• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.87-98
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• 2012

A river boundary is defined as the intersection between a main stream of a river and the land. Mapping of the river boundary is important for the protection of the properties in river areas, the prevention of flooding and the monitoring of the topographic changes in river areas. However, the utilization of the ground surveying technologies is not efficient for the mapping of the river boundary due to the irregular surfaces of river zones and the dynamic changes of water level of a river stream. Recently, the spatial information data sets such as the airborne LiDAR and aerial images are widely used for coastal mapping due to the acquisition of the topographic information without human accessibility. Due to these advantages, this research proposes a semi-automatic method for mapping of the river boundary using the spatial information data set such as the airborne LiDAR and the aerial photographs. Multiple image processing technologies such as the image segmentation algorithm and the edge detection algorithm are applied for the generation of the 3D river boundary using the aerial photographs and airborne topographic LiDAR data. Check points determined by the experienced expert are used for the measurement of the horizontal and vertical accuracy of the generated 3D river boundary. Statistical results show that the generated river boundary has a high accuracy in horizontal and vertical direction.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.727-736
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• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.1-19
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• 2020

A river bed which is submerged in water at high flow and becomes part of the river at low flow, serves as a bridge between the river and the land. The channel bar creates a unique ecosystem with vegetation adapted to the particular environment and the water pool forms a wetland that plays a very important role in the environment. To evaluate anthropogenic impacts on the river bed in the Middle Yeongsangang River, the fluvial landforms in the stream channel were analyzed using multi-temporal remotely-sensed images. In the aerial photograph of 2005 taken before the construction of the large weirs, oxbow lakes, mid-channel bars, point bars, and natural wetlands between the artificial levees were identified. Multiple bars divided the flow of stream water to cause the braided pattern in a particular section. After the construction of the Seungchon weir, aerial photographs of 2013 and 2015 revealed that most of the fluvial landforms disappeared due to the dredging of its riverbed and water level control(maintenance at 7.5El.m). Sentinel-2 images were analyzed to identify differences between before and after the opening of weir gate. Change detection was performed with the near infrared and shortwave infrared spectral bands to effectively distinguish water surfaces from land. As a result, water surface area of the main stream of the Yeongsangang River decreased by 40% from 1.144km² to 0.692km². A large mid-channel bar that has been deposited upstream of the weir was exposed during low water levels, which shows the obvious influence of weir on the river bed. Newly formed unvegetated point bars that were deposited on the inside of a meander bend were identified from the remotely sensed images. As the maintenance period of the weir gate opening was extended, various habitats were created by creating pools and riffles around the channel bars. Considering the ecological and hydrological functions of the river bed, it is expected that the increase in bar areas through weir gate opening will reduce the artificial interference effect of the weir.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1059-1070
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• 2020

River cross-section measurement data is one of the most important input data in research related to hydraulic and hydrological modeling, such as flow calculation and flood forecasting warning methods for river management. However, the acquisition of accurate and continuous cross-section data of rivers leading to irregular geometric structure has significant limitations in terms of time and cost. In this regard, a primary objective of this study is to develop a methodology that is able to measure the spatial distribution of continuous river characteristics by minimizing the input of time, cost, and manpower. Therefore, in this study, we tried to examine the possibility and accuracy of continuous cross-section estimation by estimating the water depth for each cross-section through multiple linear regression analysis using RGB-based aerial images and actual data. As a result of comparing with the actual data, it was confirmed that the depth can be accurately estimated within about 2 m of water depth, which can capture spatially heterogeneous relationships, and this is expected to contribute to accurate and continuous river cross-section acquisition.

• Wind and Structures
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• v.19 no.3
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• pp.321-337
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• 2014

This study has developed an Enhanced Remote-Sensing (ERS) scale to improve the accuracy and efficiency of using remote-sensing images of residential building to predict their damage conditions. The new scale, by incorporating multiple damage states observable on remote-sensing imagery, substantially reduces measurement errors and increases the amount of information retained. A ground damage survey was conducted six days after the Joplin EF 5 tornado in 2011. A total of 1,400 one- and two-family residences (FR12) were selected and their damage states were evaluated based on Degree of Damage (DOD) in the Enhanced Fujita (EF) scale. A subsequent remote-sensing survey was performed to rate damages with the ERS scale using high-resolution aerial imagery. Results from Ordinary Least Square regression indicate that ERS-derived damage states could reliably predict the ground level damage with 94% of variance in DOD explained by ERS. The superior performance is mainly because ERS extracts more information. The regression model developed can be used for future rapid assessment of tornado damages. In addition, this study provides strong empirical evidence for the effectiveness of the ERS scale and remote-sensing technology for assessment of damages from tornadoes and other wind events.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5095-5111
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• 2019

A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.63-70
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• 2019

Electric transmission towers are facilities to transport electrical power from a plant to an electrical substation. The towers are connected using wires considering the wire tension and the clearance from the ground or nearby objects. The wires are installed on a rights-of-way that is a strip of land used by electrical utilities to maintain the transmission line facilities. Trees and plants around transmission lines must be managed to keep the operation of these lines safe and reliable. This study proposed the use of a low-cost drone photogrammetry for the transmission line rights-of-way mapping. Aerial photogrammetry is carried out to generate a dense point cloud around the transmission lines from which a DSM (Digital Surface Model) and DTM (Digital Terrain Model) are created. The lines and nearby objects are separated using nDSM (normalized Digital Surface Model) and the noises are suppressed in the multiple image space for the geospatial analysis. The experimental result with drone images over two spans of transmission lines on a mountain area showed that the proposed method successfully generate the rights-of-way map with hazard nearby objects.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.261-271
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• 2009

Due to the recent rise of a need for 3 dimensional geospatial information on urban areas, general interest in aerial multi-view cameras has been on an increase. The conventional geospatial information system depends solely upon vertical images, while the multi-view camera is capable of taking both vertical and oblique images taken from multiple directions, thus making it easier for the user to interpret the object. Through our research we developed a prototype of a multi-view camera system that includes a camera system, GPS/INS, a flight management system, and a control system. We also studied and experimented with the camera viewing angles, the synchronization of image capture, the exposure delay, the data storage that must be considered for the development of the multi-view camera system.