• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.99-114
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• 2024

Domestic coastal debris monitoring encounters challenges due to labor-intensive methods and limited survey scope. Consequently, research is utilizing remote sensing techniques to enhance efficiency in data collection. However, standards for domestic remote sensing based monitoring methods remain insufficient. In this study, we conducted a meta-analysis of 19 coastal debris monitoring studies utilizing drones and other remote sensing devices. We analyzed data collection methods, collected data information, monitoring target details, monitoring status, detection targets, and utilization models. Based on our meta-analysis results, we proposed monitoring criteria, recommended items, and performance standards for monitoring coastal debris using drones. Our findings define necessary conditions and standards for establishing operational guidelines for coastal debris monitoring using drones. Furthermore, we anticipate that incorporating foreign case analyses and field application results will enable the development of national-level guidelines for coastal debris monitoring utilizing remote sensing devices.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.351-366
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• 2014

The aim of this study was to develop software for beach litter detection that includes a Graphical User Interface (GUI) and uses images taken by a micro-unmanned aerial vehicle. Videos were taken over Doomo pebble beach, Sogye pebble beach, and Heungnam sand beach on the northeast coast of Geojedo (Geoje Island), Korea. Still images of actual beach litter were obtained from the videos. The image processing involved preprocessing, morphological image processing, and image recognition. Comparison with still images showing beach litter demonstrated that the software could generally detect litter larger than 50 cm in size such as Styrofoam buoys and circular fish traps (excluding small pixel-size ropes). Combining the proposed method with the conventional surveying approach is expected to enhance the accuracy of beach litter detection. The new technique will also aid in predicting the amount of beach litter generated along coastlines, which is currently difficult to monitor.

• ETRI Journal
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• v.34 no.5
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• pp.713-718
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• 2012

Sensor nodes in ubiquitous sensor networks require autonomous replacement of deteriorated gas sensors with reserved sensors, which has led us to develop an encapsulation technique to avoid poisoning the reserved sensors and an autonomous activation technique to replace a deteriorated sensor with a reserved sensor. Encapsulations of $In_2O_3$ nanoparticles with poly(ethylene-co-vinyl alcohol) (EVOH) or polyvinylidene difluoride (PVDF) as gas barrier layers are reported. The EVOH or PVDF films are used for an encapsulation of $In_2O_3$ as a sensing material and are effective in blocking $In_2O_3$ from contacting formaldehyde (HCHO) gas. The activation process of $In_2O_3$ by removing the EVOH through heating is effective. However, the thermal decomposition of the PVDF affects the property of the $In_2O_3$ in terms of the gas reactivity. The response of the sensor to HCHO gas after removing the EVOH is 26%, which is not significantly different with the response of 28% in a reference sample that was not treated at all. We believe that the selection of gas barrier materials for the encapsulation and activation of $In_2O_3$ should be considered because of the ill effect the byproduct of thermal decomposition has on the sensing materials and other thermal properties of the barrier materials.

• Korean Journal of Remote Sensing
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• v.6 no.2
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• pp.115-133
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• 1990

Study was made on the spectral characteristics of rock samples including bentonites collected from the northern Ulsan area. The geology of the area consists mainly of sediments of the Kyongsang Series and Bulguksa granite, the Tertiary volcanics, andesites and tuffs. Relative reflectances of meshed samples(2.5~10mm) to BaSO$_4$ are measured at 6 Landsat TM spectral windows (excluding the thermal band) with HHRR, and their reflection charactristics were analysed. In addition, three different data selection schemes including the Eulidean distance, multiple regression, and PCA weight methods were applied to the 30 TM ratio channels, derived from the above 6 bands. The selected data sets were subject to two unsupervised classification techniques(FA and ISODATA) in order to compare the effectiveness for classification of particularly bentonite from others. As a result, in ISODATA analysis the multiple regression model shows the best, followed by the Euliean distances one. The PCA weight model seems to show some confusion. In FA, though difficult for quantitative analysis, the best still seems to be the regression model. Among ratio bands, rations of band 7 or 5 against other bands represent the best contribution in classification of bentonites from others.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.63-69
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• 2017

This study is about the development of a smart bed control system to be able to detect the human position and body signal on bed. The main control board in the bed control system consists of the human sensing part, motor driving part and MCU. Here, to increase the credibility to check the human presence on bed, the human sensing part is combined with the human position part by membrane sensor and the body-signal detecting part of EMFI sensor. Also, remotely connecting the two detected signal to the application program of the app mode makes it possible to monitor human information on bed. In this paper, the remote function monitoring of the on-bed human information by bluetooth communication will be abe to make it applicable to the technical prevention method of the bed fall and absence accident in hospital and care facilities.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.79-93
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• 1993

The relative geostrophic velocity is estimated by using the MCSST(Multi-Channel Sea Surface Temperature) from a NOAA/AVHRR image and applied to the Korea Strait. Remote sensing technique can play a useful role to research for oceanic phenomena because of its synoptic, simultaneous and repetitive viewing. The high resolution data of AVHRR can determine the geostrophic flow more precisely than the hydrographic data on shipboard. As a result of research, the relative geostrophic velocity in the weatern channel of the Korea Strait is the strongest in the trough area and its maximum speed is about 23.8cm/sec in April, 1992. But this results include the error due to neglecting the effect of salinity in estimation the geopotential anomaly. The geostrophic volume transport through the western channel of the Korea Strait is the largest between trough area and the Tsushima Island.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.601-612
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• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.2
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• pp.197-203
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• 2001

Micro-defects induced by design and production failure or working environments are known as the cause of SCC(Stress Corrosion Cracking) in aged structures. Therefore, the evaluation of structural integrity based on micro-cracks is required not only a manufacturing step but also in-service term. So we introduce a new nondestructive inspection method using the magneto-optical film to detect micro-cracks. The method has some advantage such as high testing speed, real time data acquistion and the possibility of remote sensing by using of a magneto-optical film that takes advantage of the change of magnetic domains and domain walls. This paper introduces the concept of the new nondestructive inspection method using the magneto-optical film, also proves the possibility of this method as a remote testing system under oscillating load considering application on real fields by applying the method to four types of specimens.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.209-220
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• 2010

One of the most difficult tasks in measuring oceanic conditions is to produce oceanic current information. In efforts to overcome the difficulties, various attempts have been carried out to estimate the speed and direction of ocean currents by utilizing sequential satellite images. In this study, we have estimated sea surface current vectors to the south of the Korean Peninsula, based on the maximum cross-correlation method by using sequential ocean color images of SeaWiFS chlorophyll-a. Comparison of surface current vectors estimated by this method with the geostrophic current vectors estimated from satellite altimeter data and in-situ ADCP measurements are good in that current speeds are underestimated by about 15% and current directions are show differences of about $36^{\circ}$ compared with previous results. The technique of estimating current vectors based on maximum cross-correlation applied on sequential images of SeaWiFS is promising for the future application of GOCI data for the ocean studies.

• Proceedings of the KSRS Conference
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• v.1
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.