碩士 / 國立中央大學 / 遙測科技碩士學位學程 / 103 / Suspended sediment concentration (SSC) is an important indicator of sediment output. Recently, some SSC predictions had been carried out by using optical satellites imagery in different areas. In general, the more suspension sediment in water can directly reflect the higher reflectance of solar radiation. Therefore, most studies developed unique relationships by relating field measurements of SSC to reflectance data from satellite imagery. In this study, we focused on the Pinan River estuary which is born from the largest river in eastern Taiwan. In order to identify an appropriate SSC-reflectance model, we combined our optical satellite images, which included FORMOSAT-2, SPOT-4, SPOT-5 and SPOT-6, with the field data from 2005 to 2013. After doing atmospheric correction, we got the best model with Multiple Regression analysis method. The important thing is that the method has more accurate in predicting SSC, after proving our model with the latest field data in 2014. In the final part, we used the model to resupply the SSC data in 2011, and discussed the characteristics of sediments output with rainfall and discharge. Actually, it is useful for us to replace those stations to get the SSC distribution outside the estuary. And, there are several hyperpycnal flow events occurred at the bottom of the estuary, while the SSC exceeding the threshold (40,000ppm). We also discussed the characteristic of spectral and the source of errors from environment effects. While getting more ways to reduce those noises, we could have better model to predict the SSC. At the same time, it also could enhance the frequency and range of monitoring, and make up for a lack of manual monitoring.
| Identifer | oai:union.ndltd.org:TW/103NCU05105063 |
| Date | January 2015 |
| Creators | Yu-shiang Wang, 王禹翔 |
| Contributors | Chung-pai Chang, 張中白 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 121 |
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