地理科学 ›› 2018, Vol. 38 ›› Issue (7): 997-1011.doi: 10.13249/j.cnki.sgs.2018.07.001

• •    下一篇

森林生态系统遥感监测技术研究进展

何兴元1,2(), 任春颖1, 陈琳1,2, 王宗明1, 郑海峰1   

  1. 1.中国科学院东北地理与农业生态研究所湿地生态与环境重点实验室,吉林 长春 130102
    2.中国科学院大学,北京 100049
  • 收稿日期:2018-06-06 修回日期:2018-07-19 出版日期:2018-07-20 发布日期:2018-07-20
  • 作者简介:

    作者简介:何兴元(1962-),男,辽宁义县人,研究员,博士生导师,主要从事森林生态、城市森林研究。E-mail: hexingyuan@iga.ac.cn

  • 基金资助:
    国家重点研发计划项目(2016YFC0500300)资助

The Progress of Forest Ecosystems Monitoring with Remote Sensing Techniques

Xingyuan He1,2(), Chunying Ren1, Lin Chen1,2, Zongming Wang1, Haifeng Zheng1   

  1. 1.Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-06-06 Revised:2018-07-19 Online:2018-07-20 Published:2018-07-20
  • Supported by:
    The National Key Research and Development Program of China (2016YFC0500300)

摘要:

森林是陆地生态系统的主体,森林生态系统监测技术是实现森林可持续利用与全球变化研究的重要支撑与信息保障。从4个方面概述了遥感技术在森林生态系统监测中的应用研究进展:森林遥感分类及变化监测、森林植被参数遥感反演、森林蓄积量与生物量遥感估算、森林干扰遥感监测等。结合遥感技术的发展,总结了森林生态系统监测中使用的多源遥感数据和各类模型,提出集成地面调查数据、高分地-空雷达扫描监测技术,以及多源光学遥感建模技术和生态系统过程模型,构建多维度、多尺度、高时间密度的森林生态系统监测平台的研究展望。

关键词: 森林分类, 植被参数反演, 生物量估算, 遥感模型耦合, 森林干扰, 集成监测平台

Abstract:

Forest is a main component of the terrestrial ecosystem, and its monitoring is the vital support for sustainable utilization of forest and global change researches. The home and aboard progress of remote sensing techniques application on monitoring forest ecosystems was concluded in this paper from four respects: classification and changes detection, the retrieval of vital ecological parameters of forest ecosystems including tree height, leaf area index, canopy density, etc., the estimation of stand volume and biomass, and disturbance monitoring. After summarized remote sensing data and models used in forest ecosystems monitoring, research prospect of establishment of integrated forest ecosystems monitoring platform with multi-dimension, multi-scale and high time density were put forward, which synthesized filed data, land-to-air high-resolution radar scanning techniques, multi-source optical remote sensing modeling and process models.

Key words: forest classification, vegetation parameters retrieval, biomass estimation, coupling of remote sensing model, forest disturbance, integrated monitoring platform

中图分类号: 

  • F129.9