• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.101-108
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• 2002

The studies using satellite data have been progressed in many area. Especially, Landsat data have been widely used due to its wide coverage. To establish a plan for preserving fishing and environment preservation, measurement of sea temperature is important. The measurement of the sea temperature was made on the ship. However, the measurement on the ship could not provide sufficient information due to the poor timing with relatively longer measurement, and point-based data acquisition. Thus remote sensing technique is required because satellite image data offer more wide coverage in sea temperature monitoring. The purpose of this paper was to study on the sea temperature monitoring with thermal band information of Landsat ETM+. From this study, sea temperature map of Cheju island has been made efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.856-859
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• 2010

WSN is composed of a lot of small sensors with the limited hardware resources. In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in Mobile-WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative Mobile-WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a self-configuration routing protocol for Mobile-WSN, which consists of step-wise novel protocols for initial deployment, effective joining and removal of sensor nodes, which result in reducing overall power consumption, and extending the lifetime of network.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.27-34
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• 2013

In wireless sensor networks, sensors need to communicate with each other to send their sensing data to the administration node and so they are susceptible to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic approaches. A behavior-based detection is used to defend against such attacks in which some specialized monitoring nodes overhear the communications of their neighbors to detect bad packets. As monitoring nodes use more energy, it is desirable to use the minimal number of monitoring nodes to cover the whole or maximal part of the network. The monitoring nodes can either be selected among the deployed normal nodes or differ in type from normal nodes. In this study, we have developed an algorithm for selecting the predefined number of monitoring nodes needed to cover the maximum number of normal nodes when the different types of normal nodes and monitoring nodes are deployed. We also have investigated experimentally how the number of monitoring nodes and their transmission range affect the connection ratio of the monitoring nodes and the coverage of the normal nodes.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.287-305
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• 2016

Over the past half century, satellites have continuously expanded their roles in remote sensing applications. As the number of satellites to be launched are expected to continuously increase in coming years, the research on satellite payloads will be in high demands. Earth Observation (EO) satellites are nowadays widely utilized for various purposes. Especially, Agriculture and forestry applications are considered as their major application areas. Since about 85% of domestic land cover is classified as forest or cropland areas, it would be reasonable to suggest that the demand for these satellites should be of high priority. In this paper, a comprehensive analysis is performed on the technical specifications of satellite payloads that may be applicable to agricultural applications. We attempted to build a solid database on payload specifications by collecting relevant information available from various related institutes and academic research works. A number of experts involved in national agricultural research and satellite development programs have been invited to investigate required payload design. Based on the current technology development status and future plan, multiple options for future satellite payload designs have been suggested bearing in mind that the results may be applicable to the future agriculture and forestry satellite payload design. The proposed payload specifications are analyzed in depth through satellite operation simulations under the mission of observing the national agriculture areas. The proposed design scheme and simulation results may be used as technical references to satellite payload design for future space missions.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.103-119
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• 2020

Recently, the rapid redeposition and erosion of rivers artificially created by climate change and the Four Rivers Restoration Project is questionable. According to the revised law in Korea, the river management agency will periodically carry out bed changes surveys. However, there are technical limitations in contrast to the trend of increasing spatial coverage, density and narrowing of intervals. National organizations are interest in developing innovative bed changessurvey techniquesfor efficiency. Core of bathymetry survey is to measure the depth of rivers under a variety of river conditions, but that is relatively more risky, time-consuming and expensive compared to conventional ground surveys. To overcome the limitations of traditional technology, echo sounder, which has been mainly used for ocean depth surveying, has been applied to rivers. However, due to various technical limitations, it is still difficult to periodically investigate a wide range of areas. Therefore, technique using the remote sensing has been spotlighted as an alternative, especially showing the possibility of depth measurement using spectral characteristics. In this study, we develop and examine a technique that can measure depth of water using reflectance from spectral characteristics. As a result of applying the technique proposed in thisstudy, it was confirmed that the measured depth and the correlation and error corresponding to 0.986 and 0.053 m were measured in the depth range within 0.95 m. In the future, this study could be applied to the measurement of spatial depth if it is applied to the hyperspectral sensor mounted on the drone.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.429-437
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• 2013

Recently, wireless mesh network has been focused as a core technology for resolving the issues of shadow zone and distributed bypass route as it has broad service coverage as well as good scalability features. It, however, provides users with relatively lower QoS than infrastructure-based networks. In order for addressing this QoS issue and also enhancing the routing performance of mobile WiMax mesh network, this paper proposes a load sensing QoS routing (LSQR) scheme. In the proposed LSQR, each node figures out network congestion status and selects a bypass route accordingly. With this scheme, we can expect good load balancing effect by changing the routing paths from centralized links to distributed links under a heavy traffic condition. From the simulation results using NS-2, it has been verified that the LSQR shows lower packet loss rates and data transmission delays than the existing representative routing schemes.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.653-662
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• 2011

