摘要
植被生长峰值不仅是典型的物候节点,也是植被最大生长能力的重要指示参数。本文以中国东北地区为研究区域,基于长时序遥感NDVI数据,采用Mann-Kendall检验法探索植被生长峰值的变化趋势,利用Hurst指数对植被生长峰值进行可持续性分析。结果表明:1)我国东北地区植被生长峰值时间点(POP)和最大生长幅度(PEAK)整体上呈现出波动上升的趋势。植被峰值时间点在东部以及北部阔叶林和草原区域表现为延迟趋势;植被最大生长幅度在中部、北部以及西南部表现为增强趋势,在森林区峰值时间点表现为延迟趋势,生长峰值表现为增强趋势;2)东北地区整体上植被返青开始期(SOS)和生长峰值时间主要以延迟为主,峰值幅度有所升高;3)Hurst指数结果表明,东北地区植被PEAK呈持续增强趋势,仅6.38%的区域与过去呈现相反的变化趋势,植被增强区域主要集中在中部地区。东北地区植被生长峰值变化可持续性研究,可以为评价东北地区植被固碳能力和生态系统功能提供参考。
The peak value of vegetation growth is not only a typical phenological node,but also an important indicator of the maximum growth capacity of vegetation.This paper takes Northeast China as the research area,based on long time series remote sensing NDVI data,uses Mann-Kendall test method to explore the change trend of vegetation growth peak,and uses the Hurst index to analyze the sustainability of vegetation growth peak.The results show that:(1)Peak time point and maximum amplitude of vegetation in Northeast China show a fluctuating upward trend.Peak time point of vegetation shows a delayed trend in the eastern and northern broadleaved forests and grassland areas;The maximum amplitude of vegetation shows an increasing trend in the central,northern and southwestern regions,a delayed trend at the peak time point in the forest area,and an enhanced trend in the peak growth;(2)The vegetation return period(SOS)and peak growth time are mainly delayed in the Northeast as a whole,and the peak amplitude has increased;(3)The results of Hurst index show that the vegetation PEAK in the northeast region shows a continuous increasing trend,and only 6.38%of the areas show an opposite trend to the past.The areas showing increased vegetation are mainly concentrated in the central,eastern and western regions.The study on the sustainability of peak vegetation growth changes in Northeast China can provide a reference for the assessment of vegetation carbon sequestration capacity and ecosystem function in Northeast China.
作者
张瑞欣
李付全
周玉科
王笑影
孙文彬
ZHANG Ruixin;LI Fuquan;ZHOU Yuke;WANG Xiaoying;SUN Wenbin(School of Geoscience and Surveying Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China;Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic and Nature Resources Research,Chinese Academy of Sciences,Beijing 100101,China;No.7 Geological Brigade,Shandong Bureau of Geology and Mineral Resources Exploration and Development,Linyi 276000,China;Institute of Atmospheric Environment,China Meteorological Administration,Shenyang 110166,China)
出处
《测绘与空间地理信息》
2023年第5期25-28,共4页
Geomatics & Spatial Information Technology
基金
国家重点研发计划项目(2018YFB0505301、2016YFC0500103)
沈阳大气环境研究所中央公益性科研院所基本科研业务费(2020SYIAEMS1、2018SYIAEZD3)资助。
