Please use this identifier to cite or link to this item:
|Title: ||Bathymetric mapping in Dong-Sha Atoll using SPOT data|
|Authors: ||Huang, Shih-Jen|
|Keywords: ||unsupervised classification|
|Issue Date: ||2017-01-17T06:40:20Z
|Publisher: ||Proceedings of ISRS 2006 PORSEC|
|Abstract: ||Abstract: The remote sensing data can be used to calculate the water depth especially in the clear and shallow water area. In this study, the SPOT data was used for bathymetric mapping in Dong-Sha atoll, located in northern South China Sea. The in situ sea depth was collected by echo sounder as well. A global positioning system was employed to locate the accurate sampling points for sea depth. An empirical model between measurement sea depth and band digital count was determined and based on least squares regression analysis. Both non-classification and unsupervised classification were used in this study. The results show that the standard error is less than 0.9m for non-classification. Besides, the 10% error related to the measurement water depth can be satisfied for more than 85% in situ data points. Otherwise, the 10% relative error can reach more than 97%, 69%, and 51% data points at class 4, 5, and 6 respectively if supervised classification is applied. Meanwhile, we also find that the unsupervised classification can get more accuracy to estimate water depth with standard error less than 0.63, 0.93, and 0.68m at class 4, 5, and 6 respectively.|
|Appears in Collections:||[海洋環境資訊系] 期刊論文|
Files in This Item:
There are no files associated with this item.
All items in NTOUR are protected by copyright, with all rights reserved.