• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.81-93
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• 2008

Current re-arrangement of river and waterway has been made uniformly ignoring characteristics of individual rivers thereby aggravating artificial river restructuring. Subsequently this severely affects the rivers' physical, chemical, and biological phenomenon. On the contrary, quantitative techniques to evaluate the aftermath of artificial river disturbance such as uprising of river bed, intrusion of foreign fisheries, and changes of ecological habitats are not available. To establish such quantitative techniques, analysis of river changes to evaluate the major causes of the river disturbance and its impacts is essential. Therefore, this study mainly focused on proposing a method which can be applied for the development of techniques to investigate river disturbance according to the major factors for the domestic rivers using airphotos and GIS techniques. For the analysis, the study area on the downstream of the river was selected and airphotos of the area were converted into GIS format to generate 'shape' files to secure waterways, river banks, and auxiliary data required for analyzing river disturbance. Trend analysis of the waterway sinuosity and changes of the flow path leaded to detailed verification of the river disturbance for specific location or time period, and this enabled to relatively accurate numbers representing sinuosity of the waterway and relevant changes. As the major results from the analysis, the relocation of waterways and the level of river sinuosity were quantified and used to verify the impacts on the stability of the waterways especially in the downstream of the dam. The results from this study enabled effective establishing proper measures against waterways' unstability, and emphasized subsequent researches for identifying better alternatives against river disturbances.

• 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.