• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.394-397
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• 2005

This study aims to estimate a heat island potential distribution based on the land-use types using LANDSAT/TM(1100LST April 2000) and AWS data in Daegu. The heat island potential is defined as a difference between surface temperature and air-temperature at each place. The study area was selected as about $900k km^2$ square including Daegu metropolitan area. Land-use data obtained by dividing all of Daegu metropolitan area into l-km-square three types of maps were prepared, in the 1 960s, 1970s and 2000s respectively. The types of land-use were divided into 5. Forest and farm lands have been reduced at a wide range during 40 years, most of which changed to urban area. The heat island potential distribution presented a striking contrasts according to land-use types. For example, the heat island potential of urban area was higher than $14^{\circ}$ in comparison to those of water or paddy rice areas.

• Journal of Environmental Science International
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• v.16 no.1
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• pp.65-71
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• 2007

This study aims to estimate a urban heat island potential distribution based on the land-use types using Landsat TM(1100 LST August 2004) and AWS data in Daegu. The heat island potential is defined as a difference between surface temperature and air-temperature at each place. The study area was selected as about $900km^2$ square including Daegu metropolitan area. Land-use data obtained by dividing all of Daegu metropolitan area in- to 1-km-square three types of maps were prepared in the 1960s, 1970s and 2000s respectively. Land-use types were classified into 5 categories. Forest and farm lands have been reduced at a wide range during 40 years. Most of those changed into urban area. The heat island potential distribution presented a striking contrasts according to land-use types. For example, the heat island potential of urban area was higher than $10^{\circ}C$ in comparison to those of water or paddy rice areas.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.303-315
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• 2012

This study developed a wetland inventory describing the characteristics and change of Nakdong estuary wetland ecosystem. The data which are used to develop the inventory are Landsat TM(April 1, 1986; June 23, 1987; June 18, 1997), Kompsat(Jan. 12, 2008) and LiDAR(March 1, 2009) images and published monitoring data of Busan metropolitan city. The developed inventory was utilized for the classification of wetland cover, the spatiotemporal analysis of wetland and landscape pattern, the distribution of benthos species etc. Furthermore, the developed 3 dimensional wetland map showed a better way to delineate wetland boundary and understand wetland dynamics. Considering these results, it's concluded that it is possible to use the similar techniques for the development of wetland inventory in Korea.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.237-248
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• 1998

Landcover has been largely influenced by human activities, especially in recent days. The analysis of the change of land use by urbanized development is useful for determining development plan hereafter. This study aimed to the quantitative analysis about the urban sprawl within 12 years from 1985 to 1996, at Chonan, and for extracting the characteristics of change. For this purpose, this study performed land cover classifications using Landsat TM data . A hybrid classification method was used to classify satellite images into seven types of land cover. Road network digitied from 1:25,000 topographic map was rasterized and overlaid on the landcover map. A result of this study showed that area of forest and paddy decreased due to urban sprawl. Especially from 1993 to 1996, the change of land use progressed rapidly because of merging a city and a country in Chonan. The size of patch in forest had been smaller and irregular form. It is a general progress that size of patch in forest had been smaller and irregular form. It is a general progress that the forest have changed the paddy and bare land paddy and bare land have changed low-density urban or high-density urban. This explained how urbanized Chonan was and applied the suggeston of plan in landuse with the result of this study.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.80-91
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• 2003

In this research, re-using band ratio data was proposed and examined as a method of raising the accuracy in landcover classification which is using satellite data.In order to determine the band which is used to calculation in the classified item, the six bands except the band 6 were combined with the band in which combination is possible and the landcover classification by MLC of supervised classification was carried out. In the result of landcover classification which is combined with forty nine combination, Two bands which were mostly used by band combination in the accuracy belonged inside the 10th place of a higher rank were selected and also calculated. landcover classification were performed again after the calculation result had been recombinated from the research. In addition, the new landcover classification result was compared and examined with the landcover classification using the old data. From the result of which was compared and examined the new landcover classification data recombinated calculation result with landcover classification using the original data, The classification accuracy of the new landcover classification data recombinated calculation result became low in ground but became improved in the all class. Specially The accuracy to urban area is very improved. therefore, it determined that reusing band ratio data is very useful when we need to analyze landcover classification and land information to urban area after that.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.449-451
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• 2007

In the commercially managed timber lands, the information such as height, age, stand density, canopy closure and leaf area index need to be collected periodically. Stand volume is the most fundamental information in the valuation of timber, however, stand age information is the primary element of forest inventory and these two are highly correlated. Conventional method of collecting stand age information by field surveys such as ring count method is accurate; however, it is expensive, labor-intensive and time consuming. In the present study it was aimed to collect stand age information using modem techniques in a commercially managed timberland situated in Tennessee, USA. The Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) of three different periods, Shuttle Radar Topography Mission (SRTM), National elevation dataset (NED) and field inventory data were used. Normalized difference vegetation index (NDVI) and Tasselled Cap (TC) transformation techniques were applied on the TM and ETM+ data. The regression analysis was carried out to identify the correlation between stand age and NDVI, TC. In the present study about 2,469 datasets were analyzed. The $R^{2}$ value for stand age estimation was 0.713. The NDVI, TC2 and TC3 were found to produce accurate timber age information.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• KCID journal
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• v.7 no.2
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• pp.34-48
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• 2000

The tidal land reclamation schemes and projects located along the western coast of North Korea were investigated by the remote sensing using sattelite image data such as Landsat TM and Jers-1 data. North Korea reported their ambitious territory expansion