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Study on urban surface water extraction from heterogeneous environments using GF-2 remotely sensed images

  • role： First author第一作者
  • Affiliation：

    Yunnan Normal University, School of Tourism and Geography, Kunming 650500, China

    Yunnan Normal University, GIS Technology Research Center of Resource and Environment in Western China of Ministry of Education, Kunming 650500, China

    Yunnan Normal University, Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China

    Yunnan Normal University, Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China

  • Email：hongliang20433@hotmail.com
  • Introduction：洪亮，1981年生，男，副教授，研究方向为高分辨率遥感影像智能信息提取及应用。E-mail：hongliang20433@hotmail.com
HONG Liang1234,  
  • role： Corresponding author通信作者
  • Affiliation：

    Yunnan Normal University, School of Tourism and Geography, Kunming 650500, China

    Yunnan Normal University, GIS Technology Research Center of Resource and Environment in Western China of Ministry of Education, Kunming 650500, China

    Yunnan Normal University, Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China

    Yunnan Normal University, Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China

  • Email：huong66@163.com
  • Introduction：黄雅君，1991年生，男，硕士研究生，研究方向为定量遥感。E-mail：huong66@163.com
HUANG Yajun1234*,  
  • Affiliation：

    Yunnan Normal University, GIS Technology Research Center of Resource and Environment in Western China of Ministry of Education, Kunming 650500, China

    Yunnan Normal University, School of Information Science and Technology, Kunming 650500, China

YANG Kun25,  
  • Affiliation：

    Yunnan Normal University, School of Tourism and Geography, Kunming 650500, China

    Yunnan Normal University, GIS Technology Research Center of Resource and Environment in Western China of Ministry of Education, Kunming 650500, China

    Yunnan Normal University, Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China

    Yunnan Normal University, Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China

PENG Shuangyun1234,  
  • Affiliation：

    Yunnan Normal University, School of Tourism and Geography, Kunming 650500, China

    Yunnan Normal University, GIS Technology Research Center of Resource and Environment in Western China of Ministry of Education, Kunming 650500, China

    Yunnan Normal University, Center for Geospatial Information Engineering and Technology of Yunnan Province, Kunming 650500, China

    Yunnan Normal University, Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan, Kunming 650500, China

XU Quanli1234

résumé

The water index can suppress background noise and increase the separability of surface water. Thus, it has been widely used for surface water extraction. Traditional FCM clustering algorithm considers the uncertainty of ground objects without neighborhood spatial information, which is sensitive to background heterogeneity. On the basis of the shortcomings of traditional FCM clustering algorithms, this study proposed a regional FCM clustering algorithm and applied it to extract city surface water in complex environment regions using GF-2 remote sensing imagery. The main steps of the method include (1)Calculating the normalized difference water index after the removal of shadows; (2) Presenting a regional FCM clustering algorithm;(3)Proposing the urban surface water automatic extraction algorithm by combining the water body index and the regional FCM clustering algorithm. Finally, the proposed method was carried out on two GF-2 high-resolution remote sensing image data located in Guangzhou and Wuhan. The experimental results showed that the proposed method has better accuracy and water boundary than state-of-the-art methods. The proposed method also retains regional integrity and local details of surface water objects while effectively inhibiting noise from urban surface water in the complex background, thereby reducing the " salt and pepper” phenomenon found in traditional FCM clustering algorithm.

mots-clés

remote sensing;GF-2;urban surface water;normalized difference water index;Fuzzy clustering algorithm;FCM algorithm;region FCM clustering algorithm

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