地理科学进展 ›› 2020, Vol. 39 ›› Issue (3): 454-460.doi: 10.18306/dlkxjz.2020.03.010

• 研究论文 • 上一篇    下一篇

适用于遥感影像的水生态空间多功能分类体系研究

唐寅1, 王中根1,*(), 王婉清1, 黄火键2, 袁勇2   

  1. 1.中国科学院地理科学与资源研究所,中国科学院陆地水循环及地表过程重点实验室,北京 100101
    2.水利部水利水电规划设计总院,北京 100120
  • 收稿日期:2019-04-08 修回日期:2019-10-10 出版日期:2020-03-28 发布日期:2020-05-28
  • 通讯作者: 王中根 E-mail:wangzg@igsnrr.ac.cn
  • 作者简介:唐寅(1986— ),女,贵州贵阳人,助理研究员,主要从事水文水资源研究。E-mail: tangyin@igsnrr.ac.cn
  • 基金资助:
    中国科学院战略性先导科技专项(A类)(XDA19030204)

Multifunctional classification of aquatic habitats for remote sensing data

TANG Yin1, WANG Zhonggen1,*(), WANG Wanqing1, HUANG Huojian2, YUAN Yong2   

  1. 1.Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2.General Institute of Water Resources and Hydropower Planning and Design, Ministry of Water Resources, Beijing 100120, China
  • Received:2019-04-08 Revised:2019-10-10 Online:2020-03-28 Published:2020-05-28
  • Contact: WANG Zhonggen E-mail:wangzg@igsnrr.ac.cn
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences (Class A)(XDA19030204)

摘要:

水生态空间分类体系是研究水生态空间变化的重要前提。目前,水生态空间分类体系一般都基于特定的研究或者管理目的,没有相对统一的划定标准。因此,这些水生态空间分类体系间的可比性及可操作性就存在一定的局限。鉴于此,论文结合遥感观测技术,基于系统论提出了适用于遥感影像的水生态空间多功能分类体系。该分类体系具有一定的理论基础,同时也兼具遥感技术的可操作性和可比性,能为研究水生态空间的面积动态变化提供理论基础和技术保障。此外,研究还结合生产管理经验和专家咨询等方法,建立了适用于Landsat卫星遥感数据的各类水生态空间的解译标志。最后,以中国为例,运用2015年的Landsat卫星遥感数据,划定了中国各类水生态空间的分布,并得到了不同水生态空间类型所占的面积比,这为进一步研究中国水生态空间的演化规律奠定了坚实基础。

关键词: 水生态空间, 遥感影像, 分类体系, 系统论, 多功能

Abstract:

Classification is the key to understanding changes in aquatic habitats. Most of the existing classifications were proposed for different purposes such as specific research and management needs and there are no commonly applied criteria for the classification, thus their operability and comparability are limited. Therefore, the purpose of this study was to propose a multifunctional classification system of aquatic habitats that embraces the advantages of remote sensing data based on the system theory, so that the classification can be practical and comparable. Additionally, this study provided the interpreting marks of different types of aquatic habitats for Landsat remote sensing data. Based on the interpreting marks, this study obtained the spatial distribution and areal ratio of different types of aquatic habitat in China by using the Landsat remote sensing data in 2015. The multifunctional classification of aquatic habitats for remote sensing data is the foundation for understanding changes in aquatic habitats.

Key words: aquatic habitat, remote sensing data, classification, system theory, multifunction