遥感科学与应用技术

草地退化杂类草入侵遥感监测方法研究进展

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  • 1. 环境保护部卫星环境应用中心, 北京 100094;
    2. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室, 北京 100101;
    3. 中国科学院大学, 北京 100049
屈冉(1978-),女,博士,工程师,主要从事生态环境遥感监测研究。E-mail:qrword@126.com

收稿日期: 2012-11-30

  修回日期: 2013-06-28

  网络出版日期: 2013-09-29

基金资助

全国生态环境十年变化遥感调查与评估项目(STSN-14-00);中国科学院西部行动计划项目(KZCX2-XB3-08-01);国家“863”计划项目(2009AA122003)

Progress on Methods of Grassland Degradation and Weed Invasion Monitoring Based on Remote Sensing

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  • 1. Satellite Environment Center, Ministry of Environmental Protection, Beijing 100094, China;
    2. State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2012-11-30

  Revised date: 2013-06-28

  Online published: 2013-09-29

摘要

近年来,受全球气候变暖及日趋频繁的人类活动的共同影响,我国草地生态系统出现了不同程度的退化,成为草地生态学界的研究热点。本文较系统总结了草地退化、杂类草入侵遥感监测方法的应用进展,指出了常规草地退化遥感监测方法的不足,并展望了今后的发展方向。研究发现草地退化在群落尺度上往往表现为优质牧草种类减少,杂类草种类增加。在草地退化过程中,杂类草侵入,往往导致植被覆盖度增加,因而传统的基于植被覆盖度、生产力和产草量下降的草地退化遥感监测方法,无法反映草地退化在植被种群方面的变化特征,尤其是杂类草入侵的草地退化过程。而目前基于高光谱数据的草地退化杂类草入侵监测方法,结合地面光谱测定和对退化草地物种特征微弱光谱差异的定量分析,能有效识别群落中杂类草种类,并反演出占群落的面积比例、高度和盖度等,可为草地退化监测及其治理提供群落演替过程及其态势的重要指标,为草地退化监测提供新的遥感技术方法。

本文引用格式

屈冉, 李双, 徐新良, 王昌佐, 通拉嘎 . 草地退化杂类草入侵遥感监测方法研究进展[J]. 地球信息科学学报, 2013 , 15(5) : 761 -767 . DOI: 10.3724/SP.J.1047.2013.00761

Abstract

Grassland degradation is one of the important ecological problems in China. During recent years, influenced by global warming and increasing human activities, different degrees of grassland degradation have occurred in China, which has become a research focus in the field of grassland ecology. Based on the systematic summary of studies in the grassland degradation and weed invasion in the latest decade, the limitations of traditional methods of monitoring grassland degradation and weed invasion by remote sensing are put forward, and some important study directions and priorities for future are reviewed. Grassland degradation is often shown as decline in species of high quality forage and increase in the number of weed species at the community scale. In the process of grassland degradation, weed species invasion leads to the increase of vegetation coverage. And thus traditional methods of monitoring grassland degradation based on the decrease of vegetation coverage, productivity and grass yield are limited in detecting the change characteristics of plant population, especially the process of weed species invasion. The results of our research show that there exists great limitations in using traditional methods to detect the change characteristics of plant population, but the weed invasion monitoring method using hyper-spectral data can detect the weed species in plant population and retrieve the area proportion, height and coverage, through making full use of the ample spectral information of hyper-spectral data, and integrate field measuring using spectrometer with quantitative analysis of spectral difference of plant population characteristics on grassland degradation. The studies on methods of monitoring grassland degradation and weed invasion using hyper-spectral data can provide important indicators of community succession process and trend for grassland degradation monitoring and treatment. It can also effectively solve the defects in traditional methods of monitoring grassland degradation based on remote sensing and provide new remote sensing methods for monitoring grassland degradation and weed invasion.

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