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Mapping and dynamic changes of refined vegetation distribution in Xisha Islands

  • role： First author第一作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：sunxh2017@radi.ac.cn
  • Introduction：孙晓慧，1995年生，女，硕士研究生，研究方向为资源环境遥感应用。E-mail： sunxh2017@radi.ac.cn
SUN Xiaohui12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Ecological Environment Monitoring Center, Hainan Provincial, Haikou 571126, China

  • Email：stanking16888@163.com
  • Introduction：史建康，1980年生，男，高级工程师，研究方向为生态调查与评估。E-mail：stanking16888@163.com
SHI Jiankang3*,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

LI Xinwu1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

WU Wenjin1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

LIANG Lei1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

GONG Chen1

resumen

The Paracel Islands is the largest island with the largest number of islands in the South China Sea Islands. They have a unique natural environment and particular natural flora. The vegetation on the islands has always been a key concern of botanists and geographers. In order to quickly obtain the continuous distribution and long-term dynamic changes of vegetation in a large area of ​​the island, the study integrated multi-source high resolution remote sensing data and measured GPS sampling data, spectral data and other auxiliary information. The vegetation types of typical islands in Paracel Islands were identified based on spectral classification, which fusing Support Vector Machine (SVM) and Spectral Information Divergence (SID) two classifiers on decision-making level and generating the typical vegetation distribution maps. A typical vegetation spectrum library of the Paracel Islands was also established using to analyze the characteristics of the measured spectrum and its first derivative of the typical vegetation in the Paracel Islands, enriching the basic information of vegetation in Paracel Islands. The study compared the classification method of SVM+SID and the general Spectral Angle Mapper (SAM) method，then further obtained the accuracy assessment results of each island. Based on the vegetation distribution maps of typical islands in different periods after the accuracy assessment, the statistical change of the area occupied by each vegetation and the correlation analysis of the vegetation diversity of different islands were conducted. The results demonstrating that: (1) The average production accuracy and user accuracy of the spectral classification method (combining SVM and SID classifiers on decision-making level) were 83.49% and 85.54% and Kappa coefficient was 0.8728 of the most whole islands in Paracel Islands. Therefore, the study achieved good performances in identifying different vegetation types on typical islands. (2) From 2002 to 2018, the vegetation types and its areas increased and tended to be stable. Scaevola was prone to form single-superior vegetation community in islands and Sandbank Grass on sands account for a large area; In recent years, vegetation on many islands such as Yagong Island, West Sand, Tree Island, etc., had been artificially interfered, and it had been regularly distributed along buildings, roads in spatial, and the diversity of vegetation species had greatly increased. (3) Through correlation analysis, this study found that the number of vegetation types on each typical island was basically positively correlated with the area of the island, that is, the larger the island area, the richer the plant habitat and the greater the number of species. And the larger the area of the island, the faster the vegetation types increase over time. In addition, the distance between adjacent islands was positively correlated with the similarity of vegetation on the two islands, that is, the closer the distance between the two islands, the more conducive to the mutual penetration of flora and the higher the similarity of vegetation types. But on a long-term scale, the dynamic changes of vegetation in Paracel Islands had been affected by human activities more than other natural factors.

palabra clave

Paracel Islands;spectral classification;vegetation identification and change;Scaevola taccada;number of vegetation types

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