Issue |
E3S Web Conf.
Volume 213, 2020
2nd International Conference on Applied Chemistry and Industrial Catalysis (ACIC 2020)
|
|
---|---|---|
Article Number | 03024 | |
Number of page(s) | 4 | |
Section | Environmental Chemical Research and Energy-saving Technology Application | |
DOI | https://doi.org/10.1051/e3sconf/202021303024 | |
Published online | 01 December 2020 |
The method for water body information extraction in complex environment using GF-1 WFV images
1
Marine Science and Technology College, Zhejiang Ocean University, Zhoushan, 316022, China
2
School of Economics and Management, Zhejiang Ocean University, Zhoushan, Zhejiang 316022, China
* Correspondence: chuyanli_shandong@163.com
Water body is one of the most active and important earth resources, and which has a profound impact on the natural system and human society. In order to acquire surface water body information quickly, accurately and efficiently, the method of water body information extraction using remote sensing imagery has attracted the attention of many searchers. On the basis of sorting out relevant research results of water body information extraction using remote sensing imagery, this paper proposed the method of water body information extraction based on the tasseled cap transformation for complex environments such as shadow and dense vegetation. First, radiometric calibration and atmospheric correction were carried out for remote sensing images. Then, the tasseled cap transformation was performed to obtain the greenness component and wetness component. Finally, the model of water body information extraction based on the tasseled cap transformation was constructed, and the water body information was extracted. In a region of Hunan province, China, the experiment using GF-1 WFV remote sensing image shows that the extracted water body information has a clear boundary and complete shape, and the Kappa coefficient, overall accuracy and user accuracy are 0.89, 92.72%, and 88.04%, respectively.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.