Extraction of plateau lake water bodies based on an improved FCM algorithm
Extraction of plateau lake water bodies based on an improved FCM algorithm
复制标题
基于改进FCM算法的高原湖泊水体提取
DOI：
10.3233/jifs-210526
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发表时间：
2021
影响因子：
2
通讯作者：
Qiu Lidan
中科院分区：
文献类型：
--
作者：
Li Yingxin;Li Shihua;Peng Shuangyun;Zhao Shoulu;Yang Wenxian;Qiu Lidan
高原湖泊水体的变化是全球生态系统变化的一个重要指标，及时、准确地掌握这一变化信息可为相关政策的制定提供科学参考。传统的模糊C均值（算法，此处似乎不完整，原文可能还有后续内容）
Changes in plateau body lake water are an important indicator of global ecosystem changes, and a timely and accurate grasp of this change information can provide a scientific reference for the formulation of relevant policies. The traditional fuzzy C-means clustering (FCM) algorithm takes into account the ambiguity of the classification of the ground object pixels but does not consider the rich spectral information of the neighboring pixels and is very sensitive to the background noise” of the remote sensing image, resulting in low water extraction accuracy. Aiming to compensate for the shortcomings of the traditional FCM algorithm, this paper proposes an improved FCM algorithm. This algorithm replaces the Euclidean distance of the traditional FCM algorithm with a combination of the Mahalanobis distance and spectral angle matching (SAM) to fully take into account the spectral information of neighboring pixels and improve the clustering accuracy. The study selected Sentinel-2 images of the Fuxian Lake and Xingyun Lake basins during normal, wet, and dry periods as the data source. Under the same conditions, the clustering accuracy was compared with the traditional FCM algorithm, improved FCM algorithm, K-means clustering method and iterative self-organizing data analysis (ISODATA) clustering method. The experimental results show that the improved FCM algorithm has a higher water extraction accuracy than the traditional FCM algorithm, K-means clustering method and ISODATA clustering method. The kappa coefficient and overall accuracy (OA) of the improved FCM algorithm can be increased by 5.56%–9.45% and 2.66%–5.32%, respectively, and the omission error and commission error can be reduced by 1.72%–4.55% and 12.14%–22.10%, respectively. When the improved FCM algorithm is used, the extraction accuracy is higher for plateau deep lakes than for plateau shallow lakes, and the extraction effect for lakes with poor water environments is more significant than that of other methods. The improved FCM algorithm better maintains the integrity of the water boundary and overcomes the influence of a certain number of mountain shadows and urban building pixels on the clustering results.
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DOI：
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发表时间：
2013
期刊：
Journal of Northwest A & F University
影响因子：
--
作者：
Yusufujiang Rusul
通讯作者：
Yusufujiang Rusul
DOI：
10.1109/igarss.2016.7729733
发表时间：
2016-07
期刊：
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
影响因子：
--
作者：
Heshan Lin;Jinyan Xu;Degang Jiang;Yikang Gao;Lianhuan Wei;Jianhui Liu
通讯作者：
Heshan Lin;Jinyan Xu;Degang Jiang;Yikang Gao;Lianhuan Wei;Jianhui Liu
DOI：
--
发表时间：
2016
期刊：
--
影响因子：
--
作者：
Zhou Dongxu;Z. Xinghua;Lei Ning;Wang Zhaoyang;Tang Qiuhua
通讯作者：
Zhou Dongxu;Z. Xinghua;Lei Ning;Wang Zhaoyang;Tang Qiuhua
DOI：
--
发表时间：
2019
期刊：
--
影响因子：
--
作者：
Z. Xiaoqiang;Ding Jianli;Xia Nan;Guo Jiaxin;Zhang Shuxia;Yang;Tongtong;Wang Jingzhe;Li Xiaohang
通讯作者：
Z. Xiaoqiang;Ding Jianli;Xia Nan;Guo Jiaxin;Zhang Shuxia;Yang;Tongtong;Wang Jingzhe;Li Xiaohang
DOI：
10.11947/j.agcs.2016.20150621
发表时间：
2016-12
期刊：
--
影响因子：
--
作者：
W. Shaoyu;Jiao Hongzan;Zhong Yanfei
通讯作者：
W. Shaoyu;Jiao Hongzan;Zhong Yanfei