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红树林生态系统遥感监测研究进展
引用本文:孙永光,赵冬至,郭文永,高阳,苏岫,卫宝泉.红树林生态系统遥感监测研究进展[J].生态学报,2013,33(15):4523-4538.
作者姓名:孙永光  赵冬至  郭文永  高阳  苏岫  卫宝泉
作者单位:1. 国家海洋环境监测中心,大连,116023
2. 奥胡斯大学生物科学学院,奥胡斯8000C丹麦
3. 国家海洋局南海环境监测中心,广州,510300
基金项目:国家自然科学基金资助项目(41201179);海洋公益性行业科研专项(DOME(MEA)-01-03)
摘    要:随着现代遥感技术的迅速发展,遥感监测已经成为红树林生态系统变化监测的重要手段和方法。从遥感技术在生态系统变化监测应用领域入手,综述了国内外红树林遥感监测的发展历程,系统总结了遥感技术在红树林湿地动态、种间分类、群落结构(叶面积指数、冠幅、树高等)、生物量、灾害灾情(病虫害、风暴潮等)、景观格局动态、驱动力、红树林湿地保护与管理等领域应用现状,归纳了不同应用领域遥感监测的理论、方法及研究现状。指出我国在红树林遥感监测中存在的不足。提出红树林遥感监测应在分类标准体系规范化、分类精度提升、红树林生态学特征参数(物种多样性、优势度等)、生态系统环境空间演变过程及遥感监测的尺度效应方面加大研究力度。充分发挥区域综合监测模型在红树林生态系统变化遥感监测中的作用。

关 键 词:红树林  遥感技术  应用领域  展望
收稿时间:2012/5/15 0:00:00
修稿时间:6/9/2013 12:00:00 AM

A review on the application of remote sensing in mangrove ecosystem monitoring
SUN Yongguang,ZHAO Dongzhi,GUO Wenyong,GAO Yang,SU Xiu and WEI Baoquan.A review on the application of remote sensing in mangrove ecosystem monitoring[J].Acta Ecologica Sinica,2013,33(15):4523-4538.
Authors:SUN Yongguang  ZHAO Dongzhi  GUO Wenyong  GAO Yang  SU Xiu and WEI Baoquan
Institution:National Marine Environmental Monitoring Center, Dalian 116023, China;National Marine Environmental Monitoring Center, Dalian 116023, China;Department of Bioscience, Plant Biology, Aarhus University Ole Worms Allé 1, 8000 Aarhus C, Denmark;South China Sea Environmental Monitoring Center, Guangzhou 510300, China;National Marine Environmental Monitoring Center, Dalian 116023, China;National Marine Environmental Monitoring Center, Dalian 116023, China
Abstract:Mangrove trees form a community of woody plants in intertidal areas periodically immersed by sea water, and are located in tropical and sub-tropical zones. Mangrove forests are complicated ecological systems with characteristics of both land and sea, and form coastal ecologically critical areas (ECA). Monitoring ecological parameters of mangrove ecological systems has gained increased attention from governments and scholars. Ground-based investigation can lead to comprehensive understanding of the structure and functions of the mangrove ecosystem. However, because of spatial and temporal limitations, information on ecological changes of mangrove trees over long periods and large regions cannot be obtained in this way. Advancements in modern remote sensing technology, modeling and simulation, and landscape pattern analysis have provided important technological means for discerning spatiotemporal ecological ecosystem changes. In particular, remote sensing has become an important tool for obtaining temporal and spatial dimensions of ecological parameters of the mangrove forest ecological system. Statistics show that by May 2012, a total of 233 academic papers had been published outside China on remote sensing for monitoring mangrove forests, a number which is increasing yearly. This research mainly focuses on dynamic monitoring, inter-species classification, and structural monitoring of those forests. Especially since 2000, structural monitoring of mangrove communities and investigation of their driving forces and other aspects (sea level changes and comprehensive investigations) have become primary research topics. The application of remote sensing to mangrove forest ecosystem monitoring in China began in the 1990s and has been increasing remarkably in recent years, particularly during the period 2008-2011. This paper summarizes the status of such application and current problems. Specifically, the work expounds on the following aspects: 1) Theories and methods of dynamic monitoring of mangrove-covered wetlands. 2) Theories and methods of inter-species classification technology, as well as requirements of image data. In particular, classification of mangrove trees does not rely only on spectral characteristics, but also requires consideration of structural information that helps enhance classification precision. 3) Theories and methods of remote monitoring of structural parameters of mangrove communities (LAI, crown diameter, tree height and others). In addition, investigations of the relationship between the radar backscattering coefficient and crown diameter and vertical structure of mangrove trees, through establishing a model of their quantitative relationships; this facilitates remote monitoring of mangrove forest growth by applying C-band, L-band, P-band, C-VV and C-HH bands of NASA/JPL. 4) Theories and methods of remote monitoring and inversion of primary production of mangrove forests. Comparative analysis shows that the radar backscattering coefficient is more precise than the NDVI model in estimating vegetation biomass. 5) The status of disasters affecting mangrove forests (diseases, insect infestation and storm surges) and of monitoring theories. 6) Remote dynamic monitoring of and comments on the mangrove-covered region and inter-species landscape patterns. 7) Remote sensing of and comments on driving mechanisms of dynamic evolution of mangrove-covered wetlands. 7) Status and methods of application of remote sensing technology in protection and management of mangrove-covered wetlands. This paper points out existing deficiencies and challenges in remote monitoring of elements of the mangrove forest ecosystem, and emphasizes the need for more research into standardization of classification systems and enhancement of classification precision. Also needed is research into parameters of the ecological characteristics of mangrove forests (diversity and species dominance), spatial evolution of the ecological system, and dimensional effects of remote monitoring. Remote monitoring of the mangrove forest ecosystem lags behind in China, so more such studies should be undertaken in the country.
Keywords:mangrove  remote sensing  application fields  outlook
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