• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.431-441
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• 2016

Since the use of UAV (Unmanned Aerial Vehicle) is convenient for the acquisition of data on broad or inaccessible regions, it is nowadays used to establish spatial information for various fields, such as the environment, ecosystem, forest, or for military purposes. In this study, the process of estimating FVC (Fractional Vegetation Cover), based on multi-spectral UAV, to overcome the limitations of conventional methods is suggested. Hence, we propose that the FVC map is generated by using multi-spectral imaging. First, two types of result classifications were obtained based on RF (Random Forest) using RGB images and NDVI (Normalized Difference Vegetation Index) with RGB images. Then, the result map was reclassified into vegetation and non-vegetation. Finally, an FVC map-based RF were generated by using pixel calculation and FVC map-based GI (Gutman and Ignatov) model were indirectly made by fixed parameters. The method of adding NDVI shows a relatively higher accuracy compared to that of adding only RGB, and in particular, the GI model shows a lower RMSE (Root Mean Square Error) with 0.182 than RF. In this regard, the availability of the GI model which uses only the values of NDVI is higher than that of RF whose accuracy varies according to the results of classification. Our results showed that the GI mode ensures the quality of the FVC if the NDVI maintained at a uniform level. This can be easily achieved by using a UAV, which can provide vegetation data to improve the estimation of FVC.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.216-218
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• 2009

This paper proposes an image processing algorithm to stabilize shaken scenes of UAV(Unmanned Aerial Vehicle) caused by vehicle self-vibration and aerodynamic disturbance. The proposed method stabilizes images by compensating estimated shake motion which is evaluated from global motion. The global motion between two continuous images modeled by 6 parameter warping model is estimated by non-linear square method based on Gauss-Newton algorithm with excluding outlier region. The shake motion is evaluated by subtracting the global motion from aerial vehicle motion obtained by averaging global motion. Experimental results show that the proposed method stabilize shaken scenes effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.153-164
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• 2018

Calculating the relevant length of left turn storages in urban intersections is very crucial in road designs. A left turn lane consists of deceleration lanes and left turn storages. In this study, we developed methods for calculating relevant lengths of left turn storages that vary at each intersection using UAV (Unmanned Aerial Vehicle) spatial images. Problems of conventional design techniques are applying the same number of left turn vehicles (N) using Poisson distribution without considering land use types, using a vehicle length that may not be measurable when applying the length of waiting vehicles (S), and using same storage length coefficient (${\alpha}$), 1.5, for every intersections. In order to solve these problems, we estimated the number of left turn vehicles (N) using an empirical distribution, suggested to use headways of vehicles for (S) to calculate the length of waiting vehicles (S) with a help of using UAV spatial images, and defined ranges of storage length coefficient (${\alpha}$) from 1.0 to 1.5 for flexible design. For more convenient design, it is suitable to classify two cases when possible to know and impossible to know about ratio of large trucks among vehicles when planning an intersection. We developed formula for each case to calculate left turn storage lengths of a minimum and a maximum. By applying developed methods and values, more efficient signalized intersection operation can be accomplished.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.555-563
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• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.539-543
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• 2016

In this paper, we study the technique to improve the performance of the aerial images taken by UAV using daubechies stationary wavelet transform. When aerial images taken by UAV were damaged by gaussian noise very commonly applied, the experiment for image performance improvement was performed. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. Also haar wavelet is discontinuous function so not efficient for smooth signal and image processing. Therefore, this study is confirmed that the noise can be removed by daubechies stationary wavelet and the performance is improved by haar stationary wavelet.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11B
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• pp.1732-1737
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• 2010

Currently, one of the main purposes of the military using Unmanned Air System (VAS) is to perform surveillance and reconnaissance of hostile enemy. To carry out their mission, Unmanned aerial vechicle (UAV) transmits video images to ground control station using ISR devices installed on the UAV. After receiving the images, the ground control station distribute them to various type of users. At this case, it is important to keep QoS. This paper presents data delivery and QoS managements using DDS for DDS for UAV video images. The experiment result, based on H.264 and JPEG2000, shows that DDS standard is able to be applied to video image transmission for UAS.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.177-188
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• 2024

The strategic UAV for theater level ISR(Intelligence, Surveillance and Reconnaissance) mission typically has numerous ground targets over area of responsibility(AOR) or area of operation(AO). It is necessary to automatically incorporate these multitude of ground targets into mission planning process in order to collect ISR images before actual flight mission. In addition, weather information such as wind direction and/or velocity may have significant impacts on the qualities of collected sensor images, especially in SAR(Synthetic Aperture Radar) images. Thus weather factors in the operation altitude should also be considered in the mission planning stage. In this study, we propose a novel mission planning scheme based on target scheduling and deviation correction method incorporating weather factors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.394-396
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• 2017

In various types of UAV systems, which have been developed recently, the communication system that is responsible for the connection between the ground control unit and the UAV is called the data link.Especially, in the data link used in systems for transmission of surveillance images from UAV in real time, stability of communication should be ensured. In this paper, the design of the data link modem was proposed for the purpose of applying for UAV for surveillance. And, the designed wad verified through the performance measurement of the implemented systems.