生物多样性 ›› 2016, Vol. 24 ›› Issue (11): 1249-1266.DOI: 10.17520/biods.2016059

• 中国生物多样性监测与研究网络专题 • 上一篇    下一篇

生物多样性近地面遥感监测: 应用现状与前景展望

郭庆华1*, 刘瑾1, 李玉美1,2, 翟秋萍1,2, 王永财1,2, 吴芳芳1,2, 胡天宇1, 万华伟3, 刘慧明3, 申文明3   

  1. 1 中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
    2 中国科学院大学, 北京 100049
    3 环境保护部卫星环境应用中心, 北京 100094
  • 收稿日期:2016-02-29 修回日期:2016-08-10 出版日期:2016-11-20 发布日期:2016-12-14
  • 通讯作者: 郭庆华
  • 基金资助:

    国家自然科学基金(41471363)、国家重点研发计划(2016YFC0500202)

A near-surface remote sensing platform for biodiversity monitoring: perspectives and prospects

Qinghua Guo1*, Jin Liu1, Yumei Li1,2, Qiuping Zhai1,2, Yongcai Wang1,2, Fangfang Wu1,2, Tianyu Hu1, Huawei Wan3, Huiming Liu3, Wenming Shen3   

  1. 1 State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
    2 University of Chinese Academy of Sciences, Beijing 100049
    3 Satellite Environmental Application Center, Ministry of Environmental Protection, Bejing 100094
  • Received:2016-02-29 Revised:2016-08-10 Online:2016-11-20 Published:2016-12-14
  • Contact: Qinghua Guo

摘要:

近年来中国生物多样性监测与研究网络(Sino BON)建设得到了快速发展, 为我国生物多样性长期监测和研究提供了良好的平台条件。其中, 以激光雷达技术为核心的近地面遥感平台, 作为Sino BON综合监测与管理中心的重要组成部分, 已研发形成了较为成熟的软、硬件技术体系, 可以提供林下地形建模, 林分高度、林分表面结构, 林窗或内部分界线, 郁闭度动态, 植被群落划分、群落内部精细空间结构, 单木高度与胸径, 冠层形态、周长和盖度, 物种识别, 亚米级三维景观图等数字产品, 从而能够为国家相关部门和研究单位开展多种时空尺度的生物多样性监测、评价和保护工作提供精准、高效的技术支持。本文首先介绍了遥感技术在生物多样性研究中的应用发展历史及最新趋势。然后在生物多样性遥感监测直接和间接两种方法研究进展基础之上, 总结了从遥感数据中可提取的重要生物多样性指标, 以及选择不同类型遥感数据源时需要考虑的时空尺度信息。在详细阐述NEON、CEOS、GEO BON等国际合作组织推动遥感技术开展生物多样性监测的过程中指明: 以无人机为代表的近地面遥感平台具有机动灵活、高效低廉和高分辨率的特点, 可在卫星平台、载人航空平台和地面常规调查平台之间架构起生物多样性信息尺度推绎不可或缺的中间桥梁, 将是未来生物多样性监测的一个重要手段。最后, 文章指出: Sino BON近地面遥感平台的逐步建设完善将为我国生物多样性监测提供全方位的立体定量化信息, 在促进我国生物多样性监测网络向跨尺度等级动态系统监测、多源信息集成、智能决策与服务的平台方向发展意义重大。

Abstract:

In recent years, the Chinese Biodiversity Monitoring and Research Network (Sino BON) has developed rapidly, which provides an unprecedented platform for long-term biodiversity monitoring and research. The near-surface remote sensing (NsRS) platform, an important component of the Sino BON-Synthesis (Synthesis Center of Sino BON) and equipped with LiDAR (Light Detection and Ranging) as the core technique, has developed a mature technology system integrating hardware and software, which can provide digital products such as topographic modeling under forest, stand height, stand surface structure, gap or internal boundaries, canopy closure dynamics, vegetation community division, fine spatial structure within the community, individual tree height and diameter at breast height, canopy morphology, circumference and cover, species identification, sub-meter three-dimensional landscape map and so on. Therefore it can be used to acquire multiple spatiotemporal scales of biodiversity observations and offer scientists and managers specialized and effective technical support for biodiversity evaluation and conservation. In this paper, we provide a comprehensive review on the history and recent development of remote sensing technology in biodiversity studies. Then, we summarize the important indices of biodiversity that can be extracted from remote sensing data based on the direct and indirect methods for remote sensing monitoring of biodiversity and suggest spatial and temporal scales that should be referenced against the selection of different types of remote sensing data. Next we describe in detail the application of the state-of-the-art NsRS platform at home and abroad and figure out that the near-surface remote sensing platform represented by unmanned aerial vehicle (UAV), characterized by flexibility, high efficiency, low cost and high resolution, will be an important means for biodiversity monitoring in the near future. Because it can act as an indispensable intermediate bridge between satellite platform, manned aviation platform and ground survey platform when conducting the biodiversity information scaling. Finally, based on currently available techniques and equipment of the NsRS platform, we conclude that further improvement of the platform construction will greatly help us to obtain three-dimensional quantitative habitat information. And it will be a long-term, significant step for the biodiversity observation network in China to have transformed into an intelligent decision and service platform with trans-scale hierarchy dynamic monitoring ability and multi-source information integration technology.