Land surface temperature (LST) is a one of the key variables of land surface which can be estimated from geostationary meteorological satellite. In this study, we have developed the three sets of LST retrieval algorithm from MTSAT-2 data through the radiative transfer simulations under various atmospheric profiles (TIGR data), satellite zenith angle, spectral emissivity, and surface lapse rate conditions using MODTRAN 4. The three LST algorithms are daytime, nighttime and total LST algorithms. The weighting method based on the solar zenith angle is developed for the consistent retrieval of LST at the early morning and evening time. The spectral emissivity of two thermal infrared channels is estimated by using vegetation coverage method with land cover map and 15-day normalized vegetation index data. In general, the three LST algorithms well estimated the LST without regard to the satellite zenith angle, water vapour amount, and surface lapse rate. However, the daytime LST algorithm shows a large bias especially for the warm LST (> 300 K) at day time conditions. The night LST algorithm shows a relatively large error for the LST (260 ~ 280K) at the night time conditions. The sensitivity analysis showed that the performance of weighting method is clearly improved regardless of the impacting conditions although the improvements of the weighted LST compared to the total LST are quite different according to the atmospheric and surface lapse rate conditions. The validation results of daytime (nighttime) LST with MODIS LST showed that the correlation coefficients, bias and RMSE are about 0.62~0.93 (0.44~0.83), -1.47~1.53 (-1.80~0.17), and 2.25~4.77 (2.15~4.27), respectively. However, the performance of daytime/nighttime LST algorithms is slightly degraded compared to that of the total LST algorithm.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.505-510
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• 2014

Normalized Difference Vegetation Index (NDVI) is a major indicator for monitoring climate change and detecting vegetation coverage. In order to retrieve NDVI, it is preprocessed using cloud masking and atmospheric correction. However, the preprocessed NDVI still has abnormally low values known as noise which appears in the long-term time series due to rainfall, snow and incomplete cloud masking. An existing method of using polynomial regression has some problems such as overestimation and noise detectability. Thereby, this study suggests a simple method using amoving average approach for correcting NDVI noises using SPOT/VEGETATION S10 Product. The results of the moving average method were compared with those of the polynomial regression. The results showed that the moving average method is better than the former approach in correcting NDVI noise.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.340-343
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• 2004

Since the tide embankment construction started in 1991, the coastal environment in and around the Saemangeum area has undergone changes rapidly, there is a need for monitoring the environmental change in this region. Owing to high temporal and spatial heterogeneity of the coastal ecosystem and processes as well as the expense with traditional filed sampling at discrete locations, satellite remote sensing measurements offer a unique perspective on mapping a large region simultaneously because of the synoptic and repeat coverage and that quantitative algorithms used for estimating constituents' concentration in the coastal environments. Thus, the main objectives of the present study are to analyze the retrieved Suspended Sediment (SS) pattern to predict changes after the commencement of the tide embankment construction work in 1991. This is accomplished with a series of the Landsat TM/ETM+ imagery acquired from 1985-2002 (a total of 18 imageries). Instead of a simple empirical algorithm, we implement an analytical SS algorithm, developed by Ahn et al. (2003), which is especially developed for estimating SS concentration (SSC) in Case-2 waters. The results show that there is a significant change in SS pattern, which is mainly influenced by the tide and tidal height after the construction of the embankment work. As the construction progressed, the distribution pattern of SS has greatly changed, and the rate of SS concentration in the gap area of the dyke of post-construction has significantly increased.

• Proceedings of the KSRS Conference
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• v.1
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• pp.90-93
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• 2006

The first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. The special feature with GOCI is that like MODIS, MERIS and GLI, it will include the band triplets 660-680-745 for the measurements of sun-induced chlorophyll-a fluorescence signal from the ocean. The GOCI will provide SeaWiFS quality observations with frequencies of image acquisition 8 times during daytime and 2 times during nighttime. With all the above features, GOCI is considered to be a remote sensing tool with great potential to contribute to better understanding of coastal oceanic ecosystem dynamics and processes by addressing environmental features in a multidisciplinary way. To achieve the objectives of the GOCI mission, we develop the GOCI Data Processing System (GDPS) which integrates all necessary basic and advanced techniques to process the GOCI data and deliver the desired biological and geophysical products to its user community. Several useful ocean parameters estimated by in-water and other optical algorithms included in the GDPS will be used for monitoring the ocean environment of Korea and neighbouring countries and input into the models for climate change prediction.