• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.298-300
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• 2003

A management information system of the Nanji Islands National Marine Reserve is designed and constructed based on method of integration of remote sensing and geographic information system (GIS). The system consists of two sub-systems, dynamic monitoring information system and general database system. The former is used for storage and manage fundamental geographical data (topographical and bathymetric map), satellite remote sensing data (IKONOS, SPOT, IRS, NOAA and SeaWiFS etc.) and multimedia data. The latter is used for storage and manage resource data (shellfish and alga etc.), environmental data (meteorological and hydrologic) and in situ data. As part of electronic government, this system will be submitted to local government for monitoring, management and decision.

• Proceedings of the KSRS Conference
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• v.2
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• pp.981-984
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• 2006

Oil pollution of the ocean is a major environmental problem, especially in its coastal zones. Synthetic aperture radar (SAR) flown on satellites, such as ERS-2 and Envisat, has been proved to be a useful tool in oil spill monitoring due to its wide coverage, day and night, and all-weather capability. The total 120 SAR images containing oil spill over the East China Sea were collected and analyzed, ranging in date from July 23, 2002 to November 11, 2005. After preprocessed, SAR images were segmented by adaptive threshold method. The oil spill images were incorporated into GIS after distinguished from look-like phenomena, finally we presented the oil spills distribution map for the East China Sea. The wide-swath and quick-looks SAR imagery for mapping of oil spill distribution over large marine areas were proved to be useful when full resolution data are not available. After the temporal and spatial distribution of the oil spills were analyzed, we found that most of oil spills were distributed along the main ship routes, which means the illegal discharge by ships, and the occurrence of oil spill detected on SAR images acquired during morning and summer is much higher than during evening and winter.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.450-453
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• 2005

A forest fire occurs mainly as natural factor such as wind, temperature or human factor such as light. Recently, the most of forest fire prevention is prediction or prevision against forest fire by using remote sensing technology. However in order to forest fire prevention, the remote sensing has many limitations such as high cost and advanced technologies and so on. Therefore, we need to multisensor integration system that utilize not only remote sensing but also in-situ sensing in order to reduce large damage of forest fire though analysis of happen cause and prediction routing of occurred forest fire. In this paper we propose a multisensor integration system that offers prediction information of factors and route of forest fire by integrates collected data from remote sensor and in-situ sensor for forest fire prevention. The proposed system is based on wireless sensor network for collect observed data from various sensors. The proposed system not only offers great quality information because firstly, raw data level fuse different format of collected data from remote and in-situ sensor but also accomplish information level fusion based on result of first stage. Offered information from our system can help early prevention of factor and early prevision against occurred forest fire which transfer to SMS service or alert service into monitoring interface of administrator.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.59-64
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• 2001

The objectives of the thesis are to propose a pattern classification method for remote sensing data using artificial neural network. First, we apply the error back propagation algorithm to classify the remote sensing data. In this case, the classification performance depends on a training data set. Using the training data set and the error back propagation algorithm, a layered neural network is trained such that the training pattern are classified with a specified accuracy. After training the neural network, some pixels are deleted from the original training data set if they are incorrectly classified and a new training data set is built up. Once training is complete, a testing data set is classified by using the trained neural network. The classification results of Landsat TM data show that this approach produces excellent results which are more realistic and noiseless compared with a conventional Bayesian method.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.345-357
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• 2001

This review provides a summary of data assimilation applied to the seas around Korea. Currently the worldwide efforts are devoted to applying advanced assimilation to realistic cases, thanks to improvements in mathematical foundations of assimilation methods and the computing capabilities, and also to the availability of extensive observational data such as from satellites. Over the seas around Korea, however, the latest developments in the advanced assimilation methods have yet to be applied. Thus it would be timely to review the progress in data assimilation over the seas. Firstly, the definition and necessity of data assimilation are described, continued by a brief summary of major assimilation methods. Then a review of past research on the ocean data assimilation in the regional seas around Korea is given and future trends are considered. Special consideration is given to the assimilation of remotely-sensed data.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.140-143
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• 2004

The west coast of the Korean Peninsula is famous for its large tidal range (up to 9 m) and vast tidal flats. With comparison the sedimentary environments of open and close tidal flat using remote sensing, we select Kanghwa tidal flat and Hwang-Do tidal flat in Cheonsu Bay. Prior to surface sediment discrimination using remote sensing, sedimentary environments including intertidal OEM, hydraulic condition, and relationship between grain size and various tidal condition are investigated. Remote sensing has the potential to provide synoptic information of intertidal environments. The objectives of this study are: (i) to generate an intertidal digital elevation model (OEM) using the waterline method of Lansat TM/ETM+, (ii) to investigate the tidal channel distribution using texture analysis, and (iii) to analyze the relationship between surface grain size by using in-situ data and intertidal OEM and tidal channel density by using high-resolution satellite data such as IKONOS and Kompsat EOC. The results demonstrate that satellite remote sensing is an efficient and effective tool for a surface sediment discrimination and long term morphologic change estimation in tidal flats.

• Proceedings of the KSRS Conference
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• v.1
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• pp.455-458
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• 2006

Stretching on the coastline of 70 km, the Tam Giang - Cau Hai Lagoon plays a very important role for the coastal ecology and socio-economic development of Hue region where was Vietnam's Ancient Kingdom Capital and recognized as a World's Cultural Heritage. Recently, coastal hazard in the lagoon have occurred seriously such as inlet movement and fill up, coastal erosion, flood and inundation, etc. These hazards have impacted on lagoon environment, resources, ecosystems, socio-economic and sustainable development of this coastal area. This paper present a case study using remote sensing data in combination with ground survey for monitoring the coastal hazards in Tam Giang - Cau Hai lagoon in recent decades. Analysis results find that during its natural evolution, the lagoon has been being in three situations of only one, two and three inlets. When inlets opened or displaced, coastal erosion have occurred seriously toward new balance condition. Flood and inundation occurs every rainy season in lowland plain around lagoon. The historical flood happened in early of November 1999 with six days long, created very terrible damages for Thua Thien Hue province. Remote sensing data with capability of regular update, large area coverage is effective provide real-time and continuous information for coastal hazards monitoring.

• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• Current Industrial and Technological Trends in Aerospace
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• v.9 no.1
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• pp.45-54
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• 2011

Earth observation satellites data apply to various fields and global satellite imagery market continues to expand with increasing the scale according to the developed satellites. Sudden natural disasters frequently have occurred in Japan. ALOS satellite data support to repair the damaged area and mitigate the disasters in Japan as well as all around the world. In this paper, the status of remote sensing and data policy in Japan are described. In addition, satellite-based remote sensing technology effectively contribute to the public sector and related support to establish the infra system of satellite application promotion has been investigated.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.113-119
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• 2003

Building information is extremely important for many applications within the urban environment. Sufficient techniques and user-friendly tools for information extraction from remotely sensed imagery are urgently needed. This paper presents an automatic and manual approach for extracting footprints of buildings in urban areas from airborne Light Detection and Ranging (LIDAR) data. First a digital surface model (DSM) was generated from the LIDAR point data. Then, objects higher than the ground surface are extracted using the generated DSM. Based on general knowledge on the study area and field visits, buildings were separated from other objects. The automatic technique for extracting the building footprints was based on different window sizes and different values of image add backs, while the manual technique was based on image segmentation. A comparison was then made to see how precise the two techniques are in detecting and extracting building footprints. Finally, the results were compared with manually digitized building reference data to conduct an accuracy assessment and the result shows that LIDAR data provide a better shape characterization of each buildings.