• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.395-409
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• 2009

The objective of this paper is to illustrate that kriging can provide an effective framework both for integrating remote sensing data and for uncertainty modeling through a case study of sediment grain size mapping with remote sensing data. Landsat TM data which show reasonable relationships with grain size values are used as secondary information for sediment grain size mapping near the eastern part of Anmyeondo and Cheonsuman bay. The case study results showed that uncertainty attached to prediction at unsampled locations was significantly reduced by integrating remote sensing data through the analysis of conditional variance from conditional cumulative distribution functions. It is expected that the kriging-based approach presented in this paper would be efficient integration and analysis methodologies for any environmental thematic mapping using secondary information as well as sediment grain size mapping.

• Journal of Environmental Impact Assessment
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• v.18 no.4
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• pp.219-227
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• 2009

Because of urban development and changed land cover types, It is very important to acquire pixel unit of land surface temperature(LST) information when the heat island effect(HIE) of regional area are investigated. The brightness temperature observed by satellite is very useful for assessing the pixel unit of LST distributions for the analysis of thermal environment problems of urban areas. Also, satellite land cover data are very useful to our understanding of surface conditions of study areas. In this study, brightness temperature information of Landsat TM thermal channel was analyzed and compared with land cover information of Jeon-ju city. The atmospheric correction of TM thermal channel carried out to explain for compared LST long term monitoring errors. However, simple estimation and evaluation methods to find a physical relationship between LST from satellite images and in-situ data are compared with reference channel emissivity.

• Journal of Korea Water Resources Association
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• v.38 no.5 s.154
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• pp.391-399
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• 2005

The purpose of this study is to evaluate hydrological impact by the land cover change of typhoon damage. For the typhoon RUSA (rainfall 1,402 mm) occurred in 2002 (August $31\;{\sim}$ September 1), satellite images of Landsat 7 ETM+ of September 29, 2000 and Landsat 5 TM of September 11, 2002 were selected, and each land cover was classified for Namdae-cheon watershed $192.7km^2$ located in the middle-eastern part of Korea Peninsula. SCS unit hydrograph for watershed runoff and Muskingum for streamflow routing of WMS HEC-1 was adopted. 30m resolution DEM & hydrological soil group using 1:50,000 soil map were prepared. The model was calibrated using three available data of storm events of 1985 to 1988 based on 1985 land cover condition. To predict the streamflow change by damaged land cover condition, rainfall of 50 years to 500 years frequency were generated using 2nd quantile of Huff method. The damaged land cover condition treated as bare soil surface increased streamflow of $50.1\;m^3/sec$ for 50 years rainfall frequency and $67.6\;m^3/sec$ for 500 years rainfall frequency based on AMC-I condition. There may be some speedy treatment by the government for the next coming typhoon damage.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.201-211
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• 2017

The estuary in Nakdong River has changes by the construction of harbors, land reclamation and artificial waterway changes. These resultslead to changes of extinction and creation of deltaic barrier island. The deltaic barrier island changes in the Nakdong River estuary affect the function of the barrier islands and cause environmental changes. Therefore, it is important to monitor the changes in the area of the Nakdong estuary. In this study, long-term changes of the area and suspended sediment of deltaic barrier island in the Nakdong River estuary were analyzed using Landsat TM/ETM+ images. As a result, end point rate (EPR) values of shoreline in Jinwoodo and Sinjado are about 5m/yr and about 50 m/yr, respectively. The EPR values of north-south and east-west direction in Doyodeung are 20 m/yr and -20 ~ 10 m/yr. The suspended sediment concentration (SSC) has a maximum value of $25g/m^3$ in the vicinity of Jinwoodo and Sinjado, while it has a maximum concentration of $40g/m^3$ in the vicinity of Shinjido and Doyodeung. In other words, the area and the SSC change are small in Jinwoodo, and the area change and the SSC variation are large in Sinjado and Doyodeung. As a result of analysis of correlation between area change and SSC variation using all data, the Pearson coefficient value (r) is 0.36 and it is 0.32 in winter data. In other words, it is considered that the SSC variation affectsthe deltatic barrier island area change. However, verification using advanced altimetry data is necessary in the future. These studies can be used for coastal monitoring and environmental monitoring.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.185-191
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• 2007

Remote sensing images are multispectral image data collected from several band divided by wavelength ranges. The classification of remote sensing images is the method of classifying what has similar spectral characteristics together among each pixel composing an image as the important algorithm in this field. This paper presents a pattern classification method of remote sensing images by applying a possibilistic fuzzy c-means (PFCM) algorithm. The PFCM algorithm is a hybridization of a FCM algorithm, which adopts membership degree depending on the distance between data and the center of a certain cluster, combined with a PCM algorithm, which considers class typicality of the pattern sets. In this proposed method, we select the training data for each class and perform supervised classification using the PFCM algorithm with spectral signatures of the training data. The application of the PFCM algorithm is tested and verified by using Landsat TM and IKONOS remote sensing satellite images. As a result, the overall accuracy showed a better results than the FCM, PCM algorithm or conventional maximum likelihood classification(MLC) algorithm.

• 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.

• 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.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.128-133
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• 1998

To assess the flood damages and to provide necessary information for preventing future catastrophe, it is necessary to appraise the inundated area with more accurate and rapid manner. This study attempts to evaluate the potential of satellite synthetic aperture radar (SAR) data for mapping of flood inundated area in southern part of Korea. JERS L-band SAR data obtained during the summer of 1997 were used to delineate the inundated areas. In addition, Landsat TM data were also used for analyzing the land cover condition before the flooding. Once the two data sets were co-registered, each data was separately classified. The water surface areas extracted from the SAR data and the land cover map generated using the TM data were overlaid to determine the flood inundated areas. Although manual interpretation of water surfaces from the SAR image seems rather simple, the computer classification of water body requires clear understanding of radar backscattering behavior on the earth's surfaces. It was found that some surface features, such as rice fields, runaway, and tidal flat, have very similar radar backscatter to water surface. Even though satellite SAR data have a great advantage over optical remote sensor data for obtaining imagery on time and would provide valuable information to analyze flood, it should be cautious to separate the exact areas of flood inundation from the similar features.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.22-27
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• 1998

A grid-based soil moisture routing model(GRISMORM) was developed to assess the information of groundwater recharge using spatial data such as Landsat TM and digital elevation model etc.. The model predicts the hydrologic components, that is, surface runoff, subsurface runoff, baseflow and evapotranspiration at each grid elements by grid-based water balance computation.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.22-24
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• 2004

The land use has changed rapidly since 1960s in accordance with urbanization in Seoul Metropolitan Region. As a result, the urban microclimate has undergone changes as well. This study aims to recognize trend of the urban heat island change which is caused by land use change during urbanization in large city. Thermal data of Landsat TM images in 1987 and 1999 were for land surface temperature change detection in the study.