index scores per photos. Accuracy of X is 0.141m~0.166m and accuracy of Y is 0.136m~0.241m. Considering that allowable error for the maritime boundary survey is ${\pm}2m$, it is possible to get the accuracy data available for the photogrammetry of UAV using an reference point. In addition, the coefficient of correlation between the number of reference points per unit and number of buoys used as reference point and the ratio of the reference point per square measure, and percentage of buoys used as reference point and the coefficient of x and y were performed. Each element, x, and y showed a strong correlation and the coefficient of number of buoys used as reference point was irrelevant. The results of this correlation analysis can be analyzed that the number of reference points used in each picture is greater than the actual number of reference points used in location accuracy.

Numerical Analysis of Debris Flow Using Drone Images and NFLOW (드론 영상 및 NFLOW를 활용한 토석류 수치해석 연구)

  • Lee, Seungjoo;Lim, Hyuntaek;Lim, Moojae;Lee, Eungbeom;Lee, Kang-Il;Kim, Yongseong
    • Journal of the Korean Geosynthetics Society
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    • v.19 no.3
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    • pp.1-8
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    • 2020
  • In this study, numerical analysis of debris flow was performed using the SPH (Smoothed Particle Hydrodynamics) technique to analyze the mechanism of debris flow, and the applicability of soil parameters was verified by comparison with previous studies. In addition, after performing aerial photographic survey using a drone, a topographic model was created based on this survey to check the applicability of the site to the valley part of Jagul Mountain basin. And after numerical analysis of debris flow was performed using NFLOW, and the result was compared and analyzed with the existing satellite image based method. As a result of this study, the numerical analysis method using drone image and NFLOW was found to have a higher applicability to predicting the impact of debris flow, because it can reflect the actual topography better than the existing method based on satellite imagery. Therefore, it is considered that this study can be used as basic data to establish the preventive measures for debris flow such as location selection of the eruption control dam.

Vegetation and Landscape Analysis and Management Methods of Ip-am Wetland in the Naejang National Park (내장산국립공원 입암습지의 식생 및 경관 변화와 관리방안)

  • Lee, Seon-Mi;Myeong, Hyeon-Ho
    • Korean Journal of Ecology and Environment
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    • v.48 no.1
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    • pp.26-31
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    • 2015
  • This study was performed to evaluate the Ip-am wetland located in the Naejang National Park by analyzing vegetation and landscape and to suggest management plans. We carried out field survey in 2013 and analyzed aerial photos in 1976 and 2010 for landscape change. As a result, the places that were paddy fields in the past were dominated by 5 communities such as Salix koreensis Community (21.6%), Persicaria thunbergii Community (2.8%), Phragmites communis Community (1.1%), Molinia japonica Community (4.9%), Persicaria thunbergii-Molinia japonica Community (0.5%). On the other hand, the places that were upper fields in the past were occupied mostly by Rosa multiflora Community (6.8%), Humulus japonicus-Rosa multiflora Community (42.0%), Humulus japonicus Community (10.6%). In order to maintain and manage the wetland, water should be supplied continuously by making use of the six among the seven reservoirs located in the upper part through the hydrological survey should be accomplished. In addition, it was necessary to reinforce the banks for minimizing water outflow. It contributes to prevent dry peat and decrease in decomposition speed. Thus, it is hard to invade and settle of terrestrial plants and then secondary succession would be delayed.