• Spatial Information Research
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• v.19 no.2
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• pp.19-28
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• 2011

Three dimensional modeling for seafloor topography is essential to monitoring displacements in underwater structures as well as all sorts of disasters along the shore. MBES is a system that is capable of high-density water depth measurement for seafloor topography and is in broad uses for gathering 3D data and detecting displacements. MBES data, however, contain random errors that take place in the equipment offset and surveying process and require systematic researches on the correction of wrong depth measurements. Thus this study set out to propose a post-processing technique to eliminate an array of random errors taking place after equipment offset correction and basic noise correction in the MBES system and analyze its applicability to seafloor topography modeling by applying it to the subject area.

• Spatial Information Research
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• v.17 no.3
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• pp.301-307
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• 2009

Recently, the various studies has been focused on evaluating the damage and stability of long span bridge through measuring and monitoring to ensure the stability and usability. But, even if various studies are performed, it is hard to predict and evaluate the real motion of structure. The aim of this study is check the application of GPS to the motion monitoring of long span bridge by comparing data acquired form RTK-GPS and laser displacement meter.

• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.257-267
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• 2011

This paper examines the spatial and temporal variability in the shoreline boundary caused by artificial structures in Songdo Beach of South Korea. Quickbird Images of 2003, 2005, 2007, and 2010 extracted from Google Earth were used to identify changing trends of shoreline boundary. The most significant changes were observed in area where groins were extensively established, inducing the sand beach much narrower than before in almost 75% of the area($15070.72m^2$ in 2003 to $3877.46m^2$ in 2010). The Google Earth made it possible to identify area-wide patterns of shoreline change subject to many different type of artificial structures, which cannot be acquired by traditional field sampling. Groin heights, lengths and profiles can be modified during maintenance operations if the Google Earth monitoring indicates that the initial layout is not operating properly as a physical barrier to control sediment transport. It is anticipated that this research could be used as a valuable reference to confirm the outputs from past field researches for coastal processes to respond to storms in more visual and quantitative manner.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.307-314
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• 2011

This study proposed detection method of Marine debris using unmanned aerial photography. For unmanned aerial photography, a RC(Radio Control) helicopter which has good movability and economics was used. To a camera mounting, a gimbal equipment was attached to the bottom of the RC helicopter. The gimbal equipment is very useful because it is not seriously affected by vibration and rolling. In addition, we invented that digital image processing algorithm using Matlab program for detection of marine debris from photographs. Particularly, background subtraction in invented algorithm was applied. As a result, marine debris of a variety of forms from different sand states of coast were reliably detected. In the future, monitoring using proposed method was expected to contribute that the solution to representative problem of monitoring area selecting and estimate the total litter mass over the beach. Moreover, It is considered a greater application possibility to marine environmental observations.

• Spatial Information Research
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• v.19 no.4
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• pp.21-31
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• 2011

As large scaled natural or man-made disasters being increased, the demand for rapid responses for such emergent situations also has been ever-increasing. These responses need to acquire spatial information of each individual site rapidly for more effective management of the situations. Therefore, we are developing a close-range real-time aerial monitoring system based on a low altitude unmanned helicopter. This system can acquire airborne sensory data in real-time and generate rapidly geospatial information. The system consists of two main parts: aerial and ground parts. The aerial part includes an aerial platform equipped with multi-sensor(cameras, a laser scanner, a GPS receiver, an IMU) and sensor supporting modules. The ground part includes a ground vehicle, a receiving system to receive sensory data in real-time and a processing system to generate the geospatial information rapidly. Development and testing of the individual modules and subsystems have been almost completed. Integration of the modules and subsystems is now in progress. In this paper, we w ill introduce our system, explain intermediate results, and discuss expected outcome.

• Journal of Biosystems Engineering
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• v.39 no.1
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• pp.47-56
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• 2014

Purpose: In protected crop production facilities such as greenhouse and plant factory, farmers should be present and/or visit frequently to the production site for maintaining optimum environmental conditions and better production, which is time and labor consuming. Monitoring of environmental condition is highly important for optimum control of the conditions, and the condition is not uniform within the facility. Objectives of the paper were to investigate spatial and vertical variability in ambient environmental variables and to provide useful information for sensing and control of the environments. Methods: Experiments were conducted in a strawberry-growing greenhouse (greenhouse 1) and a cherry tomato-growing greenhouse (greenhouse 2). Selected ambient environmental variables for experiment in greenhouse 1 were air temperature and humidity, and in greenhouse 2, they were air temperature, humidity, PPFD (Photosynthetic Photon Flux Density), and $CO_2$ concentration. Results: Considerable spatial, vertical, and temporal variability of the ambient environments were observed. In greenhouse 1, overall temperature increased from 12:00 to 14:00 and increased after that, while RH increased continuously during the experiments. Differences between the maximum and minimum temperature and RH values were greater when one of the side windows were open than those when both of the windows were closed. The location and height of the maximum and minimum measurements were also different. In greenhouse 2, differences between the maximum and minimum air temperatures at noon and sunset were greater when both windows were open. The maximum PPFD were observed at a 3-m height, close to the lighting source, and $CO_2$ concentration in the crop growing regions. Conclusions: In this study, spatial, vertical, and temporal variability of ambient crop growing conditions in greenhouses was evaluated. And also the variability was affected by operation conditions such as window opening and heating. Results of the study would provide information for optimum monitoring and control of ambient greenhouse environments.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• 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.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1421-1434
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• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.401-410
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• 2013

Due to the increasing need for spatial information, there have been a lot of research related with monitoring and revision of changed regions for the acquisition of the accurate and latest information. In this paper, the optimal monitoring management plan for changed regions with respect to the revision periods was proposed. For this purpose, the representative monitoring methods, which are based on database, professional manpower and crowdsourcing of continuous revision, and aerial imagery, satellite imagery and LiDAR of cyclic revision, were investigated. Then, the properties and application status of monitoring systems in Korea were illustrated according to the methods. Finally, the optimal monitoring management plan for continuous and cyclic revisions was suggested through the comparison of properties and revisionable objects of each method. From the result, it was shown to be appropriate for the optimal monitoring management plan of continuous revision as using Internet-Architectural Information System (e-AIS) database cooperated with professional manpower and crowdsourcing, and cyclic revision as using domestic high-resolution satellite images and LiDAR data processed semi-automatically.