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投稿e-mail: jbnuns_sub@bnu.edu.cn

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标题

中国自然植被物候特征遥感分类

作者

郑周涛 朱文泉 周夏飞 张东海 姜涛 王伶俐

机构

北京师范大学地表过程与资源生态国家重点实验室;北京师范大学资源学院

摘要

现有的土地覆盖分类数据以及植被—气候分类或分区数据均未考虑各类型或各分区单元内的植物物候差异,也没有排除各分区单元内受人为干扰强烈的区域,从而不利于单独考察植被物候与气候变化的相互作用关系。本文基于1km分辨率的多年SPOT-VGT归一化差值植被指数(NDVI)时序数据,首先依据植被信号强度、植被季相变化强度以及受人为干扰程度将中国自然植被按物候特征划分为极明显、明显、较明显和其他4个一级类别;并进一步利用能够较好反映NDVI时序数据形状特征的光谱角余弦作为相似性测度方法,根据物候相似性对极明显、明显、较明显这3个一级类别分别聚为9、15、7个二级类别;最后采用7个物候指标的变异系数来评价分类效果。结果表明,同已有的植被—气候分类或分区数据(生物气候区、生态区、植被区划、IGBP土地覆盖分类、生态物候区)相比,本文构建的植被物候二级类别具有更为一致的物候特征,该物候分类结果可为植被物候与气候变化关系研究、陆地生态系统碳循环模拟、植被物候地面监测站点选址提供基础数据和科学依据。

关键词

生态物候区;植被指数;物候;植被区划;分类;遥感

引用

郑周涛,朱文泉,周夏飞, 张东海, 姜涛,王伶俐. 中国自然植被物候特征遥感分类[J]. 北京师范大学学报(自然科学版),2015,51(Sup.1):32-37.

基金

国家自然科学基金面上资助项目(41371389);国家重点基础研究发展计划资助项目(2011CB952001);地表过程与资源生态国家重点实验室 资助项目(2013-ZY-14)

分类号

TP79

DOI

10.16360/j.cnki.jbnuns.2015.s1.005

Title

Phenological characteristics of Chinese natural vegetation as classified from remote sensing data

Author

ZHENG Zhoutao, ZHU Wenquan, ZHOU Xiafei, ZHANG Donghai, JIANG Tao, WANG Lingli

Affiliations

State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University;College of Resources Science and Technology,Beijing Normal University

Abstract

Existing land cover classification data and vegetation-climate classification / zoning data do not reflect heterogeneity of plant phenology in a specific zone unit or class type. Moreover, regions strongly influenced by human disturbance are not excluded from the zone unit so that they are not suitable for investigations of interaction between vegetation phenology and climate change. One km resolution multi-year SPOT-VGT normalized difference vegetation index (NDVI) time-series data were used in the present work to classify phenological characteristics for Chinese natural vegetation into 4 first-level eco-phenoregions according to intensity of vegetation signal, seasonal dynamics of vegetation and degree of anthropogenic disturbance. Since spectral angle cosine distance measurement can better reflect the shape feature of NDVI time series, this paper adopted it as the similarity measurement rule to further cluster the most clear, moderately clear, more clear first-level eco-phenoregions into 9, 15 and 7 second-level eco-phenoregions according to phenological similarity. Coefficients of variation of 7 phenological metrics were used to evaluate derived classification data. Derived second-level eco-phenoregions were found to show more homogeneous phenological characteristics compared to existing vegetation-climate classification / zoning data (i.e., bio-climate zone, eco-regions, vegetation zone, IGBP land cover classification and phenoregions). Derived phenological characteristics classification data could be widely used to investigate relationship between vegetation phenology and climate change, to simulate terrestrial ecosystem carbon cycle, and to select suitable sites for vegetation phenology ground monitoring net.

Key words

eco-phenoregion;vegetation index;phenology;vegetation regionalization;classification;remote sensing

cite

ZHENG Zhoutao, ZHU Wenquan, ZHOU Xiafei, ZHANG Donghai, JIANG Tao, WANG Lingli . Determining the index factor of extension function for Kramers–Kronig relation[J]. Journal of Beijing Normal University(Natural Science),2015,51(Sup.1):32-37.

DOI

10.16360/j.cnki.jbnuns.2015.s1.005

Copyright © 2014 Journal of Beijing Normal University (Natural Science)
Designed by Mr. Sun Chumin. Email: cmsun@mail.bnu.edu.cn