• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.407-413
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• 2006

To investigate the streamflow impact of land cover changes by a typhoon, HEC-l storm runoff model was applied by using land cover information before and after the typhoon. The model was calibrated with three storm events of 1985 to 1988 based on 1985 land cover condition for a $192.7km^{2}$ watershed in northeast coast of South Korea. After the model was tested, it was run to estimate impacts of land cover change by the typhoon RUSA occurred in 2002 (31 August-1 September) with 897.5 mm rainfall. The land covers before and after the typhoon were prepared using Landsat 7 ETM+ of September 11 of 2000 and Landsat 5 TM of September 29 of 2002 respectively. For the $6.9km^{2}$ damaged area (3.6 % of the watershed), the peak runoff and total runoff by the changed land cover condition increased 12.5 % and 12.7 % for 50 years rainfall frequency and 1.4 % and 1.8 % for 500 years rainfall frequency respectively based on AMC (Antecedent Moisture Condition)-I condition.

• Korean Journal of Remote Sensing
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• v.11 no.2
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• pp.59-73
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• 1995

The study is focused on the analysis of geomorphological environment changes of alluvial bar in lower Kum river using satellite-based multitemporal/multisensor data. Landsat datas for environment changes analysis consists of Landset MSS(2 scenes) and Landset TM(7 scenes) acquired from 1979 to 1994. This study is to develop the analysis techniques for the environment change detection of using ratio, classification, false color composite etc, of Landsat data especially useful to the geomorphological study of tidal flats and river channels. The results of this study can be summarized as follows : 1. The lower Kum River alluvial bar have had rapid geomorphological changes after the construction of the temporary dam to block the river flowing in 1983. The most alluvial bar located in the river has both bankway growth, especially the allurival bar in the Lower Kum River had grown between 1983 to 1990. 2. After construction of the estuarine barrage, no remarkable geomorphological changes have been found in Kum River area but the growth and formation of new underwater bar has continued. The enormous materials was needed for the growth and formations of new underwater barrier oslands and bar would be supplied from the sea bottom and river sediment to diminish of stream velocity after construction of the estuarine barrage.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.281-286
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• 2006

In this study, acquired time series Landsat TM/ETM+ image to extract land surface temperature for wide-area region and executed geometric correction and radiometric correction. And extracted land surface temperature using NASA Model, and I achieved the first correction by perform land coverage category for study region and applies characteristic emission rate. Land surface temperature that acquire by the first correction analyzed correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two datas using establishing correction formula. As a result, land surface temperature that acquire by 1,2th correction could correct in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, could acquire land surface temperature about study region by relative high accuracy by applying to other Landsat image for re-verification of study result.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2184-2189
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• 2009

China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.

• Journal of Environmental Impact Assessment
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• v.3 no.1
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• pp.77-82
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• 1994

A Nationwide survey of ecosystem in the Republic of Korea was accomplished from 1986 to 1990 and in that survey, GIS and remote sensing were used partially. This was done by the Ministry of Environment(MOE), which introduced remote sensing and GIS for environment management in late 1980's. Especially the National Institute of Environmental Research (NIER) are under the research on systematization of environmental information with an ultimate goal of application of GIS and remote sensing to environmental impact assessment. Although the Korean peninsula is in a non-tropical zone, we introduce two case studies on remote sensing applications to ecosystem managements in the Republic of Korea. One is a study on change detection in urban vegetation of Seoul with Landsat data and the other is a study on detection of insect damaged pine tree area using Landsat TM data. The techniques involved and the conclusion from these studies were relevant to vegetation studies in tropical ecosystem.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.419-422
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• 2004

This paper was carried out desertification area change detection from 1980s to 2000s per unit decade using by multitemporal satellite images (Landsat MSS, TM, ETM+). This study aims to use Spectral Mixture Analysis (SMA) to identify and classify study area. Endmembers is selected bare soil, green vegetation (GV), water body using by Minimum Noise Fraction (MNF). Endmembers used to generate increase and decrease images respective from 1980s to 1990s and from 1990s to 2000s. From the analysis of multitemporal change detection for three periods, it was apparent that the area of bare soil increased significantly, with simultaneous decrease of GV and water body. The multitemporal fraction images can be effectively used for change detection. Though there is no field survey dataset, SMA is reliable result of change detection in desertification in China.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1239-1241
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• 2003

This paper presents the results of Landsat-TM imagery applications for detecting spatial variations of the water environments in the Saemankeum (STLR) project areas. The simulated tidal flow patterns from a two -dimensional hydro - dynamic model and water quality data from STRL project were used for relationships with the satellite data. Unsupervised classification of the tidal water body reflects the overall flow patterns at a flooding tide. Regressive equations for water quality parameters were derived and used for supervised classifications. The results were found to be useful to synoptically evaluate the water environments during the construction stages of the STLR project.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.579-581
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• 2003

Recently, the environment of the Ariake Sea, Japan has changed drastically. In this study, the result of sea survey, synchronizing the passage time of the Landsat in August 2002 was collated with the satellite data to develop the evaluating equation for transparency and sea surface temperature (SST). By Applying these equations to 5 satellite images of the same season, the transparency and SST in summer of 1985, 1991, 1996 and 2000 is estimated. Consequently, the transparency had increased until 2000 and then decreased in 2002. The SST, on the other hand, shows no remarkable trend.