生物多样性 ›› 2018, Vol. 26 ›› Issue (8): 789-806.DOI: 10.17520/biods.2018054

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遥感在生物多样性研究中的应用进展

郭庆华1,2,*(), 胡天宇1,2, 姜媛茜3, 金时超1,2, 王瑞1,2, 关宏灿1,2, 杨秋丽4, 李玉美1,2, 吴芳芳1,2, 翟秋萍1,2, 刘瑾1,2, 苏艳军1,2   

  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 北京城市学院城市建设学部, 北京 100083
    4 新疆大学资源与环境科学学院, 乌鲁木齐 830046
  • 收稿日期:2018-07-22 接受日期:2018-07-24 出版日期:2018-08-20 发布日期:2018-09-27
  • 通讯作者: 郭庆华
  • 作者简介:# 共同第一作者
  • 基金资助:
    国家重点研发计划(2016YFC0500202)和2017年北京高等学校高水平人才交叉培养“实培计划”项目

Advances in remote sensing application for biodiversity research

Qinghua Guo1,2,*(), Tianyu Hu1,2, Yuanxi Jiang3, Shichao Jin1,2, Rui Wang1, Hongcan Guan1,2, Qiuli Yang4, Yumei Li1,2, Fangfang Wu1,2, Qiuping Zhai1,2, Jin Liu1,2, Yanjun Su1,2   

  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 Urban Construction School, Beijing City University, Beijing 100083
    4 College of Resource and Environment Sciences, Xinjiang University, Urumqi 830046
  • Received:2018-07-22 Accepted:2018-07-24 Online:2018-08-20 Published:2018-09-27
  • Contact: Guo Qinghua
  • About author:# Co-first authors

摘要:

随着人口的持续增长, 人类经济活动对自然资源的利用强度不断升级以及全球气候变暖, 全球物种正以前所未有的速度丧失, 生物多样性成为了全球关注的热点问题。传统生物多样性研究以地面调查方法为主, 重点关注物种或样地水平, 但无法满足景观尺度、区域尺度以及全球尺度的生物多样性保护和评估需求。遥感作为获取生物多样性信息的另一种手段, 近年来在生物多样性领域发展迅速, 其覆盖广、序列性以及可重复性等特点使之在大尺度生物多样性监测和制图以及评估方面具有极大优势。本文主要通过文献收集整理, 从观测手段、研究尺度、观测对象和生物多样性关注点等方面综述了遥感在生物多样性研究中的应用现状, 重点分析不同遥感平台的技术优势和局限性, 并探讨了未来遥感在生物多样性研究的应用趋势。遥感平台按观测高度可分为近地面遥感、航空遥感和卫星遥感, 能够获取样地-景观-区域-洲际-全球尺度的生物多样性信息。星载平台在生物多样性研究中应用最多, 航空遥感的应用研究偏少主要受飞行成本限制。近地面遥感作为一个新兴平台, 能够直接观测到物种的个体, 获取生物多样性关注的物种和种群信息, 是未来遥感在生物多样性应用中的发展方向。虽然遥感技术在生物多样性研究中的应用存在一定的局限性, 未来随着传感器发展和多源数据融合技术的完善, 遥感能更好地从多个尺度、全方位地服务于生物多样性保护和评估。

关键词: 卫星遥感, 航空遥感, 近地面遥感, 无人机, 激光雷达

Abstract:

Since rapid human population growth, overconsumption of natural resources by human activities and climate change, loss and extinction of species is increasing, and biodiversity become an important global issue. Traditional ground-based biodiversity researches focus on the species or community, which can not provide necessary information for biodiversity conservation and assessment at a large scale. Since the advantages in spatial coverage and time series, remote sensing is very useful in large-scale biodiversity monitoring, mapping and assessment. According to the height of the platform, remote sensing platforms can be classified into satellite remote sensing, airborne remote sensing and near-surface remote sensing, which can obtain biodiversity information at different spatial scales. The purpose of this study is to review the recent advances of application of different remote sensing platforms for biodiversity research. We focus on the following aspects, such as observation methods, research scale, and analyze advantages and limitations of different remote sensing platforms. Finally, we summary the future application of remote sensing in biodiversity research. From the literature statistics result, we found that satellite platform were used more frequently in biodiversity research than other remote sensing platform. Due to the high flight cost, the biodiversity researches used airborne remote sensing was fewer than the researches used satellite. Near-surface remote sensing includes the UAV platform and the ground-based platform, which is an emerging remote sensing platform and hotspot in remote sensing of biodiversity. Compared to satellite and airborne remote sensing platforms, the near-surface remote sensing platform can directly observe the individuals and can directly obtain information from species or population. Although there are some limitations in these three platforms, we believe that remote sensing technology can better serve biodiversity conservation and assessment from different temporal and spatial scales with the development of remote sensing platforms and the improvement of sensors.

Key words: satellite remote sensing, airborne remote sensing, near-surface remote sensing, UAV, lidar