• Title/Summary/Keyword: Aerial image

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Deep Learning Approaches for Accurate Weed Area Assessment in Maize Fields (딥러닝 기반 옥수수 포장의 잡초 면적 평가)

  • Hyeok-jin Bak;Dongwon Kwon;Wan-Gyu Sang;Ho-young Ban;Sungyul Chang;Jae-Kyeong Baek;Yun-Ho Lee;Woo-jin Im;Myung-chul Seo;Jung-Il Cho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.1
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    • pp.17-27
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    • 2023
  • Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

Development of Kimchi Cabbage Growth Prediction Models Based on Image and Temperature Data (영상 및 기온 데이터 기반 배추 생육예측 모형 개발)

  • Min-Seo Kang;Jae-Sang Shim;Hye-Jin Lee;Hee-Ju Lee;Yoon-Ah Jang;Woo-Moon Lee;Sang-Gyu Lee;Seung-Hwan Wi
    • Journal of Bio-Environment Control
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    • v.32 no.4
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    • pp.366-376
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    • 2023
  • This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.

Analysis of Landscape Structure Change for Riparian Buffer Zone KyangAn Watershed (경안천 유역 수변구역 경관구조 변화 분석)

  • Kim, Kyung-Tak;Kim, Joo-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.8 no.3
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    • pp.74-83
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    • 2005
  • The Riparian Buffer Zone has many potential values including the preservation of water quality as well as being ecologically friendly. This study aims to quantitatively analyze the landscape structure index of the Riparian Buffer Zone in the Kyoung-an stream and to produce base information necessary for proper management. The study used aerial images that were applied to geometric corrections for a time series from 1966 to 2000 for land data and also used FRAGSTATS, which is a type of ARCVIEW extension module, as an analysis tool. An analysis of land use change and the Landscape Index revealed that the area of farm land has decreased and that the area of residential property has increased. In addition, there was a slight change for land used for purposes other than farming or for residence. The results of analyzing the Landscape Structure Index, revealed that the NP has increased from 437 in 1966 to 695 in 2000. This data reveals that the change of land use is influenced by various artificial factors. The NPS, which represents the declining degree of patch, decreased from 9.441 to 5.934, revealing that the change of land use has been progressing considerably. In regard to forest areas, land use reduced somewhat but did not indicate a significant change. Therefore, an analysis of the total index reveals that the edge of patch has become more complicated and that the variation index of patch has increased significantly. However, this study reveals that barriers to block pollution have weakened as a result and that there is a need to concentrate on the implementation and the management of the Riparian Buffer Zone. Consequently, this study reveals that substantial research is necessary in order to carry out the proper management of the Riparian Buffer Zone, especially in light of the distribution type of each patch and the change in conditions regarding them.

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Simulation Approach for the Tracing the Marine Pollution Using Multi-Remote Sensing Data (다중 원격탐사 자료를 활용한 해양 오염 추적 모의 실험 방안에 대한 연구)

  • Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.249-261
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    • 2020
  • Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.

Wind Corridor Analysis and Climate Evaluation with Biotop Map and Airborne LiDAR Data (비오톱 지도와 항공라이다 자료를 이용한 바람통로 분석 및 기후평가)

  • Kim, Yeon-Mee;An, Seung-Man;Moon, Soo-Young;Kim, Hyeon-Soo;Jang, Dae-Hee
    • Journal of the Korean Institute of Landscape Architecture
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    • v.40 no.6
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    • pp.148-160
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    • 2012
  • The main purpose of this paper is to deliver a climate analysis and evaluation method based on GIS by using airborne LiDAR data and Biotop type map and to provide spatial information of climate analysis and evaluation based on Biotop type Map. At first stage, the area, slope, slope length, surface, wind corridor function and width, and obstacle factors were analyzed to obtain cold/fresh air production and wind corridor evaluation. In addition, climate evaluation was derived from those two results in the second stage. Airborne LiDAR data are useful in wind corridor analysis during the study. Correlation analysis results show that ColdAir_GRD grade was highly correlated with Surface_GRD (-0.967461139) and WindCorridor_ GRD was highly correlated with Function_GRD (-0.883883476) and Obstacle_GRD (-0.834057656). Climate Evaluation GRID was highly correlated with WindCorridor_GRD (0.927554516) than ColdAir_GRD (0.855051646). Visual validations of climate analysis and evaluation results were performed by using aerial ortho-photo image, which shows that the climate evaluation results were well related with in-situ condition. At the end, we applied climate analysis and evaluation by using Biotop map and airborne LiDAR data in Gwangmyung-Shiheung City, candidate for the Bogeumjari Housing District. The results show that the aerial percentile of the 1st Grade is 18.5%, 2nd Grade is 18.2%, 3rd Grade is 30.7%, 4th Grade is 25.2%, and 5th Grade is 7.4%. This study process provided both the spatial analysis and evaluation of climate information and statistics on behalf of each Biotop type.

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.

CAS 500-1/2 Image Utilization Technology and System Development: Achievement and Contribution (국토위성정보 활용기술 및 운영시스템 개발: 성과 및 의의)

  • Yoon, Sung-Joo;Son, Jonghwan;Park, Hyeongjun;Seo, Junghoon;Lee, Yoojin;Ban, Seunghwan;Choi, Jae-Seung;Kim, Byung-Guk;Lee, Hyun jik;Lee, Kyu-sung;Kweon, Ki-Eok;Lee, Kye-Dong;Jung, Hyung-sup;Choung, Yun-Jae;Choi, Hyun;Koo, Daesung;Choi, Myungjin;Shin, Yunsoo;Choi, Jaewan;Eo, Yang-Dam;Jeong, Jong-chul;Han, Youkyung;Oh, Jaehong;Rhee, Sooahm;Chang, Eunmi;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.867-879
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    • 2020
  • As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

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.

Development of GIS Application using Web-based CAD (Web기반 CAD를 이용한 지리정보시스템 구현)

  • Kim, Han-Su;Im, Jun-Hong;Kim, Jae-Deuk;Shin, So-Eun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.3
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    • pp.69-76
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    • 2000
  • This study deals with development GIS application using web-based CAD, this application serves to user, designer, manager that more convenient and various functions. Development to this application, collect attribute data from fieldwork and geographic data from cadastral map and aerial survey map and then development to user interface using HTML, JavaScript, ASP, Whip ActiveX control. This application's characters are as follows ; First, system designer designed that anyone who have basic knowledge about web and CAD can develop this application. A system structure simplification by 2-Tier. Geographic information use DWF(drawing web format) file and attribute information use DBMS in consideration of extension. Second, system manager can service independently GIS in Web need not high priced GIS engine, so more economical. Third, internet user get service GIS information and function that search of information, zoom in/out, pan, print etc., if you need more functions, add function without difficultly. Developed application as above, not only save volume but fast of speed as use vector data exclude character and image data. Also, this application can used by means of commercial and travel information service but also various GIS service of public institution and private in web.

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Update of Digital Map by using The Terrestrial LiDAR Data and Modified RANSAC (수정된 RANSAC 알고리즘과 지상라이다 데이터를 이용한 수치지도 건물레이어 갱신)

  • Kim, Sang Min;Jung, Jae Hoon;Lee, Jae Bin;Heo, Joon;Hong, Sung Chul;Cho, Hyoung Sig
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.4
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    • pp.3-11
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    • 2014
  • Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.